# Radiation Therapy Technology Advances and Mitigation of Subsequent Neoplasms in Childhood Cancer Survivors

Camilla H. Stokkevåg, Neige Journy, Ivan R. Vogelius, Rebecca M. Howell, David Hodgson, Søren M. Bentzen

► To cite this version:

Camilla H. Stokkevåg, Neige Journy, Ivan R. Vogelius, Rebecca M. Howell, David Hodgson, et al. Radiation Therapy Technology Advances and Mitigation of Subsequent Neoplasms in Childhood Cancer Survivors. International Journal of Radiation Oncology, Biology, Physics, 2024, 119 (2), pp.681-696. 10.1016/j.ijrobp.2024.01.206. hal-04615254

HAL Id: hal-04615254

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Submitted on 20 Jun 2024

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<figure><img src="image_1.png" /></figure>
# Radiation Therapy Technology Advances and Mitigation of Subsequent Neoplasms in Childhood Cancer Survivors

Camilla H. Stokkevåg, Neige Journy, Ivan R. Vogelius, Rebecca M. Howell, David Hodgson, Søren M. Bentzen

► To cite this version:

Camilla H. Stokkevåg, Neige Journy, Ivan R. Vogelius, Rebecca M. Howell, David Hodgson, et al. Radiation Therapy Technology Advances and Mitigation of Subsequent Neoplasms in Childhood Cancer Survivors. International Journal of Radiation Oncology, Biology, Physics, 2024, 119 (2), pp.681-696. 10.1016/j.ijrobp.2024.01.206. hal-04615254

HAL Id: hal-04615254

https://hal.science/hal-04615254v1

Submitted on 20 Jun 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
PENTEC VISIONARY REVIEW

# Radiation Therapy Technology Advances and Mitigation of Subsequent Neoplasms in Childhood Cancer Survivors

<figure><img src="image_2.png" /></figure>

Camilla H. Stokkevåg, PhD,*† Neige Journy, PhD,‡ Ivan R. Vogelius, PhD,§ Rebecca M. Howell, PhD,|| David Hodgson, MD, MPH, FRCPC,¶ and Søren M. Bentzen, MSc, PhD, DMSc#

*Department of Oncology and Medical Physics, Haukeland University Hospital, Bergen, Norway; †Department of Physics and Technology, University of Bergen, Bergen, Norway; ‡French National Institute of Health and Medical Research (INSERM) Unit 1018, Centre for Research in Epidemiology and Population Health, Paris Saclay University, Gustave Roussy, Villejuif, France; §Department of Clinical Oncology, Centre for Cancer and Organ Diseases and University of Copenhagen, Copenhagen, Denmark; ||Department of Radiation Oncology, MD Anderson Cancer Center, Houston, Texas; ¶Department of Radiation Oncology, University of Toronto, Princess Margaret Cancer Center, Toronto, Ontario, Canada; and #Department of Epidemiology and Public Health, University of Maryland, Baltimore, Maryland

Received Sep 20, 2023; Accepted for publication Jan 13, 2024

**Purpose:** In this Pediatric Normal Tissue Effects in the Clinic (PENTEC) vision paper, challenges and opportunities in the assessment of subsequent neoplasms (SNs) from radiation therapy (RT) are presented and discussed in the context of technology advancement.

**Methods and Materials:** The paper discusses the current knowledge of SN risks associated with historic, contemporary, and future RT technologies. Opportunities for research and SN mitigation strategies in pediatric patients with cancer are reviewed.

**Results:** Present experience with radiation carcinogenesis is from populations exposed during widely different scenarios. Knowledge gaps exist within clinical cohorts and follow-up; dose-response and volume effects; dose-rate and fractionation effects; radiation quality and proton/particle therapy; age considerations; susceptibility of specific tissues; and risks related to genetic predisposition. The biological mechanisms associated with local and patient-level risks are largely unknown.

**Conclusions:** Future cancer care is expected to involve several available RT technologies, necessitating evidence and strategies to assess the performance of competing treatments. It is essential to maximize the utilization of existing follow-up while planning for prospective data collection, including standardized registration of individual treatment information with linkage across patient databases. © 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

Corresponding author: Camilla H. Stokkevåg, PhD; E-mail: camilla.stokkevag@uib.no

Disclosures: C.H.S. receives funding from the Norwegian Cancer Society (grant 202089) and the Norwegian Childhood Cancer Society (grant 210007). I.R.V. reports institutional research contracts with Varian Medical Systems, Brainlab, and ViewRay. R.M.H. reports the following grant contracts: (1) Howell, Mulrooney, Yasui, Personalized Risk Prediction to Reduce Cardiovascular Disease in Childhood Cancer Survivors, 1R01CA261750-01A1, National Institutes of Health (NIH)/National Cancer Institute (NCI), 7/2022-4/2026; (2) Subcontract principal investigator, Childhood Cancer Survivor Study, U24CA055727, NIH/NCI, principal investigator: Gregory T. Armstrong, 12/1/2021-11/30/2026; (3) principal investigator, Dosimetry for the St. Jude Lifetime Cohort, Research Service Agreement, St. Jude Children's Research Hospital Inc, 7/31/2020-12/31/2025. R.M.H. reports being a member of the American Association of Physicists in Medicine Board of Directors. D.H. reports funding from the Canadian Cancer Society and the Pediatric Oncology Group of Ontario. S.M.B. receives funding through the Maryland Department of Health's Cigarette Restitution Fund Program and by funds through NCI Cancer Center Support Grant P30CA134274; is on the Board of Directors, International Commission of Radiation Units and Measurements; and is chairman of ASTRO Conflicts of Interest Review Committee.

Data Sharing Statement: Research data are not available at this time.
PENTEC VISIONARY REVIEW

# Radiation Therapy Technology Advances and Mitigation of Subsequent Neoplasms in Childhood Cancer Survivors

<figure><img src="image_2.png" /></figure>

Camilla H. Stokkevåg, PhD,*† Neige Journy, PhD,‡ Ivan R. Vogelius, PhD,§ Rebecca M. Howell, PhD,|| David Hodgson, MD, MPH, FRCPC,¶ and Søren M. Bentzen, MSc, PhD, DMSc#

*Department of Oncology and Medical Physics, Haukeland University Hospital, Bergen, Norway; †Department of Physics and Technology, University of Bergen, Bergen, Norway; ‡French National Institute of Health and Medical Research (INSERM) Unit 1018, Centre for Research in Epidemiology and Population Health, Paris Saclay University, Gustave Roussy, Villejuif, France; §Department of Clinical Oncology, Centre for Cancer and Organ Diseases and University of Copenhagen, Copenhagen, Denmark; ||Department of Radiation Oncology, MD Anderson Cancer Center, Houston, Texas; ¶Department of Radiation Oncology, University of Toronto, Princess Margaret Cancer Center, Toronto, Ontario, Canada; and #Department of Epidemiology and Public Health, University of Maryland, Baltimore, Maryland

Received Sep 20, 2023; Accepted for publication Jan 13, 2024

**Purpose:** In this Pediatric Normal Tissue Effects in the Clinic (PENTEC) vision paper, challenges and opportunities in the assessment of subsequent neoplasms (SNs) from radiation therapy (RT) are presented and discussed in the context of technology advancement.

**Methods and Materials:** The paper discusses the current knowledge of SN risks associated with historic, contemporary, and future RT technologies. Opportunities for research and SN mitigation strategies in pediatric patients with cancer are reviewed.

**Results:** Present experience with radiation carcinogenesis is from populations exposed during widely different scenarios. Knowledge gaps exist within clinical cohorts and follow-up; dose-response and volume effects; dose-rate and fractionation effects; radiation quality and proton/particle therapy; age considerations; susceptibility of specific tissues; and risks related to genetic predisposition. The biological mechanisms associated with local and patient-level risks are largely unknown.

**Conclusions:** Future cancer care is expected to involve several available RT technologies, necessitating evidence and strategies to assess the performance of competing treatments. It is essential to maximize the utilization of existing follow-up while planning for prospective data collection, including standardized registration of individual treatment information with linkage across patient databases. © 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

Corresponding author: Camilla H. Stokkevåg, PhD; E-mail: camilla.stokkevag@uib.no

Disclosures: C.H.S. receives funding from the Norwegian Cancer Society (grant 202089) and the Norwegian Childhood Cancer Society (grant 210007). I.R.V. reports institutional research contracts with Varian Medical Systems, Brainlab, and ViewRay. R.M.H. reports the following grant contracts: (1) Howell, Mulrooney, Yasui, Personalized Risk Prediction to Reduce Cardiovascular Disease in Childhood Cancer Survivors, 1R01CA261750-01A1, National Institutes of Health (NIH)/National Cancer Institute (NCI), 7/2022-4/2026; (2) Subcontract principal investigator, Childhood Cancer Survivor Study, U24CA055727, NIH/NCI, principal investigator: Gregory T. Armstrong, 12/1/2021-11/30/2026; (3) principal investigator, Dosimetry for the St. Jude Lifetime Cohort, Research Service Agreement, St. Jude Children's Research Hospital Inc, 7/31/2020-12/31/2025. R.M.H. reports being a member of the American Association of Physicists in Medicine Board of Directors. D.H. reports funding from the Canadian Cancer Society and the Pediatric Oncology Group of Ontario. S.M.B. receives funding through the Maryland Department of Health's Cigarette Restitution Fund Program and by funds through NCI Cancer Center Support Grant P30CA134274; is on the Board of Directors, International Commission of Radiation Units and Measurements; and is chairman of ASTRO Conflicts of Interest Review Committee.

Data Sharing Statement: Research data are not available at this time.
## Introduction

Ionizing radiation is a well-known carcinogen for most human tissues.¹ This carcinogenic effect is evident across all age groups, yet young patients exhibit heightened susceptibility to developing subsequent neoplasms (SNs) after radiation therapy (RT) alone or in conjunction with cytotoxic- or molecular-targeted agents.² This issue is further compounded by the relatively favorable prognosis of many pediatric cancers, putting long-term survivors at risk of developing SNs several decades after initial therapy.³ Among childhood cancer treatment modalities, RT is the most important contributor to SNs in long-term survivors.⁴ Besides the longer life expectancy with extended time for cancer development, children have increased susceptibility because of their growing tissues being more vulnerable to radiation damage. SN poses a significant long-term burden on the lives of children and adolescents treated for cancer. Approximately one-fifth of those treated in recent decades have developed an SN by the age of 50,⁵ whereas the general population's cumulative risk of cancer by the same age remains below 1%.⁶ Compared with siblings, children and adolescents treated with cranial RT have 10 times higher risk of developing an SN of the central nervous system (CNS).⁷ Among girls treated with chest RT, 30% develop breast cancer, a rate comparable to the cumulative incidence among BRCA mutation carriers in the general population.⁸ The application of RT unavoidably exposes normal tissues but varies considerably depending on patient diagnosis and tumor dose prescription as well as on the applied radiation quality and delivery technique.⁹ New RT delivery technologies are being introduced at a historically high rate. Notably, high-conformity photon-based RT and light ion beam therapy have provided hope of enhancing the therapeutic ratio by improving the balance between the effect on the primary malignancy and the risk of inducing toxicities. However, this development has also triggered concern about unknown late effects from the redistribution of dose and secondary stray radiation.¹⁰,¹¹ Additionally, the evolving use of proton therapy is associated with uncertainty in the biological effectiveness, including the occurrence of SNs.¹²,¹³

For individuals who survived childhood cancers for at least 5 years, the median latent period for the onset of SNs varied, with subsequent leukemia showing a median of 8.9 years (range, 5.0-31.1 years), whereas several solid malignancies exhibit a median latency period of over 20 years¹⁴; for example, breast cancer,¹⁵,¹⁶ non-Hodgkin lymphoma,¹⁷ colorectal cancers,¹⁸,¹⁹ lung cancer,¹⁴,²⁰ and thyroid cancer.¹⁴,²¹ Given the swift advancements in RT planning and delivery, it is a note of caution that the extended latent period for SNs reduces our capacity to quantify effects on SN risks with new technologies. This report examines the evidence concerning the relationship between dose distribution and excess risk of SNs. We pinpoint gaps in our knowledge, explore volume effects across different dose levels, and consider variations in carcinogenicity among tissues.

Additionally, we discuss the effect of radiation modality and the importance of other contributing risk factors. Finally, we highlight future research opportunities and priorities, centering on diminishing SNs in survivors of childhood and adolescent cancers through the utilization of technological advancements in RT and multimodal treatment strategies.

