bluuebunny/crossref_metadata_2025 huggingface dataset:
P07.02.A SEX-SPECIFIC EVALUATION OF EMOTIONAL PROBLEMS, UNMET NEEDS AND PSYCHIATRIC COMORBIDITY IN PATIENTS WITH HIGH-GRADE GLIOMAS - A MULTI-CENTER STUDY
Authors: Renovanz M , Hippler M , Kuchen R , Doerner L , Rieger D , Steinbach J , Ronellenfitsch M , Kessler A , Misch M , Onken J , Rapp M , Nadji-Ohl M , Mehlitz M , Meixensberger J , Fehrenbach M , Keric N , Ringel F , Coburger J , Weiss Lucas C , Wehinger J , Schmidt-Graf F , Gempt J , Tatagiba M , Tabatabai G , Schranz M , Singer S
Published: October 2024

BACKGROUND

Patients diagnosed with high-grade gliomas (HGG) often experience considerable emotional distress. However, not all of them actively seek professional psychosocial support even when clearly needed and so far, gender aspects are not considered in clinical routine. We evaluated differences between female and non-female patients regarding emotional functioning and psychiatric comorbidity.

METHODS

In this multi-center study involving 13 centers, emotional functioning was assessed in patients with high-grade glioma during their visits to the outpatient clinic with the EORTC Quality of Life Questionnaire (EORTC QLQ-C30), using thresholds of clinical importance following Giesinger to define increased problems. Unmet psychosocial care needs were ascertained with study specific questions and psychiatric comorbidity with the Structured Clinical Interview according to DSM (SCID). Analyses employed chi-square tests and multivariate binary logistic regression.

RESULTS

In total, 763 patients were enrolled of whom n=691 could be interviewed with the SCID. About half of them (57%, n= 396) were male, 294 (43%) female and 1 (0.1%) identified as diverse. For the following analyses, females were compared with non-females (male and diverse). Emotional functioning was poor in 67% of female and 57% of the non-female patients (unadjusted odds ratio (OR) 1.5, 95% CI 1.1-2.1, p=0.01; adjusted OR=1.4, 95% CI 0.9-2.1, p=0.11). About 22% of the women and 20% of men/diverse expressed the wish for support by a psychologist (p=0.54); additional support by social workers was wished for by 9% of all sexes (p=0.90), and additional emotional support by oncologists from 11% of the women and 6% of the men/diverse. According to the SCID interview, a total of 217 patients (31%, CI 28%-35%) were diagnosed with at least one common mental disorder (male: 115, 29%; female: 102, 35%). There was no evidence that gender was a predictor of comorbid mental disorders (adjusted OR=1.2; 95% CI 0.9-1.8, p=0.25).

CONCLUSION

Patients diagnosed with a high-grade glioma are at risk of comorbid mental disorders independently of gender though women might express their support needs and emotional problems more openly. Therefore, support should be offered to all genders low-threshold and equally.
P07.03.B THE EFFECT OF SEX HORMONES ON THE COURSE OF MENINGIOMAS IN DIFFERENT HORMONAL PHASES IN THE FEMALE LIFE
Authors: Taliansky A , Haisraely O , Atar N , Jan E , Modan-Moses D
Published: October 2024

BACKGROUND

The influence of gender on the incidence and the survival of patients with nervous system tumors (NST) is well known, but the mechanism is not fully understood yet. The effect of sex hormones on the course of NST in different hormonal phases in female life raises interest, but only the pregnancy condition has been discussed in detail, however, consensus has not been reached regarding clinical recommendations. Descriptions of the effect of fertility treatments (FT) on NST are in a few not recent reports. The importance of sex hormones replacement treatment (HRT) as a risk factor for radiation induced tumors in patients after radiotherapy for childhood NST has not been studied yet.

MATERIAL AND METHODS

We retrospectively evaluated the data of three cases of high-grade meningiomas in women of reproductive age treated in the Neuro-oncology unit at Sheba MC.

RESULTS

One case is a 41 years old woman, who received two cycles of FT in 2022 and was diagnosed with a Rt. Frontal WHO 2 meningioma on April 2023 that was treated by gross total resection (GTR). The second case is a 32 years old woman treated with radiotherapy and chemotherapy at age 10 years due to medulloblastoma, who on January 2023 was diagnosed and had GTR for a Lt. Frontal WHO 2 meningioma after 1 year of HRT. The last case is a 28 years old woman that had GTR for a Rt cerebellar WHO 2 meningioma in 2020. During 2023 the patient had FT for surrogate pregnancy and on February 2024 recurrent tumor was diagnosed and treated with radiosurgery.

CONCLUSION

There is not much information available regarding the effect of sex hormones on the course of meningiomas, possibly due to the low incidence of meningiomas during the reproductive years. In Israel, fertility treatments are included in the national healthcare and the number of treatment cycles is not limited. This allows the collection of information about the effect of fertility treatments on NST, especially meningiomas in women. This project initiated this year. A phenomenon of “ social” egg freezing that has been expanding in recent years caused an increase in the number of women applying for fertility treatments and the need for a large number of treatment cycles. Since the incidence of meningiomas increases with age, presumably, the use of fertility treatments at an older age may affect the incidence and the grade of meningiomas in women. We would like to raise the importance of this topic.
P08.01.A ANGIOGENESIS IN CHEMOTHERAPY INDUCED PERIPHERAL NEUROPATHY (CIPN): EXPLORING CIRCULATING VEGF AS BIOMARKER OF CIPN DEVELOPMENT AND RECOVERY
Authors: Velasco R , Andrés-Benito P , Marco C , Roca-Pereira S , Pros-Marsal A , López-Sampere Y , Eva D , Santos C , Stradella A , Bruna J
Published: October 2024

BACKGROUND

Chemotherapy induced peripheral neuropathy may result from an antiangiogenic effect of these drugs, resulting in destruction of the vasa nervorum. Vascular integrity alterations may contribute to neuropathic pain pathogenesis. Vascular endothelial growth factor A (VEGF-A) is an angiogenic factor that enhances nerve blood flow and oxygen supply by inducing angiogenesis, in response to the nerve ischemia and hypoxia caused by these drugs. Besides, microvascular damage has been suggested as the basis for neuropathic pain due to chemotherapy. Whether VEGF-A plays a role in the pathogenesis and repairment of CIPN is unknown. The aim of this study was to (1) explore the evolution of plasma VEGF during and after chemotherapy treatment and its association with development and recovery of CIPN; (2) compare the VEGF among different neurotoxic chemotherapy agents; (3) investigate the potential role of VEGF as biomarker of CIPN severity and prognosis.

MATERIAL AND METHODS

This is a single-center prospective observational longitudinal study including three cohorts of patients with breast, lymphoma or colorectal cancer treated with paclitaxel, brentuximab and oxaliplatin, respectively. All patients were assessed using the Total Neuropathy Score- clinical, Common Terminology Criteria for Adverse Events, EORTC QLQ-CIPN20 and nerve conduction studies (NCS) before, and periodically up to 12 months after finishing treatment. Serial VEGF and light chain Neurofilaments (NfL), a biomarker of nerve axon damage, were collected at the same timepoints and quantified using ELISA and SIMOA techniques, respectively. The changes in VEGF identified will be compared between groups of agents (platinum or microtubule disruptors) alone or in combination, and correlated with clinical, NfL and NCS data, depending on the degree of neuropathy and the presence of neuropathic pain.

RESULTS

One-hundred patients are included, mostly women (60%). At baseline, mean VEGF plasma levels were for males (215,70 +/- 204,06 pg/mL) and females (204,60 +/- 224,97 pg/mL), with no differences according to type of chemotherapy agent received (p=0.148). No correlation between VEGF and NfL at baseline was identified (p=0.9). One-third of the whole patients developed clinically relevant (> grade 2) CIPN) or painful CIPN. Analysis of VEGF is ongoing and will be reported as part of this abstract.