## Evolution of RT and Carcinogenesis in Children

### Early experience

Early experience with radiation carcinogenesis of RT in children came from the treatment of several benign diseases.²² After x-ray treatment for thymic enlargement during infancy between 1926 and 1951, a significant excess risk of acute leukemia and thyroid carcinoma was observed. This risk was relative to the incidence in untreated siblings and in the general population of the same age distribution.²³ At follow-up exceeding 40 years, thyroid cancer occurred in 3.8% of 1303 irradiated individuals (mean thyroid dose at 1.3 Gy) and in 0.7% of 1768 nonirradiated siblings.²⁴ Follow-up of 10,834 children treated with single fractions up to 6 Gy for ringworm of the scalp during the 1950s was later found to have a 7-fold higher risk of developing tumors in the CNS compared with matched controls from the general population and untreated siblings.²⁵ Exposures as low as 1 to 2 Gy were associated with a significant relative risk (RR), approaching 20 at doses of 2.5 Gy. The youngest children had a higher risk compared with exposure after the age of 10 years. Excess risk of leukemia occurred within a few years after exposure, whereas an excess of solid tumors was most pronounced after about 15 years of follow-up.²⁶

### Toward conformal RT

Although the carcinogenic effect of radiation exposure has been long known, there were previously no realistic mitigation strategies because of limitations in available technology and alternatives in medicine for cancer treatment. Technology developments throughout past decades have increased the selectivity in irradiated tissues.²⁷ One prominent example is the involved-node RT in patients with Hodgkin lymphoma and the development of new guidelines with reduced fields.²⁸,²⁹ Paradoxically, it was the evolving success of RT and improved pediatric cancer survival³⁰ that actualized the concerns of long-term side effects. Among 14,359 5-year survivors treated from 1970 to 1986 and followed through the Childhood Cancer Survivor Study (CCSS), RT exposure was associated with an RR of SN of 2.7 (95% CI, 2.2-3.3) across all primary cancers and all ages at diagnoses.¹⁴ The considerable improvement in survival rates observed from this era was primarily attributable to reduced mortality from recurrence or progression of the primary
Introduction

Ionizing radiation is a well-known carcinogen for most human tissues.¹ This carcinogenic effect is evident across all age groups, yet young patients exhibit heightened susceptibility to developing subsequent neoplasms (SNs) after radiation therapy (RT) alone or in conjunction with cytotoxic- or molecular-targeted agents.² This issue is further compounded by the relatively favorable prognosis of many pediatric cancers, putting long-term survivors at risk of developing SNs several decades after initial therapy.³ Among childhood cancer treatment modalities, RT is the most important contributor to SNs in long-term survivors.⁴ Besides the longer life expectancy with extended time for cancer development, children have increased susceptibility because of their growing tissues being more vulnerable to radiation damage. SN poses a significant long-term burden on the lives of children and adolescents treated for cancer. Approximately one-fifth of those treated in recent decades have developed an SN by the age of 50,⁵ whereas the general population's cumulative risk of cancer by the same age remains below 1%.⁶ Compared with siblings, children and adolescents treated with cranial RT have 10 times higher risk of developing an SN of the central nervous system (CNS).⁷ Among girls treated with chest RT, 30% develop breast cancer, a rate comparable to the cumulative incidence among BRCA mutation carriers in the general population.⁸ The application of RT unavoidably exposes normal tissues but varies considerably depending on patient diagnosis and tumor dose prescription as well as on the applied radiation quality and delivery technique.⁹ New RT delivery technologies are being introduced at a historically high rate. Notably, high-conformity photon-based RT and light ion beam therapy have provided hope of enhancing the therapeutic ratio by improving the balance between the effect on the primary malignancy and the risk of inducing toxicities. However, this development has also triggered concern about unknown late effects from the redistribution of dose and secondary stray radiation.¹⁰,¹¹ Additionally, the evolving use of proton therapy is associated with uncertainty in the biological effectiveness, including the occurrence of SNs.¹²,¹³

For individuals who survived childhood cancers for at least 5 years, the median latent period for the onset of SNs varied, with subsequent leukemia showing a median of 8.9 years (range, 5.0-31.1 years), whereas several solid malignancies exhibit a median latency period of over 20 years¹⁴; for example, breast cancer,¹⁵,¹⁶ non-Hodgkin lymphoma,¹⁷ colorectal cancers,¹⁸,¹⁹ lung cancer,¹⁴,²⁰ and thyroid cancer.¹⁴,²¹ Given the swift advancements in RT planning and delivery, it is a note of caution that the extended latent period for SNs reduces our capacity to quantify effects on SN risks with new technologies. This report examines the evidence concerning the relationship between dose distribution and excess risk of SNs. We pinpoint gaps in our knowledge, explore volume effects across different dose levels, and consider variations in carcinogenicity among tissues.

Additionally, we discuss the effect of radiation modality and the importance of other contributing risk factors. Finally, we highlight future research opportunities and priorities, centering on diminishing SNs in survivors of childhood and adolescent cancers through the utilization of technological advancements in RT and multimodal treatment strategies.

Evolution of RT and Carcinogenesis in
Children

Early experience

Early experience with radiation carcinogenesis of RT in chil-
dren came from the treatment of several benign diseases.²²
After x-ray treatment for thymic enlargement during
infancy between 1926 and 1951, a significant excess risk of
acute leukemia and thyroid carcinoma was observed. This
risk was relative to the incidence in untreated siblings and
in the general population of the same age distribution.²³ At
follow-up exceeding 40 years, thyroid cancer occurred in
3.8% of 1303 irradiated individuals (mean thyroid dose at
1.3 Gy) and in 0.7% of 1768 nonirradiated siblings.²⁴ Fol-
low-up of 10,834 children treated with single fractions up to
6 Gy for ringworm of the scalp during the 1950s was later
found to have a 7-fold higher risk of developing tumors in
the CNS compared with matched controls from the general
population and untreated siblings.²⁵ Exposures as low as 1
to 2 Gy were associated with a significant relative risk (RR),
approaching 20 at doses of 2.5 Gy. The youngest children
had a higher risk compared with exposure after the age of
10 years. Excess risk of leukemia occurred within a few years
after exposure, whereas an excess of solid tumors was most
pronounced after about 15 years of follow-up.²⁶

Toward conformal RT

Although the carcinogenic effect of radiation exposure has
been long known, there were previously no realistic mitiga-
tion strategies because of limitations in available technology
and alternatives in medicine for cancer treatment. Technol-
ogy developments throughout past decades have increased
the selectivity in irradiated tissues.²⁷ One prominent exam-
ple is the involved-node RT in patients with Hodgkin lym-
phoma and the development of new guidelines with
reduced fields.²⁸,²⁹ Paradoxically, it was the evolving success
of RT and improved pediatric cancer survival³⁰ that actual-
ized the concerns of long-term side effects. Among 14,359
5-year survivors treated from 1970 to 1986 and followed
through the Childhood Cancer Survivor Study (CCSS), RT
exposure was associated with an RR of SN of 2.7 (95% CI,
2.2-3.3) across all primary cancers and all ages at diagno-
ses.¹⁴ The considerable improvement in survival rates
observed from this era was primarily attributable to reduced
mortality from recurrence or progression of the primary
cancer.³¹ Certain initial cancer types, such as leukemia, Hodgkin lymphoma, astrocytoma, and Wilms tumor, showed a reduction in treatment-related mortality with decreased exposure to RT and chemotherapy. However, despite more advanced RT techniques and lower chemotherapy doses, no or very little reduction in treatment-related mortality was reported for tumors such as medulloblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and bone tumors. For certain tumor types, primarily neuroblastoma, there was even an increase in all-cause and treatment-related mortality, presumably due to increased therapeutic intensity. Noticeably, apart from Hodgkin lymphoma survivors, the cumulative incidence of SNs remained unchanged in patients treated in the 1990s compared with those treated earlier.³²

## Intensity modulated RT, volumetric modulated arc therapy, and image guidance

There have been high expectations regarding the ability of intensity modulated RT (IMRT) and volumetric modulated arc therapy (VMAT) to reduce late sequelae.³³ Advances in medical imaging (computed tomography [CT], magnetic resonance imaging, positron emission tomography) have been integral to this process, with better visualization of the gross tumor volume and organs at risk. Despite improved dose conformity from modern RT and image guidance, the use of IMRT and VMAT in children³⁴,³⁵ has remained controversial because of increased volumes of nontarget tissues receiving low doses of radiation (the “low-dose bath”), as well as longer beam-on times increasing normal-tissue exposure to scatter and leakage radiation. Although secondary neutrons are of concern from high-energy photon-based therapy (>10 MV), these energies are rarely used in pediatric RT.³⁴,³⁶ IMRT has now been used routinely for almost 2 decades, but little evidence from clinical studies has been accumulated so far on associated SN risk, especially in pediatric cancer survivors. Published series³⁷ on late toxicities after IMRT in children involve small patient numbers with median follow-up times less than 10 years, mostly with no or inadequate comparator groups in terms of indication, selection biases, and nonstandardized methods of follow-up, and therefore poor capability to assess SN risk.

## Proton therapy

Compared with photon-based therapy, proton therapy generally reduces the integral radiation dose to nontarget tissues. This, in turn, reduces the estimated risk of SNs in children compared with IMRT and VMAT.³⁵,³⁸ Avoiding the low-dose bath associated with IMRT and VMAT became a strong rationale for protons being the RT modality of choice in pediatric radiation oncology (Fig. 1). Whereas passive collimation of the proton beams was the previous standard to shape and modulate treatment fields, new proton facilities have implemented pencil beam scanning (PBS)

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Developments in techniques for craniospinal radiation therapy, from 3-dimensional conformal photon-based radiation therapy (3DCRT) and volumetric modulated arc therapy (VMAT) to proton therapy (PT), have gradually reduced the dose to non-target tissues over time.</figcaption></figure>

to reduce the amount of secondary radiation. Today, thousands of children have received proton RT, but the data available from controlled clinical trials and from prospective cohort studies are still limited.³⁹⁻⁴¹ Most studies to date originated from single institutions with small sample sizes, featuring limitations in terms of standardized and robust follow-up methods, lack of relevant comparator group receiving photon RT, and a too short follow-up for assessing SN risk. In the most recent and largest study of pediatric proton therapy, reporting from the first decade following a retrospective cohort of 1700 children with a median follow-up of 3.3 years (range, 0.1-12.8), the 5-year cumulative incidence of SNs was 0.8%,⁴² with most located within the high-dose region. Compared with SN risk after IMRT,⁴³ the authors concluded with caution that “at least within the first decade following treatment, the stray dose from passive modulation [of protons] and heavy particle RBE [relative biological effectiveness] is not associated with an increased risk of second neoplasms relative to IMRT in children.” A new cohort with record linkage in the United States and Canada has been established to perform the first large-scale systematic comparison of SNs from protons compared with photon-based RT.⁴⁴

## Dose-Distributional Effects

The biological effects related to the absorbed radiation dose depend on the volume distribution in tissue, dose rate and
cancer.31 Certain initial cancer types, such as leukemia, Hodgkin lymphoma, astrocytoma, and Wilms tumor, showed a reduction in treatment-related mortality with decreased exposure to RT and chemotherapy. However, despite more advanced RT techniques and lower chemotherapy doses, no or very little reduction in treatment-related mortality was reported for tumors such as medulloblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and bone tumors. For certain tumor types, primarily neuroblastoma, there was even an increase in all-cause and treatment-related mortality, presumably due to increased therapeutic intensity. Noticeably, apart from Hodgkin lymphoma survivors, the cumulative incidence of SNs remained unchanged in patients treated in the 1990s compared with those treated earlier.32

## Intensity modulated RT, volumetric modulated arc therapy, and image guidance

There have been high expectations regarding the ability of intensity modulated RT (IMRT) and volumetric modulated arc therapy (VMAT) to reduce late sequelae.33 Advances in medical imaging (computed tomography [CT], magnetic resonance imaging, positron emission tomography) have been integral to this process, with better visualization of the gross tumor volume and organs at risk. Despite improved dose conformity from modern RT and image guidance, the use of IMRT and VMAT in children34,35 has remained controversial because of increased volumes of nontarget tissues receiving low doses of radiation (the “low-dose bath”), as well as longer beam-on times increasing normal-tissue exposure to scatter and leakage radiation. Although secondary neutrons are of concern from high-energy photon-based therapy (>10 MV), these energies are rarely used in pediatric RT.34,36 IMRT has now been used routinely for almost 2 decades, but little evidence from clinical studies has been accumulated so far on associated SN risk, especially in pediatric cancer survivors. Published series37 on late toxicities after IMRT in children involve small patient numbers with median follow-up times less than 10 years, mostly with no or inadequate comparator groups in terms of indication, selection biases, and nonstandardized methods of follow-up, and therefore poor capability to assess SN risk.

## Proton therapy

Compared with photon-based therapy, proton therapy generally reduces the integral radiation dose to nontarget tissues. This, in turn, reduces the estimated risk of SNs in children compared with IMRT and VMAT.35,38 Avoiding the low-dose bath associated with IMRT and VMAT became a strong rationale for protons being the RT modality of choice in pediatric radiation oncology (Fig. 1). Whereas passive collimation of the proton beams was the previous standard to shape and modulate treatment fields, new proton facilities have implemented pencil beam scanning (PBS)

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Developments in techniques for craniospinal radiation therapy, from 3-dimensional conformal photon-based radiation therapy (3DCRT) and volumetric modulated arc therapy (VMAT) to proton therapy (PT), have gradually reduced the dose to non-target tissues over time.</figcaption></figure>

to reduce the amount of secondary radiation. Today, thousands of children have received proton RT, but the data available from controlled clinical trials and from prospective cohort studies are still limited.39-41 Most studies to date originated from single institutions with small sample sizes, featuring limitations in terms of standardized and robust follow-up methods, lack of relevant comparator group receiving photon RT, and a too short follow-up for assessing SN risk. In the most recent and largest study of pediatric proton therapy, reporting from the first decade following a retrospective cohort of 1700 children with a median follow-up of 3.3 years (range, 0.1-12.8), the 5-year cumulative incidence of SNs was 0.8%,42 with most located within the high-dose region. Compared with SN risk after IMRT,43 the authors concluded with caution that “at least within the first decade following treatment, the stray dose from passive modulation [of protons] and heavy particle RBE [relative biological effectiveness] is not associated with an increased risk of second neoplasms relative to IMRT in children.” A new cohort with record linkage in the United States and Canada has been established to perform the first large-scale systematic comparison of SNs from protons compared with photon-based RT.44

## Dose-Distributional Effects

The biological effects related to the absorbed radiation dose depend on the volume distribution in tissue, dose rate and
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Factors affecting the risks of subsequent neoplasms. The influence of radiation therapy depends on the total dose, dose distribution, fractionation and type of radiation, and other treatments. At the patient-level, age, sex, hormonal factors, and genetic predispositions are nonmodifiable, whereas lifestyle factors may be considered. Radiation therapy and systemic, targeted cancer treatments are changing with technology, with a direct effect on the overall risk of subsequent neoplasms.</figcaption></figure>

fractionation scheme, radiation quality, type of exposed tissue, and endpoint. Other contributors that affect the SN risk include combined treatments and lifestyle, as well as host-specific factors such as age and genetic susceptibility (Fig. 2).

**Dose-response relationship of subsequent neoplasms**

Cancer risks after radiation exposures to low and moderate doses are relatively well documented, mainly through the lifelong follow-up in the life span study (LSS) of atomic bomb survivors in Japan (approximately <2.5 Gy). Considering RT, not many children have been followed after the age of 50 years when the cancer risks of the general population increase sharply. There is subsequently uncertainty related to the overall SN burden from RT, including the shape of the dose-response relationship over the very wide dose range of in-field and out-of-field exposures as well as potential volume effects and influence of dose fractionation. The combined effect of cell inactivation, mutation rate, and repopulation effects³⁴,⁴⁵ potentially introduces a downturn of the dose-response curve at higher doses.⁴⁶⁻⁴⁹ However, such a deviation from the linear dose-risk relationship at high doses has only been consistently documented for thyroid cancer,⁵⁰ whereas for other SN histologies, a linear dose-risk relationship has been observed in the vast majority

of clinical studies.⁴,⁵¹ Inskip et al⁴ provided a comprehensive review of SNs reported by the CCSS in long-term survivors followed for 20 years, with linear dose-risk relationships for all SNs including sarcoma, skin, meningioma, salivary glands, glioma, and breast, again, with the exception of thyroid cancer. Berrington de Gonzalez et al⁵¹ found that in 26 of the 28 studies published up to 2013, there was no evidence of a decrease or even a plateau in risk at high doses (absorbed organ doses >5 Gy) from RT. It is, however, important to note that the number of SN cases detected at doses >30 Gy has in general been too low to demonstrate any departure from linearity at such dose levels. Results from the French CCSS indicated a possible downturn in the curvature of the dose-response >25 to 30 Gy in risk of meningioma after childhood cancer,⁵² whereas a larger pooled case-control analysis could not confirm this.⁵³ The newly conducted pediatric normal tissue effects in the clinic (PENTEC) analysis supports a linear dose response for the investigated SNs (Fig. 3). This is intriguing, particularly because it suggests that optimizing conformality around the target volume to restrict the high-dose volume emerges as a promising strategy for mitigating the risk of SNs after RT. The excess relative risk (ERR) of subsequent meningioma was found to have the steepest dose-response, with ERR/Gy at 0.44 (95% CI, 0.19-0.68) for all ages combined, whereas sarcomas and SN of the lung and malignant CNS neoplasms resulted in shallower dose-responses. The ERR/Gy was
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Factors affecting the risks of subsequent neoplasms. The influence of radiation therapy depends on the total dose, dose distribution, fractionation and type of radiation, and other treatments. At the patient-level, age, sex, hormonal factors, and genetic predispositions are nonmodifiable, whereas lifestyle factors may be considered. Radiation therapy and systemic, targeted cancer treatments are changing with technology, with a direct effect on the overall risk of subsequent neoplasms.</figcaption></figure>

fractionation scheme, radiation quality, type of exposed tissue, and endpoint. Other contributors that affect the SN risk include combined treatments and lifestyle, as well as host-specific factors such as age and genetic susceptibility (Fig. 2).

**Dose-response relationship of subsequent neoplasms**

Cancer risks after radiation exposures to low and moderate doses are relatively well documented, mainly through the lifelong follow-up in the life span study (LSS) of atomic bomb survivors in Japan (approximately <2.5 Gy). Considering RT, not many children have been followed after the age of 50 years when the cancer risks of the general population increase sharply. There is subsequently uncertainty related to the overall SN burden from RT, including the shape of the dose-response relationship over the very wide dose range of in-field and out-of-field exposures as well as potential volume effects and influence of dose fractionation. The combined effect of cell inactivation, mutation rate, and repopulation effects³⁴,⁴⁵ potentially introduces a downturn of the dose-response curve at higher doses.⁴⁶⁻⁴⁹ However, such a deviation from the linear dose-risk relationship at high doses has only been consistently documented for thyroid cancer,⁵⁰ whereas for other SN histologies, a linear dose-risk relationship has been observed in the vast majority

of clinical studies.⁴,⁵¹ Inskip et al⁴ provided a comprehensive review of SNs reported by the CCSS in long-term survivors followed for 20 years, with linear dose-risk relationships for all SNs including sarcoma, skin, meningioma, salivary glands, glioma, and breast, again, with the exception of thyroid cancer. Berrington de Gonzalez et al⁵¹ found that in 26 of the 28 studies published up to 2013, there was no evidence of a decrease or even a plateau in risk at high doses (absorbed organ doses >5 Gy) from RT. It is, however, important to note that the number of SN cases detected at doses >30 Gy has in general been too low to demonstrate any departure from linearity at such dose levels. Results from the French CCSS indicated a possible downturn in the curvature of the dose-response >25 to 30 Gy in risk of meningioma after childhood cancer,⁵² whereas a larger pooled case-control analysis could not confirm this.⁵³ The newly conducted pediatric normal tissue effects in the clinic (PENTEC) analysis supports a linear dose response for the investigated SNs (Fig. 3). This is intriguing, particularly because it suggests that optimizing conformality around the target volume to restrict the high-dose volume emerges as a promising strategy for mitigating the risk of SNs after RT. The excess relative risk (ERR) of subsequent meningioma was found to have the steepest dose-response, with ERR/Gy at 0.44 (95% CI, 0.19-0.68) for all ages combined, whereas sarcomas and SN of the lung and malignant CNS neoplasms resulted in shallower dose-responses. The ERR/Gy was
<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Radiation dose-response of the excess relative risk of subsequent neoplasms from the PENTEC analysis of radiation-induced meningiomas, malignant brain tumors, lung cancers, and sarcomas, including 95% CIs. Dose-response of secondary thyroid cancer as reported by Bhatti et al.⁵⁰</figcaption></figure>

0.045 (0.023-0.067) for sarcomas, 0.068 (0.03-0.11) for SN of the lung, and 0.15 (0.11-0.18) for malignant CNS neoplasms.⁵⁴ The meninges are thus considered highly susceptible to SNs, notably with significantly steeper dose-response for young individuals treated before the age of 10 years.⁵³

**Low-to-moderate dose exposures**

Cohorts of pediatric patients treated with nonconformal or conformal RT have demonstrated that, in addition to the increased risks observed close to the treated volume, SN can
<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Radiation dose-response of the excess relative risk of subsequent neoplasms from the PENTEC analysis of radiation-induced meningiomas, malignant brain tumors, lung cancers, and sarcomas, including 95% CIs. Dose-response of secondary thyroid cancer as reported by Bhatti et al.⁵⁰</figcaption></figure>

0.045 (0.023-0.067) for sarcomas, 0.068 (0.03-0.11) for SN of the lung, and 0.15 (0.11-0.18) for malignant CNS neoplasms.⁵⁴ The meninges are thus considered highly susceptible to SNs, notably with significantly steeper dose-response for young individuals treated before the age of 10 years.⁵³

**Low-to-moderate dose exposures**

Cohorts of pediatric patients treated with nonconformal or conformal RT have demonstrated that, in addition to the increased risks observed close to the treated volume, SN can
<figure><img src="image_6.png" /><figcaption>**Fig. 4.** In-field radiation exposure includes a high-dose region with the target volume and surrounding dose gradients and low-to-moderate doses to surrounding normal tissues, hereunder the “low-dose bath” associated with multiple beam angles. Dose distributions include photon-based arc (volumetric modulated arc therapy; VMAT) and proton therapy (PT) delivered by 2 fields and through arc.</figcaption></figure>

develop in the low-to-moderate dose regions, especially when highly radiosensitive tissues are involved, for example, leukemia, sarcoma, meningioma, and thyroid cancer. In a cohort of 4600 patients treated in the past decades, Diallo et al⁵⁵ found 1 of 4 SNs in the low-to-moderate dose regions (median dose, 0.3 Gy; median follow-up, 15 years). With modern RT techniques, particularly IMRT and VMAT, we can expect a reduction in SN risk for critical tissues located near the treated volume but an increased proportion of SN developing in tissues distant to the tumor because of larger low-to-moderate dose volumes from using an extended number of beams. Now, epidemiologic data on SN risk after IMRT or proton RT remain very limited to confirm or invalidate this hypothesis because of insufficient population sizes and/or too short follow-up times to detect SN. Although IMRT is associated with improved dose gradients and larger low-to-moderate dose volumes than past RT techniques, very few studies have assessed the effect of the dose-volume distributions on SN risk.⁵⁶⁻⁵⁸ These past studies found little evidence of volume effects, but this could be a result of limited individual variability of the highly standardized (mostly nonconformal) treatment plans. With the rapidly evolving RT delivery techniques, an expanding number of beams, including proton arcs, will likely become commonplace shortly.⁵⁹ The increased flexibility, particularly in proton beam delivery, will provide improved selectivity across tissues receiving low-to-moderate doses.⁶⁰ To enable meaningful optimization concerning SNs, reliable dose responses are prerequisites, and the updated PENTEC data

come with opportunities toward incorporating SN in treatment planning objectives.

## Out-of-field dose and imaging

Beyond the in-field low-to-moderate dose exposures arising from contemporary techniques delivered by multiple fields or arcs, there is an additional low-dose region of stray radiation, including secondary produced and scattered particles in the patient as well as leakage radiation from the treatment machine (Fig. 4). During passively scattered proton RT this is typically below 500 mSv for an entire treatment of craniospinal irradiation.⁶¹ In passively scattered proton therapy, neutron dose to the patient arises from interactions of the protons with high-Z materials in the beam line (external neutrons) and in the patients’ low-Z tissues (internal neutrons). The PBS techniques avoid most of the materials in the beamline, virtually eliminating external neutrons and thereby greatly reducing the overall dose from secondary neutrons.⁶²,⁶³ In the case of low energy photon-based therapy (<10 MV) there are no neutrons; however, there is a significant exit dose, which can be orders of magnitude greater than the secondary neutron dose even from passive scatter proton therapy.⁶⁴

Low-dose concerns also extend to the growing use of radiologic imaging.⁶⁵ Despite a slight reduction over time in number of CT procedures in pediatric patients, up to 7% of CT examinations in high-income countries are performed
<figure><img src="image_6.png" /><figcaption>**Fig. 4.** In-field radiation exposure includes a high-dose region with the target volume and surrounding dose gradients and low-to-moderate doses to surrounding normal tissues, hereunder the “low-dose bath” associated with multiple beam angles. Dose distributions include photon-based arc (volumetric modulated arc therapy; VMAT) and proton therapy (PT) delivered by 2 fields and through arc.</figcaption></figure>

develop in the low-to-moderate dose regions, especially when highly radiosensitive tissues are involved, for example, leukemia, sarcoma, meningioma, and thyroid cancer. In a cohort of 4600 patients treated in the past decades, Diallo et al⁵⁵ found 1 of 4 SNs in the low-to-moderate dose regions (median dose, 0.3 Gy; median follow-up, 15 years). With modern RT techniques, particularly IMRT and VMAT, we can expect a reduction in SN risk for critical tissues located near the treated volume but an increased proportion of SN developing in tissues distant to the tumor because of larger low-to-moderate dose volumes from using an extended number of beams. Now, epidemiologic data on SN risk after IMRT or proton RT remain very limited to confirm or invalidate this hypothesis because of insufficient population sizes and/or too short follow-up times to detect SN. Although IMRT is associated with improved dose gradients and larger low-to-moderate dose volumes than past RT techniques, very few studies have assessed the effect of the dose-volume distributions on SN risk.⁵⁶⁻⁵⁸ These past studies found little evidence of volume effects, but this could be a result of limited individual variability of the highly standardized (mostly nonconformal) treatment plans. With the rapidly evolving RT delivery techniques, an expanding number of beams, including proton arcs, will likely become commonplace shortly.⁵⁹ The increased flexibility, particularly in proton beam delivery, will provide improved selectivity across tissues receiving low-to-moderate doses.⁶⁰ To enable meaningful optimization concerning SNs, reliable dose responses are prerequisites, and the updated PENTEC data

come with opportunities toward incorporating SN in treatment planning objectives.

## Out-of-field dose and imaging

Beyond the in-field low-to-moderate dose exposures arising from contemporary techniques delivered by multiple fields or arcs, there is an additional low-dose region of stray radiation, including secondary produced and scattered particles in the patient as well as leakage radiation from the treatment machine (Fig. 4). During passively scattered proton RT this is typically below 500 mSv for an entire treatment of craniospinal irradiation.⁶¹ In passively scattered proton therapy, neutron dose to the patient arises from interactions of the protons with high-Z materials in the beam line (external neutrons) and in the patients’ low-Z tissues (internal neutrons). The PBS techniques avoid most of the materials in the beamline, virtually eliminating external neutrons and thereby greatly reducing the overall dose from secondary neutrons.⁶²,⁶³ In the case of low energy photon-based therapy (<10 MV) there are no neutrons; however, there is a significant exit dose, which can be orders of magnitude greater than the secondary neutron dose even from passive scatter proton therapy.⁶⁴

Low-dose concerns also extend to the growing use of radiologic imaging.⁶⁵ Despite a slight reduction over time in number of CT procedures in pediatric patients, up to 7% of CT examinations in high-income countries are performed
in children.⁶⁶,⁶⁷ Recently, a large-scale multicenter study (EPI-CT) investigated the risk of hematological malignancies after exposure from CT examinations in childhood and young adulthood.⁶⁷ The results revealed a clear dose-response relationship, indicating an increased risk of hematological malignancies at doses as low as 10 to 15 mGy. In terms of absolute risk, if 10,000 children undergo a typical CT examination (with an average dose of 8 mGy to the active bone marrow), it is anticipated that 1.4 cases of CT radiation-induced malignancy would occur in the 12 years after the examination.⁶⁷ Pediatric patients with cancer, because of numerous diagnostic, treatment, and follow-up examinations, represent a vulnerable group exposed to additional risks, potentially extending throughout lifelong surveillance. Given that certain pediatric patients with cancer may be more susceptible to radiation carcinogenesis, it is crucial to actively monitor and assess the associated risk with follow-up examinations, and to implement measures to minimize such risk.

Daily imaging is a prerequisite of high-conformity radiation techniques, in which the use of kV energies is preferred in children rather than MV modalities.⁶⁸ Cone beam CT for position verification can be achieved at 0.5 to 1 mGy, which for a full treatment would be well below expected out-of-field treatment exposure.⁶⁹ Ultimately, the desire to keep added exposure from imaging as low as possible must be weighed against the considerable benefit of high-conformity RT. It is furthermore important to note that pediatric patients should have adapted imaging protocols distinguished from adult patients. The default imaging protocols as set by manufacturers are primarily tailored for adults, and their application in children can result in doses 2 to 3 times higher than those in adults.⁶⁹ This becomes especially crucial in settings where pediatric patients receive treatment within a larger department predominantly serving adults.

## Dose-time fractionation effects

Variations in the period over which the exposure occurs have been widely used to optimize the therapeutic ratio but have also been shown to have a clear effect on carcinogenic potential.⁷⁰,⁷¹ Berrington de Gonzalez et al⁵¹ demonstrated that ERR/Gy after fractionated high-dose RT (maximum absorbed dose in the cohorts >5 Gy) was 5- to 10-fold lower for most SNs compared with the acute lower-dose exposure experienced by the Japanese atomic bomb survivors (absorbed dose <2 Gy). This varied according to the second cancer site, and even by cancer subtype, such as across meningiomas and gliomas. The occurrence of SNs in patients treated for rectal cancer (7% in 1599 patients followed at a median 6.5 years after therapy; range, 1-18 years) tended toward a lower rate of SNs in a group receiving conventional fractionation (30 × 2 Gy) versus short-term RT with higher dose fractions (5 × 5 Gy).⁷² These findings are somewhat in contradiction to a concern of cellular

repopulation adversely affecting SN risk.⁷³,⁷⁴ Given the limited SN data related to fractionation, this topic clearly represents a considerable knowledge gap.

## Risk Modifiers and Risk Mitigation

### Age at exposure

Elevated risks associated with decreasing age at exposure have been observed within a broad range of RT doses,⁷,²⁵ as well as in the LSS cohort.⁷⁵ In a pooled cohort of 28,000 infants who received radium treatment for hemangiomas, the ERR/Gy of brain cancer was 4.5 for exposure before the age of 5 months⁷⁶ compared with 0.4 if the treatment was administered later than age 7 months.⁷⁷ Among various cohorts, a particularly striking influence of age at exposure has been found for the thyroid and may be explained by an increased radiosensitivity during rapid cell proliferation in the developing thyroid gland in young individuals.⁷⁶ There is also clear evidence for age-dependent ERR of meningioma.⁵³ In the pooled case-control analysis, the excess odds ratios per gray were 2.20 (0.87-6.31) for RT before the age of 10 years and 0.57 (0.18-1.91) if treated after the age of 10. For second primary glioma, an effect of age at exposure was not demonstrated. Although the LSS indicated no significant effect of age at exposure for glioma, it reported a decreasing ERR with increasing age at exposure for schwannoma.⁷⁸ For SN of the breast, the LSS showed an increasing ERR with increasing age at exposure before menarche and then a decreasing risk with increasing age at exposure after menarche.⁷⁹ However, this result was not confirmed by the CCSS.¹⁵ Interpretation of these variations across studies and SN histologies is challenging because of differing follow-up times and the prevalence of genetic predisposing factors among patient subgroups.⁷,⁵²

## Effect of RT in combined treatments

Several chemotherapy drugs are recognized for elevating the risk of subsequent leukemia and solid tumors.⁸⁰ The use of RT to treat childhood cancers has declined over time, accompanied by changes in both the types and dosages of prescribed chemotherapies.⁸¹ In the CCSS, chemotherapy-only survivors had almost a threefold risk of SNs compared with the general population.⁸¹ The RR of leukemia was 1.4 to 2.2 after use of alkylating agents in the CCSS cohort, whereas the National Health Service Central Register in England and Wales reported the risk increasing 7-fold after the use of anthracycline-based chemotherapy. A Dutch cohort of 6165 5-year survivors of childhood cancers found a cumulative incidence of all SN at 3.9% by 25 years after chemotherapy.⁸² In this cohort, the excess absolute risk (EAR) for subsequent solid cancers increased with time since childhood cancer, while the hematologic malignancies peaked at 5 to 9 years. After adjusting for RT use, treatment
in children.⁶⁶,⁶⁷ Recently, a large-scale multicenter study (EPI-CT) investigated the risk of hematological malignancies after exposure from CT examinations in childhood and young adulthood.⁶⁷ The results revealed a clear dose-response relationship, indicating an increased risk of hematological malignancies at doses as low as 10 to 15 mGy. In terms of absolute risk, if 10,000 children undergo a typical CT examination (with an average dose of 8 mGy to the active bone marrow), it is anticipated that 1.4 cases of CT radiation-induced malignancy would occur in the 12 years after the examination.⁶⁷ Pediatric patients with cancer, because of numerous diagnostic, treatment, and follow-up examinations, represent a vulnerable group exposed to additional risks, potentially extending throughout lifelong surveillance. Given that certain pediatric patients with cancer may be more susceptible to radiation carcinogenesis, it is crucial to actively monitor and assess the associated risk with follow-up examinations, and to implement measures to minimize such risk.

Daily imaging is a prerequisite of high-conformity radiation techniques, in which the use of kV energies is preferred in children rather than MV modalities.⁶⁸ Cone beam CT for position verification can be achieved at 0.5 to 1 mGy, which for a full treatment would be well below expected out-of-field treatment exposure.⁶⁹ Ultimately, the desire to keep added exposure from imaging as low as possible must be weighed against the considerable benefit of high-conformity RT. It is furthermore important to note that pediatric patients should have adapted imaging protocols distinguished from adult patients. The default imaging protocols as set by manufacturers are primarily tailored for adults, and their application in children can result in doses 2 to 3 times higher than those in adults.⁶⁹ This becomes especially crucial in settings where pediatric patients receive treatment within a larger department predominantly serving adults.

## Dose-time fractionation effects

Variations in the period over which the exposure occurs have been widely used to optimize the therapeutic ratio but have also been shown to have a clear effect on carcinogenic potential.⁷⁰,⁷¹ Berrington de Gonzalez et al⁵¹ demonstrated that ERR/Gy after fractionated high-dose RT (maximum absorbed dose in the cohorts >5 Gy) was 5- to 10-fold lower for most SNs compared with the acute lower-dose exposure experienced by the Japanese atomic bomb survivors (absorbed dose <2 Gy). This varied according to the second cancer site, and even by cancer subtype, such as across meningiomas and gliomas. The occurrence of SNs in patients treated for rectal cancer (7% in 1599 patients followed at a median 6.5 years after therapy; range, 1-18 years) tended toward a lower rate of SNs in a group receiving conventional fractionation (30 × 2 Gy) versus short-term RT with higher dose fractions (5 × 5 Gy).⁷² These findings are somewhat in contradiction to a concern of cellular

repopulation adversely affecting SN risk.⁷³,⁷⁴ Given the limited SN data related to fractionation, this topic clearly represents a considerable knowledge gap.

## Risk Modifiers and Risk Mitigation

### Age at exposure

Elevated risks associated with decreasing age at exposure have been observed within a broad range of RT doses,⁷,²⁵ as well as in the LSS cohort.⁷⁵ In a pooled cohort of 28,000 infants who received radium treatment for hemangiomas, the ERR/Gy of brain cancer was 4.5 for exposure before the age of 5 months⁷⁶ compared with 0.4 if the treatment was administered later than age 7 months.⁷⁷ Among various cohorts, a particularly striking influence of age at exposure has been found for the thyroid and may be explained by an increased radiosensitivity during rapid cell proliferation in the developing thyroid gland in young individuals.⁷⁶ There is also clear evidence for age-dependent ERR of meningioma.⁵³ In the pooled case-control analysis, the excess odds ratios per gray were 2.20 (0.87-6.31) for RT before the age of 10 years and 0.57 (0.18-1.91) if treated after the age of 10. For second primary glioma, an effect of age at exposure was not demonstrated. Although the LSS indicated no significant effect of age at exposure for glioma, it reported a decreasing ERR with increasing age at exposure for schwannoma.⁷⁸ For SN of the breast, the LSS showed an increasing ERR with increasing age at exposure before menarche and then a decreasing risk with increasing age at exposure after menarche.⁷⁹ However, this result was not confirmed by the CCSS.¹⁵ Interpretation of these variations across studies and SN histologies is challenging because of differing follow-up times and the prevalence of genetic predisposing factors among patient subgroups.⁷,⁵²

## Effect of RT in combined treatments

Several chemotherapy drugs are recognized for elevating the risk of subsequent leukemia and solid tumors.⁸⁰ The use of RT to treat childhood cancers has declined over time, accompanied by changes in both the types and dosages of prescribed chemotherapies.⁸¹ In the CCSS, chemotherapy-only survivors had almost a threefold risk of SNs compared with the general population.⁸¹ The RR of leukemia was 1.4 to 2.2 after use of alkylating agents in the CCSS cohort, whereas the National Health Service Central Register in England and Wales reported the risk increasing 7-fold after the use of anthracycline-based chemotherapy. A Dutch cohort of 6165 5-year survivors of childhood cancers found a cumulative incidence of all SN at 3.9% by 25 years after chemotherapy.⁸² In this cohort, the excess absolute risk (EAR) for subsequent solid cancers increased with time since childhood cancer, while the hematologic malignancies peaked at 5 to 9 years. After adjusting for RT use, treatment
with alkylating agents and anthracyclines was associated
with SNs of the breast, sarcoma, lung, stomach, and pan-
creas.⁸² Although the declining use of chest RT in female
patients with childhood cancer has contributed to reducing
the occurrence of SN in the breast, there is a growing con-
cern related to the risk from chemotherapy agents.⁸³ In par-
ticular, the contribution of anthracycline exposure is a
concern.⁸⁴ Furthermore, methotrexate has been found to
increase the risk of meningioma, although no clear dose-
response relationship has been found and there is no
reported interaction with RT.⁵³ An increased risk of thyroid
cancer was reported among patients in the CCSS cohort
treated with a combination of chemotherapy and RT (RR
was 1.8-2.4) but not if chemotherapy was administered
alone.⁸⁰ A French study including 4338 5-year survivors
with an average follow-up of 27 years concluded that the
risk of SN of the thyroid should be assessed in combination
with chemotherapy, splenectomy, RT dose to the pituitary
gland, and body mass index.⁸⁵

The use of growth hormone therapy has in some studies shown an increased risk in SNs but with diminishing incidence for increasing follow-up time. The risk of meningioma was not found to increase in children receiving recombinant human growth hormones alongside brain RT.⁸⁶ Moreover, immunotherapy has not been applied in the first-line treatment of pediatric cancer, although several types have been approved for clinical use in children. Heudel et al⁸⁷ investigated the effect of immune checkpoint inhibitors on SNs and found that immunotherapy alone or in combination with chemotherapies was associated with a reduced SN incidence across all ages and cancer types. Given the considerable observed effects on SN from RT and combined treatments, approaches integrating the mutual effects of these risk contributors have substantial potential from the standpoint of optimizing and reducing the risk of SNs.

Mitigation strategies

Beyond minimizing SN risk from treatments, there is a
strong rationale for managing the overall risk of SNs. The
myriad of contributing causes at play in cancer development
provides an opportunity to reduce the background risk by
adjusting modifiable behavioral and lifestyle factors.⁸⁸ Lead-
ing risk factors for attributable cancer deaths are currently
smoking, followed by alcohol use and high body mass
index.⁸⁹ Moreover, as an example, smoking interacts multi-
plicatively with RT related to the risk of developing lung
cancer.⁹⁰ Considering that environmental and lifestyle fac-
tors could be a contributor in as many as 90% of all cancers
in the general population, the potential of adjusting this
background risk is extensive.⁹¹ Patient awareness of risk and
mitigation strategies is therefore crucial. This is within the
scope of the International Late Effects of Childhood Cancer
Guideline Harmonization Group, a worldwide collaboration
developing common guidelines for long-term follow-up and

surveillance of chronic health problems and subsequent
cancers in young cancer survivors.⁹²

Cancer screening has contributed to decreasing the mor-
bidity and mortality of cancer.⁹³ With 8.5% of pediatric can-
cers caused by genetic susceptibility,⁹⁴ it is crucial to identify
individuals who may benefit from early screening programs.
Well-known examples are carriers with BRCA mutations at
elevated risk of having breast cancer.⁹³ With the relatively
high mortality rate of SN of the breast,⁸ early detection in
this group is associated with favorable outcomes. Recently,
female childhood cancer survivors were shown to have
more than 2-fold increased risk of SN of the breast after
anthracycline-based chemotherapy (doxorubicin cumulative
dose ≥200 mg/m²),⁸⁴ suggesting a potential for including
these patients in forthcoming surveillance guidelines. Fur-
thermore, young women treated with chest RT have an
increased risk of breast cancer with incidence 13% to 20%
by age 40 to 45.⁹⁵ Significant gaps persist in our understand-
ing of the interplay between genetic susceptibility and treat-
ment factors related to SN risks.⁹⁶ Although this combined
information holds great promise for enhancing future preci-
sion screening strategies, further research is warranted to
determine the treatment dose levels and host-specific factors
that should prompt the initiation of surveillance programs.
In addition, such investigations should be supplemented by
an assessment of potential harms and benefits related to life-
long surveillance.

Because of the effect of age at exposure, postponed RT is
sometimes considered in very young patients. For instance,
the risk of breast cancer is higher when exposed at an age
younger than 5 years.⁹⁷ It is, however, unknown to what
degree systematic implementation of RT delay to avoid
exposure during particularly critical ages would influence
the incidence of SN.

Retrospective and Prospective Registry
Studies

Cancer therapy is constantly changing and poses challenges
in obtaining robust predictive methods to evaluate new
technology and exposure scenarios. Although achieving
solid clinical evidence requires sufficient cohort sizes, there
is a trade-off in generalizing and controlling for treatment
and patient factors. Variations within different radiation set-
tings, such as response depending on dose rate (across RT
and LSS cohorts)⁵¹ or across RT fractionation regimens,⁷²
highlight the complexity. Furthermore, there are research
opportunities related to retrospective, detailed whole-body
dosimetry. Dose estimates used in most studies are subject
to several uncertainties, causing information loss in the dose
distribution because of the heterogeneity of organ doses in
RT. This particularly influences organs in the vicinity of the
target volume and field edges, where the steepest dose gra-
dients occur.⁹⁸ Methods for dose reconstruction accounting
for dose uncertainties and heterogeneities in organs should
with alkylating agents and anthracyclines was associated
with SNs of the breast, sarcoma, lung, stomach, and pan-
creas.⁸² Although the declining use of chest RT in female
patients with childhood cancer has contributed to reducing
the occurrence of SN in the breast, there is a growing con-
cern related to the risk from chemotherapy agents.⁸³ In par-
ticular, the contribution of anthracycline exposure is a
concern.⁸⁴ Furthermore, methotrexate has been found to
increase the risk of meningioma, although no clear dose-
response relationship has been found and there is no
reported interaction with RT.⁵³ An increased risk of thyroid
cancer was reported among patients in the CCSS cohort
treated with a combination of chemotherapy and RT (RR
was 1.8-2.4) but not if chemotherapy was administered
alone.⁸⁰ A French study including 4338 5-year survivors
with an average follow-up of 27 years concluded that the
risk of SN of the thyroid should be assessed in combination
with chemotherapy, splenectomy, RT dose to the pituitary
gland, and body mass index.⁸⁵

The use of growth hormone therapy has in some studies shown an increased risk in SNs but with diminishing incidence for increasing follow-up time. The risk of meningioma was not found to increase in children receiving recombinant human growth hormones alongside brain RT.⁸⁶ Moreover, immunotherapy has not been applied in the first-line treatment of pediatric cancer, although several types have been approved for clinical use in children. Heudel et al⁸⁷ investigated the effect of immune checkpoint inhibitors on SNs and found that immunotherapy alone or in combination with chemotherapies was associated with a reduced SN incidence across all ages and cancer types. Given the considerable observed effects on SN from RT and combined treatments, approaches integrating the mutual effects of these risk contributors have substantial potential from the standpoint of optimizing and reducing the risk of SNs.

Mitigation strategies

Beyond minimizing SN risk from treatments, there is a
strong rationale for managing the overall risk of SNs. The
myriad of contributing causes at play in cancer development
provides an opportunity to reduce the background risk by
adjusting modifiable behavioral and lifestyle factors.⁸⁸ Lead-
ing risk factors for attributable cancer deaths are currently
smoking, followed by alcohol use and high body mass
index.⁸⁹ Moreover, as an example, smoking interacts multi-
plicatively with RT related to the risk of developing lung
cancer.⁹⁰ Considering that environmental and lifestyle fac-
tors could be a contributor in as many as 90% of all cancers
in the general population, the potential of adjusting this
background risk is extensive.⁹¹ Patient awareness of risk and
mitigation strategies is therefore crucial. This is within the
scope of the International Late Effects of Childhood Cancer
Guideline Harmonization Group, a worldwide collaboration
developing common guidelines for long-term follow-up and

surveillance of chronic health problems and subsequent
cancers in young cancer survivors.⁹²

Cancer screening has contributed to decreasing the mor-
bidity and mortality of cancer.⁹³ With 8.5% of pediatric can-
cers caused by genetic susceptibility,⁹⁴ it is crucial to identify
individuals who may benefit from early screening programs.
Well-known examples are carriers with BRCA mutations at
elevated risk of having breast cancer.⁹³ With the relatively
high mortality rate of SN of the breast,⁸ early detection in
this group is associated with favorable outcomes. Recently,
female childhood cancer survivors were shown to have
more than 2-fold increased risk of SN of the breast after
anthracycline-based chemotherapy (doxorubicin cumulative
dose ≥200 mg/m²),⁸⁴ suggesting a potential for including
these patients in forthcoming surveillance guidelines. Fur-
thermore, young women treated with chest RT have an
increased risk of breast cancer with incidence 13% to 20%
by age 40 to 45.⁹⁵ Significant gaps persist in our understand-
ing of the interplay between genetic susceptibility and treat-
ment factors related to SN risks.⁹⁶ Although this combined
information holds great promise for enhancing future preci-
sion screening strategies, further research is warranted to
determine the treatment dose levels and host-specific factors
that should prompt the initiation of surveillance programs.
In addition, such investigations should be supplemented by
an assessment of potential harms and benefits related to life-
long surveillance.

Because of the effect of age at exposure, postponed RT is
sometimes considered in very young patients. For instance,
the risk of breast cancer is higher when exposed at an age
younger than 5 years.⁹⁷ It is, however, unknown to what
degree systematic implementation of RT delay to avoid
exposure during particularly critical ages would influence
the incidence of SN.

Retrospective and Prospective Registry
Studies

Cancer therapy is constantly changing and poses challenges
in obtaining robust predictive methods to evaluate new
technology and exposure scenarios. Although achieving
solid clinical evidence requires sufficient cohort sizes, there
is a trade-off in generalizing and controlling for treatment
and patient factors. Variations within different radiation set-
tings, such as response depending on dose rate (across RT
and LSS cohorts)⁵¹ or across RT fractionation regimens,⁷²
highlight the complexity. Furthermore, there are research
opportunities related to retrospective, detailed whole-body
dosimetry. Dose estimates used in most studies are subject
to several uncertainties, causing information loss in the dose
distribution because of the heterogeneity of organ doses in
RT. This particularly influences organs in the vicinity of the
target volume and field edges, where the steepest dose gra-
dients occur.⁹⁸ Methods for dose reconstruction accounting
for dose uncertainties and heterogeneities in organs should
be explored and developed to increase the accuracy of predictive dose-response models.

In addition to data collected during the past decades, there are ongoing efforts to register SNs and late effects in children treated with modern techniques. They include the United States Pediatric Proton/Photon Consortium Registry (ClinicalTrials.gov identifier: NCT01696721), which includes 25 centers and has registered close to 4800 patients.⁹⁹ In Europe, the HARMONIC-RT project (NCT04746729) is currently piloting a similar registry in 4 European countries and is expected to include 2300 patients by the end of 2023.¹⁰⁰ To enable the evaluation of advances in pediatric RT in terms of SN, it is necessary to have multicenter and multicountry registration of patient-level outcome and treatment data. Prospective registration is ideal because it usually allows standardized, and probably more complete, data collection across centers. Still, prospective data collection faces many challenges. The most important ones are to set up a sustainable information technology infrastructure, governance, and incentives to convince individual RT centers and investigators to collaborate. This also requires the allocation of resources locally for registration (ie, staff and time), which can be particularly challenging in countries where the hospital staff is already under pressure. Moreover, low- and middle-income countries lack resources and essential infrastructure in cancer care, not at least related to follow-up and research. Pediatric cancer survival rates in low- and middle-income countries are considerably lower (5-year overall survival range, 5%-60%) compared with high-income countries.¹⁰¹,¹⁰² More than 80% of pediatric patients with cancer reside in low- and middle-income countries,¹⁰³ but over 90% of global cancer research is conducted in high-income countries.¹⁰³,¹⁰⁴ Optimized treatment protocols from high-income countries are not adapted to the local conditions and patient demographics of low- and middle-income countries, and directly transferring such protocols may result in inferior survival or increased toxicity in low- and middle-income countries.¹⁰⁵ Whereas available technology for cancer treatment is dramatically different across the world,¹⁰¹ low- and middle-income countries will likely follow a different path of implementation of developments and tools to optimize care. The research priorities are different, but rather than a limitation, this should be viewed as an opportunity to fill research gaps not attainable otherwise (eg, genetic variability, diversity in combined treatments).

Furthermore, the infrastructure and resources must be sustainable to enable long-term follow-up during the decades after treatment. For doing so, a passive follow-up by linkage with other databases, such as disease registries and health insurance databases, is the most efficient option to assess SNs and most late effects and to avoid selection bias due to follow-up rates and times depending on the health status and/or treatment-related factors. Registers should ideally also include biological information to further our knowledge of genetic variability related to radiosensitivity and radiosusceptibility.

# Mechanisms and Risk Modeling

## Risk measures

The EAR provides the additional absolute risk above the background risk, whereas the ERR is the increase in relative risk over the background risk. This is further discussed in the PENTEC state of science article by Bentzen et al in this issue. These measures can be represented for different attained ages and vary depending on SN histology. The lifetime risk is often used (eg, lifetime attributable risk), but whether an SN presents early or later in life, it clearly has an effect on the overall consequence for the childhood cancer survivor. Secondary leukemia may appear 5 to 10 years post-RT, whereas an increased risk of solid tumors typically presents later and persists throughout life.⁷⁵ In addition, the endpoints of incidence versus fatality risk should be considered. A more comprehensive perspective could be achieved by using more integrated measures, such as quality of life and life years lost.¹⁰⁶

## Mechanistic modeling approaches

The available epidemiologic data limit our capabilities to precisely model the risk of SNs on a personal level for the various scenarios of RT. There are, however, several approaches in use for predicting risks for individual patients based on the delivered dose distribution and to compare treatment plans across delivery techniques. To account for the complete dose exposure, the dose from both the primary treatment fields and the out-of-field scatter and neutron contributions should be considered. Standard radioprotection models have been extensively applied to low-dose levels from scattered radiation and neutrons.⁷⁰,¹⁰⁷,¹⁰⁸ These models are primarily based on the LSS cohort and are valid up to about 2.5 Gy,⁷⁰ wherein a dose and dose-rate effectiveness factor is applied to adapt for different exposure scenarios. For the higher doses from the primary fields, semiempirical models have been generated by fitting mechanistically founded mathematical functions to follow-up data of radiation-exposed groups. A commonly used base function is the adaption of the linear quadratic model for cell survival, replaced by tumor induction from malignant cell transformation.¹⁰⁹ Another approach assumes cellular DNA damage results in carcinogenic cell mutations or cell killing, promoting competition between these 2 components.¹¹⁰ Further advanced models adjust for fractionation effects and cell repopulation⁴⁸ or include more complex dynamics of cancer formation with short- and long-term cellular processes.⁴⁷,¹¹¹ The initial slope of the derived semi-mechanistic models is then typically fitted to follow-up data from the appropriate dose span and RT cohort. Schneider⁴⁶,¹¹² fitted a model to the observed risk of organ-specific cancer after chest RT as the only treatment of 32,591 patients with Hodgkin cancer with reconstructed treatment plans and dose distributions. Several models for absolute risks, albeit
be explored and developed to increase the accuracy of predictive dose-response models.

In addition to data collected during the past decades, there are ongoing efforts to register SNs and late effects in children treated with modern techniques. They include the United States Pediatric Proton/Photon Consortium Registry (ClinicalTrials.gov identifier: NCT01696721), which includes 25 centers and has registered close to 4800 patients.⁹⁹ In Europe, the HARMONIC-RT project (NCT04746729) is currently piloting a similar registry in 4 European countries and is expected to include 2300 patients by the end of 2023.¹⁰⁰ To enable the evaluation of advances in pediatric RT in terms of SN, it is necessary to have multicenter and multicountry registration of patient-level outcome and treatment data. Prospective registration is ideal because it usually allows standardized, and probably more complete, data collection across centers. Still, prospective data collection faces many challenges. The most important ones are to set up a sustainable information technology infrastructure, governance, and incentives to convince individual RT centers and investigators to collaborate. This also requires the allocation of resources locally for registration (ie, staff and time), which can be particularly challenging in countries where the hospital staff is already under pressure. Moreover, low- and middle-income countries lack resources and essential infrastructure in cancer care, not at least related to follow-up and research. Pediatric cancer survival rates in low- and middle-income countries are considerably lower (5-year overall survival range, 5%-60%) compared with high-income countries.¹⁰¹,¹⁰² More than 80% of pediatric patients with cancer reside in low- and middle-income countries,¹⁰³ but over 90% of global cancer research is conducted in high-income countries.¹⁰³,¹⁰⁴ Optimized treatment protocols from high-income countries are not adapted to the local conditions and patient demographics of low- and middle-income countries, and directly transferring such protocols may result in inferior survival or increased toxicity in low- and middle-income countries.¹⁰⁵ Whereas available technology for cancer treatment is dramatically different across the world,¹⁰¹ low- and middle-income countries will likely follow a different path of implementation of developments and tools to optimize care. The research priorities are different, but rather than a limitation, this should be viewed as an opportunity to fill research gaps not attainable otherwise (eg, genetic variability, diversity in combined treatments).

Furthermore, the infrastructure and resources must be sustainable to enable long-term follow-up during the decades after treatment. For doing so, a passive follow-up by linkage with other databases, such as disease registries and health insurance databases, is the most efficient option to assess SNs and most late effects and to avoid selection bias due to follow-up rates and times depending on the health status and/or treatment-related factors. Registers should ideally also include biological information to further our knowledge of genetic variability related to radiosensitivity and radiosusceptibility.

# Mechanisms and Risk Modeling

## Risk measures

The EAR provides the additional absolute risk above the background risk, whereas the ERR is the increase in relative risk over the background risk. This is further discussed in the PENTEC state of science article by Bentzen et al in this issue. These measures can be represented for different attained ages and vary depending on SN histology. The lifetime risk is often used (eg, lifetime attributable risk), but whether an SN presents early or later in life, it clearly has an effect on the overall consequence for the childhood cancer survivor. Secondary leukemia may appear 5 to 10 years post-RT, whereas an increased risk of solid tumors typically presents later and persists throughout life.⁷⁵ In addition, the endpoints of incidence versus fatality risk should be considered. A more comprehensive perspective could be achieved by using more integrated measures, such as quality of life and life years lost.¹⁰⁶

## Mechanistic modeling approaches

The available epidemiologic data limit our capabilities to precisely model the risk of SNs on a personal level for the various scenarios of RT. There are, however, several approaches in use for predicting risks for individual patients based on the delivered dose distribution and to compare treatment plans across delivery techniques. To account for the complete dose exposure, the dose from both the primary treatment fields and the out-of-field scatter and neutron contributions should be considered. Standard radioprotection models have been extensively applied to low-dose levels from scattered radiation and neutrons.⁷⁰,¹⁰⁷,¹⁰⁸ These models are primarily based on the LSS cohort and are valid up to about 2.5 Gy,⁷⁰ wherein a dose and dose-rate effectiveness factor is applied to adapt for different exposure scenarios. For the higher doses from the primary fields, semiempirical models have been generated by fitting mechanistically founded mathematical functions to follow-up data of radiation-exposed groups. A commonly used base function is the adaption of the linear quadratic model for cell survival, replaced by tumor induction from malignant cell transformation.¹⁰⁹ Another approach assumes cellular DNA damage results in carcinogenic cell mutations or cell killing, promoting competition between these 2 components.¹¹⁰ Further advanced models adjust for fractionation effects and cell repopulation⁴⁸ or include more complex dynamics of cancer formation with short- and long-term cellular processes.⁴⁷,¹¹¹ The initial slope of the derived semi-mechanistic models is then typically fitted to follow-up data from the appropriate dose span and RT cohort. Schneider⁴⁶,¹¹² fitted a model to the observed risk of organ-specific cancer after chest RT as the only treatment of 32,591 patients with Hodgkin cancer with reconstructed treatment plans and dose distributions. Several models for absolute risks, albeit
omitting background risks, were generated including linear dose responses, as well as models reaching a plateau or fall-off at higher doses. Furthermore, the organ-equivalent dose concept has been a much-applied approach for comparing SN risk across different dose distributions,¹¹³,¹¹⁴ and it provides risk ranking independent of knowledge of the absolute risk. Nevertheless, there are uncertainties associated with retrospective dose reconstruction and SN location⁹⁸ that may be improved using new modeling strategies addressing dose heterogeneity. In addition to considering RT characteristics, semi-mechanistic models incorporate risk factors such as age at exposure, attained age, and sex. Other known contributors such as genetic predisposition, hormonal status, lifestyle factors, and other therapies remain to be integrated in the SN models but could provide important input to clinical practice and an opportunity to guide technology developments.

## Genetic predisposition and individual radiation response

The diversity in responses to ionizing radiation within a population suggests that future treatment planning could potentially leverage personalized tolerance doses based on biological markers.¹¹⁵ Patients with cancer predisposition, such as those with genetic mutations in the critical tumor suppressor gene *T53*, are often approached with caution regarding diagnostic and therapy-related use of ionizing radiation.¹¹⁶,¹¹⁷ A recent review examined the risks linked to radiation exposure in individuals with pathogenic variants of DNA damage response genes.¹¹⁸ The authors concluded that for carriers of germline variants of *T53* there was clinical evidence indicating a high risk from RT and recommended contraindicating RT for this group. For other common germline mutations including *BRCA1/BRCA2*, *ATM*, and *CHEK2*, there was either no direct evidence or only limited evidence of risk related to RT, and avoidance of RT was not recommended except for a few specific variants among these.

Historically, the term “radiation sensitivity” has been applied in describing both acute tissue effects and radiation-related cancers.¹¹⁹ Britel et al¹²⁰ proposed using this term only when referring to the endpoint of tissue toxicity related to noncancer events and using “radiation susceptibility” for SNs. Furthermore, different normal-tissue effects are likely not clustered within individuals,¹²¹,¹²² implying that individuals are not inherently radiosensitive but may be predisposed to specific types of adverse events. This predisposition could be attributed to various host factors and may not necessarily reflect intrinsic cellular radiosensitivity. Similarly, individuals may be susceptible to developing a specific type of SN without being universally at an elevated risk for all SNs. Despite evidence for variation across both radiation sensitivity and susceptibility, there is currently no standard clinical testing available.¹²³ Access to such biological information would open new avenues for selection among

available technologies and likely influence the development of RT delivery techniques.

## Modeling of local versus patient-level risks

The relationship between local cellular effects and global, patient-level risk represents one of the widest knowledge gaps related to SNs from competing technologies. The local nature of mutagenesis and the linear relationship between dose and risk could suggest that it is the total energy deposited (dose x volume) that drives the risk of SNs. However, it is conceivable that the wound-healing response induced by radiation¹²⁴ could promote malignant progression on one hand and suppress tumor regrowth on the other. Likewise, the immune effects seen in survivors after RT¹²⁵ may influence carcinogenesis. The interplay between these properties will likely only be sorted from actual analysis of long-term human data, supported by biologically motivated multiscale models considering the body as a set of interconnected systems.

## Proton therapy and relative biological effectiveness

Protons deposit energy as a function of the distance traveled in tissue, which causes an increase in linear energy transfer (LET) toward the end of the Bragg peak. In general, more densely ionizing radiation increases the biological effect and has clinically been set to a generic factor of 1.1 relative to the biological effectiveness of photon-based therapies. This spatially invariant RBE of 1.1 was originally chosen as a conservative scalar to maintain tumor control probability throughout the tumor and disregards effects in normal tissues.¹²⁶ In particular, the potential contribution to brain stem injury related to increased LET near the target has been a concern.¹²⁷⁻¹²⁹ The clinical significance and RBE for SNs are unknown¹³⁰; however, data from preclinical studies¹²⁶,¹³¹ do not indicate deviation in RBE for cell kill and mutation frequencies, and should, given transferability to the tissue level, have similar carcinogenic impact per unit of delivered biologically equivalent dose.

The energy deposition in microscopic structures (cell/nucleus/DNA) is likely biologically relevant and may be studied through so-called microdosimetric quantities, representing stochastic analogs of dose and LET.¹³² Recent dedicated Monte Carlo packages can be applied for this purpose, such as Geant4-DNA,¹³³ which in combination with preclinical model experiments may help our understanding of damage patterns and radiation-induced mechanisms in cells and the relation to biological outcomes.

## Emerging and Future Technologies

### Proton arc therapy

State-of-the-art PBS typically delivers 2 to 5 treatment fields. The use of proton arc therapy is emerging, analogous to the
omitting background risks, were generated including linear dose responses, as well as models reaching a plateau or fall-off at higher doses. Furthermore, the organ-equivalent dose concept has been a much-applied approach for comparing SN risk across different dose distributions,¹¹³,¹¹⁴ and it provides risk ranking independent of knowledge of the absolute risk. Nevertheless, there are uncertainties associated with retrospective dose reconstruction and SN location⁹⁸ that may be improved using new modeling strategies addressing dose heterogeneity. In addition to considering RT characteristics, semi-mechanistic models incorporate risk factors such as age at exposure, attained age, and sex. Other known contributors such as genetic predisposition, hormonal status, lifestyle factors, and other therapies remain to be integrated in the SN models but could provide important input to clinical practice and an opportunity to guide technology developments.

## Genetic predisposition and individual radiation response

The diversity in responses to ionizing radiation within a population suggests that future treatment planning could potentially leverage personalized tolerance doses based on biological markers.¹¹⁵ Patients with cancer predisposition, such as those with genetic mutations in the critical tumor suppressor gene *T53*, are often approached with caution regarding diagnostic and therapy-related use of ionizing radiation.¹¹⁶,¹¹⁷ A recent review examined the risks linked to radiation exposure in individuals with pathogenic variants of DNA damage response genes.¹¹⁸ The authors concluded that for carriers of germline variants of *T53* there was clinical evidence indicating a high risk from RT and recommended contraindicating RT for this group. For other common germline mutations including *BRCA1/BRCA2*, *ATM*, and *CHEK2*, there was either no direct evidence or only limited evidence of risk related to RT, and avoidance of RT was not recommended except for a few specific variants among these.

Historically, the term “radiation sensitivity” has been applied in describing both acute tissue effects and radiation-related cancers.¹¹⁹ Britel et al¹²⁰ proposed using this term only when referring to the endpoint of tissue toxicity related to noncancer events and using “radiation susceptibility” for SNs. Furthermore, different normal-tissue effects are likely not clustered within individuals,¹²¹,¹²² implying that individuals are not inherently radiosensitive but may be predisposed to specific types of adverse events. This predisposition could be attributed to various host factors and may not necessarily reflect intrinsic cellular radiosensitivity. Similarly, individuals may be susceptible to developing a specific type of SN without being universally at an elevated risk for all SNs. Despite evidence for variation across both radiation sensitivity and susceptibility, there is currently no standard clinical testing available.¹²³ Access to such biological information would open new avenues for selection among

available technologies and likely influence the development of RT delivery techniques.

## Modeling of local versus patient-level risks

The relationship between local cellular effects and global, patient-level risk represents one of the widest knowledge gaps related to SNs from competing technologies. The local nature of mutagenesis and the linear relationship between dose and risk could suggest that it is the total energy deposited (dose x volume) that drives the risk of SNs. However, it is conceivable that the wound-healing response induced by radiation¹²⁴ could promote malignant progression on one hand and suppress tumor regrowth on the other. Likewise, the immune effects seen in survivors after RT¹²⁵ may influence carcinogenesis. The interplay between these properties will likely only be sorted from actual analysis of long-term human data, supported by biologically motivated multiscale models considering the body as a set of interconnected systems.

## Proton therapy and relative biological effectiveness

Protons deposit energy as a function of the distance traveled in tissue, which causes an increase in linear energy transfer (LET) toward the end of the Bragg peak. In general, more densely ionizing radiation increases the biological effect and has clinically been set to a generic factor of 1.1 relative to the biological effectiveness of photon-based therapies. This spatially invariant RBE of 1.1 was originally chosen as a conservative scalar to maintain tumor control probability throughout the tumor and disregards effects in normal tissues.¹²⁶ In particular, the potential contribution to brain stem injury related to increased LET near the target has been a concern.¹²⁷⁻¹²⁹ The clinical significance and RBE for SNs are unknown¹³⁰; however, data from preclinical studies¹²⁶,¹³¹ do not indicate deviation in RBE for cell kill and mutation frequencies, and should, given transferability to the tissue level, have similar carcinogenic impact per unit of delivered biologically equivalent dose.

The energy deposition in microscopic structures (cell/nucleus/DNA) is likely biologically relevant and may be studied through so-called microdosimetric quantities, representing stochastic analogs of dose and LET.¹³² Recent dedicated Monte Carlo packages can be applied for this purpose, such as Geant4-DNA,¹³³ which in combination with preclinical model experiments may help our understanding of damage patterns and radiation-induced mechanisms in cells and the relation to biological outcomes.

## Emerging and Future Technologies

### Proton arc therapy

State-of-the-art PBS typically delivers 2 to 5 treatment fields. The use of proton arc therapy is emerging, analogous to the
<table><caption>**Table 1** Research topics with opportunities related to RT technology advances</caption><thead><tr><th></th><th></th></tr></thead><tbody><tr><td>Maturing of retrospective outcome data</td><td>Opportunities exist with increasing follow-up time in cohorts treated decades ago with nonconformal or 3DCRT techniques. This includes dose-response modeling using retrospective dosimetry, related to dose fractionation and combined treatments.</td></tr><tr><td>Documentation of RT treatment in studies</td><td>Standardized registration and follow-up of patients treated with current RT techniques and emerging and future technologies. Reporting should include both diagnostic and therapeutic radiation exposures.</td></tr><tr><td>Dose-response relationship</td><td>Estimation of the SN risk attributable to low-dose bath versus high-dose volumes. Potential for risk mitigation related to dose conformity surrounding the target volume and the integral dose volumes of the body.</td></tr><tr><td>Characterization of patient and treatment factors</td><td>Better characterize the combined effect of radiation factors (ie, total dose, dose fractionation, volume, beam quality), systemic cancer treatments, patient's genetic background, and other potential modifying factors such as comorbidities, noncancer medications, smoking, and hormonal factors.</td></tr><tr><td>SN risk modeling</td><td>Risk projection models provide guidance to what data are needed to obtain new knowledge. Providing input of projected SN risk of emerging and future RT modalities can maximize the potential of risk reduction when technology matures. Models should include dose-volume data for various organs at risk, and include RBE of protons and secondary neutrons.</td></tr><tr><td>Decision support tools</td><td>Develop efficient decision-aid tools to explore contemporary and developing RT techniques. Opportunities to optimize personalized treatment for current patients, as well as influence technology development.</td></tr><tr><td>Mechanisms of radiation carcinogenesis</td><td>Improved understanding of the microscopic dose distribution to increase knowledge of mechanisms involved in cancer induction (Monte Carlo, microdosimetry, radiobiological experiments, and theoretical modeling from basic principles). Relationship between local cellular effects and global patient-level risk.</td></tr><tr><td>Emerging RT planning and delivery</td><td>Explore future treatment planning and delivery techniques, including proton arcs, multi-ion schemes, and FLASH RT, and improve modeling of biological effectiveness in mixed radiation fields. Selective SN constraints on dose to organs at risk.</td></tr></tbody></table>

Abbreviations: 3DCRT = 3-dimensional conformal photon-based RT; RBE = relative biological effectiveness; RT = radiation therapy; SN = subsequent neoplasm.

evolution of photon-based RT. In silico studies have demonstrated the feasibility of proton arc therapy delivery and its potential to reduce normal tissue complication probability (NTCP) in brain tumors.<sup>134-136</sup> This reduction is achieved by decreasing high-dose volumes, albeit at the expense of increasing volumes at doses below approximately 2 Gy. For pediatric craniopharyngioma, Toussaint et al<sup>137</sup> found that increasing the number of proton beams in total achieved lower integral dose and estimated risks of SNs compared with standard intensity modulated proton therapy (IMPT) and VMAT. The reduced integral dose with increased dose conformity around the target holds promise, in particular related to the linear dose response as presented in the current PENTEC data.

Carbon ions and multi-ion therapy

Carbon ions have so far been applied with great caution in children,<sup>138</sup> mainly in highly aggressive and radio-resistant

tumors difficult to treat with conventional photons or protons.<sup>139,140</sup> The radiation field is more complex compared with protons, with increasing uncertainties in RBE of normal tissues, including uncertainties in carcinogenic potential.<sup>141,142</sup> From in vitro experiments, the carcinogenic patterns of the entrance channel of carbon ion beams have, however, been found comparable to those of photon-based RT, whereas for decreasing energies relevant for the tumor volume, the transformation per surviving cell was significantly higher with carbon ions.<sup>143</sup> Nevertheless, a clinical study of SNs after treatment of prostate cancer in adults<sup>144</sup> found a lower risk from carbon ions compared with photons.<sup>145</sup> Helium is another promising candidate for RT,<sup>146</sup> offering improved dose characteristics with a reduced lateral penumbra compared with protons, but with less uncertainty in RBE compared to carbon ions.<sup>147</sup> It is conceivable that future personalized RT will involve selection and combination across multiple ions.<sup>148</sup> Expanding our knowledge of SNs seems crucial for a wider adaption of carbon and other ions in children.
<table><caption>**Table 1** Research topics with opportunities related to RT technology advances</caption><thead><tr><th></th><th></th></tr></thead><tbody><tr><td>Maturing of retrospective outcome data</td><td>Opportunities exist with increasing follow-up time in cohorts treated decades ago with nonconformal or 3DCRT techniques. This includes dose-response modeling using retrospective dosimetry, related to dose fractionation and combined treatments.</td></tr><tr><td>Documentation of RT treatment in studies</td><td>Standardized registration and follow-up of patients treated with current RT techniques and emerging and future technologies. Reporting should include both diagnostic and therapeutic radiation exposures.</td></tr><tr><td>Dose-response relationship</td><td>Estimation of the SN risk attributable to low-dose bath versus high-dose volumes. Potential for risk mitigation related to dose conformity surrounding the target volume and the integral dose volumes of the body.</td></tr><tr><td>Characterization of patient and treatment factors</td><td>Better characterize the combined effect of radiation factors (ie, total dose, dose fractionation, volume, beam quality), systemic cancer treatments, patient's genetic background, and other potential modifying factors such as comorbidities, noncancer medications, smoking, and hormonal factors.</td></tr><tr><td>SN risk modeling</td><td>Risk projection models provide guidance to what data are needed to obtain new knowledge. Providing input of projected SN risk of emerging and future RT modalities can maximize the potential of risk reduction when technology matures. Models should include dose-volume data for various organs at risk, and include RBE of protons and secondary neutrons.</td></tr><tr><td>Decision support tools</td><td>Develop efficient decision-aid tools to explore contemporary and developing RT techniques. Opportunities to optimize personalized treatment for current patients, as well as influence technology development.</td></tr><tr><td>Mechanisms of radiation carcinogenesis</td><td>Improved understanding of the microscopic dose distribution to increase knowledge of mechanisms involved in cancer induction (Monte Carlo, microdosimetry, radiobiological experiments, and theoretical modeling from basic principles). Relationship between local cellular effects and global patient-level risk.</td></tr><tr><td>Emerging RT planning and delivery</td><td>Explore future treatment planning and delivery techniques, including proton arcs, multi-ion schemes, and FLASH RT, and improve modeling of biological effectiveness in mixed radiation fields. Selective SN constraints on dose to organs at risk.</td></tr></tbody></table>

Abbreviations: 3DCRT = 3-dimensional conformal photon-based RT; RBE = relative biological effectiveness; RT = radiation therapy; SN = subsequent neoplasm.

evolution of photon-based RT. In silico studies have demonstrated the feasibility of proton arc therapy delivery and its potential to reduce normal tissue complication probability (NTCP) in brain tumors.<sup>134-136</sup> This reduction is achieved by decreasing high-dose volumes, albeit at the expense of increasing volumes at doses below approximately 2 Gy. For pediatric craniopharyngioma, Toussaint et al<sup>137</sup> found that increasing the number of proton beams in total achieved lower integral dose and estimated risks of SNs compared with standard intensity modulated proton therapy (IMPT) and VMAT. The reduced integral dose with increased dose conformity around the target holds promise, in particular related to the linear dose response as presented in the current PENTEC data.

Carbon ions and multi-ion therapy

Carbon ions have so far been applied with great caution in children,<sup>138</sup> mainly in highly aggressive and radio-resistant

tumors difficult to treat with conventional photons or protons.<sup>139,140</sup> The radiation field is more complex compared with protons, with increasing uncertainties in RBE of normal tissues, including uncertainties in carcinogenic potential.<sup>141,142</sup> From in vitro experiments, the carcinogenic patterns of the entrance channel of carbon ion beams have, however, been found comparable to those of photon-based RT, whereas for decreasing energies relevant for the tumor volume, the transformation per surviving cell was significantly higher with carbon ions.<sup>143</sup> Nevertheless, a clinical study of SNs after treatment of prostate cancer in adults<sup>144</sup> found a lower risk from carbon ions compared with photons.<sup>145</sup> Helium is another promising candidate for RT,<sup>146</sup> offering improved dose characteristics with a reduced lateral penumbra compared with protons, but with less uncertainty in RBE compared to carbon ions.<sup>147</sup> It is conceivable that future personalized RT will involve selection and combination across multiple ions.<sup>148</sup> Expanding our knowledge of SNs seems crucial for a wider adaption of carbon and other ions in children.
## FLASH RT

In preclinical models, the sparing of normal tissue toxicity has been observed after FLASH RT.¹⁴⁹ FLASH delivers radiation at a single ultrahigh dose rate (≥40 Gy/s), approximately 400-fold higher than contemporary RT. Compared with conventional dose rates, FLASH has been found to reduce brain injury and radiation-induced cognitive dysfunction in the radiosensitive juvenile mouse brain.¹⁵⁰ Although the carcinogenic effects of using ultrahigh dose rates in normal tissues are unknown, the potential to reduce late morbidity, for instance from whole-brain RT of pediatric medulloblastoma, could represent long-awaited relief for this patient group.

## Advanced computing and artificial intelligence

Software and hardware developments are paving the way for new possibilities in the delivery of treatment, multicriteria optimization, and in the domain of data collection, analysis, and follow-up. Artificial intelligence can offer comprehensive risk assessment in guidance of therapeutic strategies, by combining RT dose optimization with other patient-specific risk factors with the scalability to large patient cohorts.¹⁵¹ Radiomics and radiogenomics are promising fields in conjunction with developments in data management and sharing across institutions.¹⁵²,¹⁵³ The future of routine health care after childhood cancer should ideally include efficient decision support tools¹⁵⁴,¹⁵⁵ as well as personalized surveillance combined with management and prevention of late effects based on individual risks.¹⁵⁶ Although multiscale modeling and optimization are computationally demanding, quantum computing stands out as a promising technological advancement that could propel progress in this field.

## Summary and Conclusions

The rapid pace of technological advancements in hardware and software development is not likely to slow down, presenting a landscape where numerous evolving RT modalities will become available in the coming years. To enhance our knowledge of SNs in various scenarios involving RT alone or in combination with other therapies and host-specific risk factors, more clinical data and analyses are needed, as outlined in Table 1. When setting research priorities, it is crucial to maintain perspectives on patients treated with currently available technology while considering implications with novel RT techniques and other treatment modalities. Furthermore, supporting and prioritizing research in low- and middle-income countries holds significance not only from an ethical viewpoint but also in gathering data from children of diverse genetic backgrounds and different geographic locations. Future treatments are unlikely to converge into a single technology; rather, we will have several alternatives to choose from. This in turn means that we

need tools and evidence to assess the relative merits of competing treatments tailored to each child with cancer.

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17. Dudley IM, Sunguc C, Heymer EJ, et al. Risk of subsequent primary lymphoma in a cohort of 69,460 five-year survivors of childhood and adolescent cancer in Europe: The PanCareSurFup study. *Cancer* 2023;129:426-440.

18. Reulen RC, Frobisher C, Winter DL, et al. Long-term risks of subsequent primary neoplasms among survivors of childhood cancer. *JAMA* 2011;305:2311-2319.

19. Henderson TO, Oeffinger KC, Whitton J, et al. Secondary gastrointestinal cancer in childhood cancer survivors: A cohort study. *Ann Intern Med* 2012;156:757-766 W-260.

20. Zahnreich S, Schmidberger H. Childhood cancer: Occurrence, treatment and risk of second primary malignancies. *Cancers (Basel)* 2021;13.

21. Turcotte LM, Whitton JA, Friedman DL, et al. Risk of subsequent neoplasms during the fifth and sixth decades of life in the Childhood Cancer Survivor Study cohort. *J Clin Oncol* 2015;33:3568-3575.
## FLASH RT

In preclinical models, the sparing of normal tissue toxicity has been observed after FLASH RT.¹⁴⁹ FLASH delivers radiation at a single ultrahigh dose rate (≥40 Gy/s), approximately 400-fold higher than contemporary RT. Compared with conventional dose rates, FLASH has been found to reduce brain injury and radiation-induced cognitive dysfunction in the radiosensitive juvenile mouse brain.¹⁵⁰ Although the carcinogenic effects of using ultrahigh dose rates in normal tissues are unknown, the potential to reduce late morbidity, for instance from whole-brain RT of pediatric medulloblastoma, could represent long-awaited relief for this patient group.

## Advanced computing and artificial intelligence

Software and hardware developments are paving the way for new possibilities in the delivery of treatment, multicriteria optimization, and in the domain of data collection, analysis, and follow-up. Artificial intelligence can offer comprehensive risk assessment in guidance of therapeutic strategies, by combining RT dose optimization with other patient-specific risk factors with the scalability to large patient cohorts.¹⁵¹ Radiomics and radiogenomics are promising fields in conjunction with developments in data management and sharing across institutions.¹⁵²,¹⁵³ The future of routine health care after childhood cancer should ideally include efficient decision support tools¹⁵⁴,¹⁵⁵ as well as personalized surveillance combined with management and prevention of late effects based on individual risks.¹⁵⁶ Although multiscale modeling and optimization are computationally demanding, quantum computing stands out as a promising technological advancement that could propel progress in this field.

## Summary and Conclusions

The rapid pace of technological advancements in hardware and software development is not likely to slow down, presenting a landscape where numerous evolving RT modalities will become available in the coming years. To enhance our knowledge of SNs in various scenarios involving RT alone or in combination with other therapies and host-specific risk factors, more clinical data and analyses are needed, as outlined in Table 1. When setting research priorities, it is crucial to maintain perspectives on patients treated with currently available technology while considering implications with novel RT techniques and other treatment modalities. Furthermore, supporting and prioritizing research in low- and middle-income countries holds significance not only from an ethical viewpoint but also in gathering data from children of diverse genetic backgrounds and different geographic locations. Future treatments are unlikely to converge into a single technology; rather, we will have several alternatives to choose from. This in turn means that we

need tools and evidence to assess the relative merits of competing treatments tailored to each child with cancer.

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105. Howard SC, Davidson A, Luna-Fineman S, et al. A framework to develop adapted treatment regimens to manage pediatric cancer in low- and middle-income countries: The Pediatric Oncology in Developing Countries (PODC) Committee of the International Pediatric Oncology Society (SIOP). *Pediatr Blood Cancer* 2017;64(suppl 5).
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107. Howell RM, Hertel NE, Want Z, Hutchinson J, Fullerton GD. Calculation of effective dose from measurements of secondary neutron spectra and scattered photon dose from dynamic MLC IMRT for 6 MV, 15 MV, and 18 MV beam energies. *Med Phys* 2006;33:360-368.

108. Zacharouat Jarlskog C, Lee C, Bolch WE, Xu XG, Paganetti H. Assessment of organ-specific neutron equivalent doses in proton therapy using computational whole-body age-dependent voxel phantoms. *Phys Med Biol* 2008;53:693-717.

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110. Daşu A, Toma-Daşu I. Dose-effect models for risk-relationship to cell survival parameters. *Acta Oncol* 2005;44:829-835.

111. Shuryak I, Hahnfeldt P, Hlatky L, Sachs RK, Brennder DJ. A new view of radiation-induced cancer: Integrating short- and long-term processes. Part I: Approach. *Radiat Environ Biophys* 2009;48:263-274.

112. Schneider U, Walsh L. Cancer risk estimates from the combined Japanese A-bomb and Hodgkin cohorts for doses relevant to radiotherapy. *Radiat Environ Biophys* 2008;47:253-263.

113. Schneider U, Kaser-Hotz B. Radiation risk estimates after radiotherapy: Application of the organ equivalent dose concept to plateau dose-response relationships. *Radiat Environ Biophys* 2005;44:235-239.

114. Schneider U, Kaser-Hotz B. A simple dose-response relationship for modeling secondary cancer incidence after radiotherapy. *Z Med Phys* 2005;15:31-37.

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122. Barnett GC, West CML, Coles CE, et al. Standardized Total Average Toxicity score: A scale- and grade-independent measure of late radiotherapy toxicity to facilitate pooling of data from different studies. *Int J Radiat Oncol Biol Phys* 2012;82:1065-1074.

123. Gomolka M, Blyth B, Bourguignon M, et al. Potential screening assays for individual radiation sensitivity and susceptibility and their current validation state. *Int J Radiat Biol* 2020;96:280-296.

124. Bentzen SM. Preventing or reducing late side effects of radiation therapy: Radiobiology meets molecular pathology. *Nat Rev Cancer* 2006;6:702-713.

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126. Paganetti H. Relative biological effectiveness (RBE) values for proton beam therapy. Variations as a function of biological endpoint, dose, and linear energy transfer. *Phys Med Biol* 2014;59:R419-R472.

127. Underwood TSA, McNamara AL, Appelt A, Haviland JS, Singers Sørensen B, Troost EGC. A systematic review of clinical studies on

variable proton relative biological effectiveness (RBE). *Radiother Oncol* 2022;175:79-92.

128. Haas-Kogan D, Indelicato D, Paganetti H, et al. National Cancer Institute workshop on proton therapy for children: Considerations regarding brainstem injury. *Int J Radiat Oncol Biol Phys* 2018;101:152-168.

129. Paganetti H. Mechanisms and review of clinical evidence of variations in relative biological effectiveness in proton therapy. *Int J Radiat Oncol Biol Phys* 2022;112:222-236.

130. Paganetti H, Blakely E, Carabe-Fernandez A, et al. Report of the AAPM TG-256 on the relative biological effectiveness of proton beams in radiation therapy. *Med Phys* 2019;46:e53-e78.

131. Mognato M, Bortoletto E, Ferraro P, et al. Genetic damage induced by in vitro irradiation of human G0 lymphocytes with low-energy protons (28 keV/microm): HPRT mutations and chromosome aberrations. *Radiat Res* 2003;160:52-60.

132. Santa Cruz GA. Microdosimetry: Principles and applications. *Rep Pract Oncol Radiother* 2016;21:135-139.

133. Incerti S, Douglass M, Penfold S, Guatelli S, Bezak E. Review of Geant4-DNA applications for micro and nanoscale simulations. *Phys Med* 2016;32:1187-1200.

134. Ding X, Zhou J, Li X, et al. Improving dosimetric outcome for hippocampus and cochlea sparing whole brain radiotherapy using spot-scanning proton arc therapy. *Acta Oncol* 2019;58:483-490.

135. Bertolet A, Carabe A. Proton monoenergetic arc therapy (PMAT) to enhance LETd within the target. *Phys Med Biol* 2020;65 165006.

136. Toussaint L, Indelicato DJ, Holgersen KS, et al. Towards proton arc therapy: Physical and biologically equivalent doses with increasing number of beams in pediatric brain irradiation. *Acta Oncol* 2019;58:1451-1456.

137. Toussaint L, Muren LP, Stokkevåg CH. Risk of second primary cancer from proton arc therapy of pediatric brain tumors. *Phys Imaging Radiat Oncol* 2023;27 100480.

138. Ohno T, Okamoto M. Carbon ion radiotherapy as a treatment modality for paediatric cancers. *Lancet Child Adolesc Health* 2019;3:371-372.

139. Laprie A, Hu Y, Alapetite C, et al. Paediatric brain tumours: A review of radiotherapy, state of the art and challenges for the future regarding protontherapy and carbontherapy. *Cancer Radiother* 2015;19:775-789.

140. Combs SE, Kessel KA, Herfarth K, et al. Treatment of pediatric patients and young adults with particle therapy at the Heidelberg Ion Therapy Center (HIT): Establishment of workflow and initial clinical data. *Radiat Oncol* 2012;7:170.

141. Durante M, Loeffler JS. Charged particles in radiation oncology. *Nat Rev Clin Oncol* 2010;7:37-43.

142. Stokkevåg CH, Fukahori M, Nomiya T, et al. Modelling of organ-specific radiation-induced secondary cancer risks following particle therapy. *Radiother Oncol* 2016;120:300-306.

143. Bettega D, Calzolari P, Hessel P, Stucchi CG, Weyrather WK. Neoplastic transformation induced by carbon ions. *Int J Radiat Oncol Biol Phys* 2009;73:861-868.

144. Mohamad O, Tabuchi T, Nitta Y, et al. Risk of subsequent primary cancers after carbon ion radiotherapy, photon radiotherapy, or surgery for localised prostate cancer: A propensity score-weighted, retrospective, cohort study. *Lancet Oncol* 2019;20:674-685.

145. Malouff TD, Mahajan A, Krishnan S, et al. Carbon ion therapy: A modern review of an emerging technology. *Front Oncol* 2020;10:82.

146. Mairani A, Mein S, Blakely E, et al. Roadmap: Helium ion therapy. *Phys Med Biol* 2022;67.

147. Knausl B, Fuchs H, Dieckmann K, Georg D. Can particle beam therapy be improved using helium ions? A planning study focusing on pediatric patients. *Acta Oncol* 2016;55:751-759.

148. Ebner DK, Frank SJ, Inaniwa T, Yamada S, Shirai T. The emerging potential of multi-ion radiotherapy. *Front Oncol* 2021;11 624786.

149. Diffenderfer ES, Sorensen BS, Mazal A, Carlson DJ. The current status of preclinical proton FLASH radiation and future directions. *Med Phys* 2022;49:2039-2054.

150. Alagband Y, Cheeks SN, Bd Allen, et al. Neuroprotection of radiosensitive juvenile mice by ultra-high dose rate FLASH irradiation. *Cancers (Basel)* 2020;12:1671.
106. Brodin NP, Vogelius IR, Maraldo MV, et al. Life years lost—comparing potentially fatal late complications after radiotherapy for pediatric medulloblastoma on a common scale. *Cancer* 2012;118:5432-5440.

107. Howell RM, Hertel NE, Want Z, Hutchinson J, Fullerton GD. Calculation of effective dose from measurements of secondary neutron spectra and scattered photon dose from dynamic MLC IMRT for 6 MV, 15 MV, and 18 MV beam energies. *Med Phys* 2006;33:360-368.

108. Zacharouat Jarlskog C, Lee C, Bolch WE, Xu XG, Paganetti H. Assessment of organ-specific neutron equivalent doses in proton therapy using computational whole-body age-dependent voxel phantoms. *Phys Med Biol* 2008;53:693-717.

109. Schneider U. Mechanistic model of radiation-induced cancer after fractionated radiotherapy using the linear-quadratic formula. *Med Phys* 2009;36:1138-1143.

110. Daşu A, Toma-Daşu I. Dose-effect models for risk-relationship to cell survival parameters. *Acta Oncol* 2005;44:829-835.

111. Shuryak I, Hahnfeldt P, Hlatky L, Sachs RK, Brennder DJ. A new view of radiation-induced cancer: Integrating short- and long-term processes. Part I: Approach. *Radiat Environ Biophys* 2009;48:263-274.

112. Schneider U, Walsh L. Cancer risk estimates from the combined Japanese A-bomb and Hodgkin cohorts for doses relevant to radiotherapy. *Radiat Environ Biophys* 2008;47:253-263.

113. Schneider U, Kaser-Hotz B. Radiation risk estimates after radiotherapy: Application of the organ equivalent dose concept to plateau dose-response relationships. *Radiat Environ Biophys* 2005;44:235-239.

114. Schneider U, Kaser-Hotz B. A simple dose-response relationship for modeling secondary cancer incidence after radiotherapy. *Z Med Phys* 2005;15:31-37.

115. Morton LM, Sampson JN, Armstrong GT, et al. Genome-wide association study to identify susceptibility loci that modify radiation-related risk for breast cancer after childhood cancer. *J Natl Cancer Inst* 2017;109.

116. Schon K, Tischkowitz M. Clinical implications of germline mutations in breast cancer: TP53. *Breast Cancer Res Treat* 2018;167:417-423.

117. Le AN, Harton J, Desai H, et al. Frequency of radiation-induced malignancies post-adjuvant radiotherapy for breast cancer in patients with Li-Fraumeni syndrome. *Breast Cancer Res Treat* 2020;181:181-188.

118. Hosoya N, Miyagawa K. Implications of the germline variants of DNA damage response genes detected by cancer precision medicine for radiological risk communication and cancer therapy decisions. *J Radiat Res* 2021;62(suppl 1):i44-i52.

119. El-Nachef L, Al-Choboq J, Restier-Verlet J, et al. Human radiosensitivity and radiosusceptibility: What are the differences? *Int J Mol Sci* 2021;22:7158.

120. Britel M, Bourguignon M, Foray N. The use of the term 'radiosensitivity' through history of radiation: From clarity to confusion. *Int J Radiat Biol* 2018;94:503-512.

121. Bentzen SM, Overgaard M, Overgaard J. Clinical correlations between late normal tissue endpoints after radiotherapy: Implications for predictive assays of radiosensitivity. *Eur J Cancer* 1993;29A:1373-1376.

122. Barnett GC, West CML, Coles CE, et al. Standardized Total Average Toxicity score: A scale- and grade-independent measure of late radiotherapy toxicity to facilitate pooling of data from different studies. *Int J Radiat Oncol Biol Phys* 2012;82:1065-1074.

123. Gomolka M, Blyth B, Bourguignon M, et al. Potential screening assays for individual radiation sensitivity and susceptibility and their current validation state. *Int J Radiat Biol* 2020;96:280-296.

124. Bentzen SM. Preventing or reducing late side effects of radiation therapy: Radiobiology meets molecular pathology. *Nat Rev Cancer* 2006;6:702-713.

125. Constanzo J, Faget J, Ursino C, Badie C, Pouget J-P. Radiation-induced immunity and toxicities: The versatility of the cGAS-STING pathway. *Front Immunol* 2021;12:680503.

126. Paganetti H. Relative biological effectiveness (RBE) values for proton beam therapy. Variations as a function of biological endpoint, dose, and linear energy transfer. *Phys Med Biol* 2014;59:R419-R472.

127. Underwood TSA, McNamara AL, Appelt A, Haviland JS, Singers Sørensen B, Troost EGC. A systematic review of clinical studies on

variable proton relative biological effectiveness (RBE). *Radiother Oncol* 2022;175:79-92.

128. Haas-Kogan D, Indelicato D, Paganetti H, et al. National Cancer Institute workshop on proton therapy for children: Considerations regarding brainstem injury. *Int J Radiat Oncol Biol Phys* 2018;101:152-168.

129. Paganetti H. Mechanisms and review of clinical evidence of variations in relative biological effectiveness in proton therapy. *Int J Radiat Oncol Biol Phys* 2022;112:222-236.

130. Paganetti H, Blakely E, Carabe-Fernandez A, et al. Report of the AAPM TG-256 on the relative biological effectiveness of proton beams in radiation therapy. *Med Phys* 2019;46:e53-e78.

131. Mognato M, Bortoletto E, Ferraro P, et al. Genetic damage induced by in vitro irradiation of human G0 lymphocytes with low-energy protons (28 keV/microm): HPRT mutations and chromosome aberrations. *Radiat Res* 2003;160:52-60.

132. Santa Cruz GA. Microdosimetry: Principles and applications. *Rep Pract Oncol Radiother* 2016;21:135-139.

133. Incerti S, Douglass M, Penfold S, Guatelli S, Bezak E. Review of Geant4-DNA applications for micro and nanoscale simulations. *Phys Med* 2016;32:1187-1200.

134. Ding X, Zhou J, Li X, et al. Improving dosimetric outcome for hippocampus and cochlea sparing whole brain radiotherapy using spot-scanning proton arc therapy. *Acta Oncol* 2019;58:483-490.

135. Bertolet A, Carabe A. Proton monoenergetic arc therapy (PMAT) to enhance LETd within the target. *Phys Med Biol* 2020;65 165006.

136. Toussaint L, Indelicato DJ, Holgersen KS, et al. Towards proton arc therapy: Physical and biologically equivalent doses with increasing number of beams in pediatric brain irradiation. *Acta Oncol* 2019;58:1451-1456.

137. Toussaint L, Muren LP, Stokkevag CH. Risk of second primary cancer from proton arc therapy of pediatric brain tumors. *Phys Imaging Radiat Oncol* 2023;27 100480.

138. Ohno T, Okamoto M. Carbon ion radiotherapy as a treatment modality for paediatric cancers. *Lancet Child Adolesc Health* 2019;3:371-372.

139. Laprie A, Hu Y, Alapetite C, et al. Paediatric brain tumours: A review of radiotherapy, state of the art and challenges for the future regarding protontherapy and carbontherapy. *Cancer Radiother* 2015;19:775-789.

140. Combs SE, Kessel KA, Herfarth K, et al. Treatment of pediatric patients and young adults with particle therapy at the Heidelberg Ion Therapy Center (HIT): Establishment of workflow and initial clinical data. *Radiat Oncol* 2012;7:170.

141. Durante M, Loeffler JS. Charged particles in radiation oncology. *Nat Rev Clin Oncol* 2010;7:37-43.

142. Stokkevag CH, Fukahori M, Nomiya T, et al. Modelling of organ-specific radiation-induced secondary cancer risks following particle therapy. *Radiother Oncol* 2016;120:300-306.

143. Bettega D, Calzolari P, Hessel P, Stucchi CG, Weyrather WK. Neoplastic transformation induced by carbon ions. *Int J Radiat Oncol Biol Phys* 2009;73:861-868.

144. Mohamad O, Tabuchi T, Nitta Y, et al. Risk of subsequent primary cancers after carbon ion radiotherapy, photon radiotherapy, or surgery for localised prostate cancer: A propensity score-weighted, retrospective, cohort study. *Lancet Oncol* 2019;20:674-685.

145. Malouff TD, Mahajan A, Krishnan S, et al. Carbon ion therapy: A modern review of an emerging technology. *Front Oncol* 2020;10:82.

146. Mairani A, Mein S, Blakely E, et al. Roadmap: Helium ion therapy. *Phys Med Biol* 2022;67.

147. Knausl B, Fuchs H, Dieckmann K, Georg D. Can particle beam therapy be improved using helium ions? A planning study focusing on pediatric patients. *Acta Oncol* 2016;55:751-759.

148. Ebner DK, Frank SJ, Inaniwa T, Yamada S, Shirai T. The emerging potential of multi-ion radiotherapy. *Front Oncol* 2021;11 624786.

149. Diffenderfer ES, Sorensen BS, Mazal A, Carlson DJ. The current status of preclinical proton FLASH radiation and future directions. *Med Phys* 2022;49:2039-2054.

150. Alagband Y, Cheeks SN, Bd Allen, et al. Neuroprotection of radiosensitive juvenile mice by ultra-high dose rate FLASH irradiation. *Cancers (Basel)* 2020;12:1671.
151. Isaksson LJ, Pepa M, Zaffaroni M, et al. Machine learning-based models for prediction of toxicity outcomes in radiotherapy. *Front Oncol 2020;10:790.

152. Bera K, Braman N, Gupta A, Velcheti V, Madabhushi A. Predicting cancer outcomes with radiomics and artificial intelligence in radiology. *Nat Rev Clin Oncol* 2022;19:132-146.

153. Madhogarhia R, Haldar D, Bagheri S, et al. Radiomics and radiogenomics in pediatric neuro-oncology: A review. *Neurooncol Adv 2022;4:vdac083*.

154. van der Schaaf A, Langendijk JA, Fiorino C, Rancati T. Embracing phenom-enological approaches to normal tissue complication probability modeling: A question of method. *Int J Radiat Oncol Biol Phys* 2015;91:468-471.

155. Brodin NP, Maraldo MV, Aznar MC, et al. Interactive decision-support tool for risk-based radiation therapy plan comparison for Hodgkin lymphoma. *Int J Radiat Oncol Biol Phys* 2014;88:433-445.

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