CONCLUSION

Mechanisms of CIPN are not fully elucidated and differences among agents must be investigated. Whether CIPN development and/or recovery is associated with a significant modulation of angiogenesis identified by changes in the levels of VEGF will be reported.
P08.04.B DECREASED PERIPHERAL BLOOD SEROTONIN AND KYNURENINE LEVELS ARE ASSOCIATED WITH POOR ONCOLOGICAL OUTCOMES IN GLIOBLASTOMA IDH-WT PATIENTS
Authors: De Domenico P , Snider S , Comai S , Bertazzo A , Nasini S , Roncelli F , Mortini P , Gagliardi F
Published: October 2024

BACKGROUND

The contribution of tryptophan (TRP) metabolism via the kynurenine (KP) and serotonin (SP) pathways in GBM biology has recently seen a growing interest. This study aims to address the association between pre-operative peripheral blood levels of TRP, kynurenine (KYN), 5-hydroxy-tryptophan (5-HTP), and serotonin (5-HT) and relevant oncological outcomes in GBM IDH-wt patients.

MATERIAL AND METHODS

A total of 62 adult patients undergoing maximal safe resection of newly diagnosed glioblastoma WHO grade 4 IDH-wt (GBM) were included. The variables were dichotomized and analyzed to explore their single contributions in building a predictive model of overall survival (OS) and progression-free survival (PFS) in GBM patients.

RESULTS

The mean baseline serum levels of 5-HT, KYN, 5-HTP, and 5-HT/TRP were significantly lower (-76%, -87%, -76%, -75%, p<0.001 respectively) in GBM patients when compared to n=27 healthy individuals. The median OS in the whole cohort of GBM patients was 16.3 months (95% CI:13.4-21.7). Patients with 5-HT < 78 ng/mL had a median OS of 14.4 months (95% CI: 11.4-17.6) compared to 22.5 (95% CI:17.7-27) in patients with 5-HT > 78 ng/mL (p = 0.01). Shorter OS was recorded in patients with KYN < 18 ng/mL (9.8, 95% CI:11.4-17.6 vs 17.5 months, 95% CI:14.4-22.5, p=0.002), KYN/TRP < 2.55 (13.4, 95% CI:11.4-15.6 vs 19.1 months, 95% CI:14.0-28.6, p=0.002), 5-HTP/TRP < 0.89 (11.5, 95% CI:10.9-20.6 vs 17.6 months 95% CI:14.4-32.4, p=0.02), and 5-HT/TRP < 5.78 (13.4, 95% CI: 11.4-15.6 vs 19.1 months, 95% CI: 14.0-28.6, p=0.002)The median PFS was 9.27 months (95% CI:7.77-13.9). Significantly shorter PFS was observed in patients with 5-HT < 78 ng/mL (p=0.04), KYN < 18 ng/mL (p=0.02), 5-HT/TRP < 5.78 (p=0.001), KYN/TRP < 2.55 (p=0.005). Multivariate Cox analysis (R2=67%) confirmed an independent predictive role for poor OS of decreased KYN (p=0.001), 5-HTP (p<0.001) and 5-HT (p<0.001). Similarly, decreased 5-HT (p=0.004), and decreased 5-HTP (p=0.01) were predictive of poorer PFS.

CONCLUSION

This study highlights an intriguing association between enhanced degradation of TRP into KYN at the expense of the amount of the amino acid for the SP and median survival times in GBM. Decreased levels of KYN, 5-HTP, and 5-HT were associated with shorter OS.
P08.05.A LIQUID BIOPSY FOR GLIOBLASTOMA: UTILIZING PLASMA EXTRACELLULAR VESICLES FOR TUMOR DIAGNOSIS AND MONITORING
Authors: Del Bene M , Zaccheroni E , Osti D , Faletti S , Cavallo S , Costanzi E , DiMeco F , Pelicci G
Published: October 2024

BACKGROUND

Glioblastoma (GBM), the deadliest brain tumor in adults, is traditionally diagnosed and characterized using neuroimaging and brain biopsies. These methods, however, suffer from limited specificity and sensitivity. The surgical risks associated with tumor sampling further complicate the monitoring of GBM’s molecular progression. Consequently, the identification of circulating GBM biomarkers is crucial for non-invasive tracking of the disease from diagnosis to relapse. Extracellular vesicles (EVs) secreted by GBM cells, which cross the blood-brain barrier and carry tumor-derived molecules, present a promising avenue for the continuous evaluation of GBM presence and status.

MATERIAL AND METHODS

We isolated extracellular vesicles (EVs) using Size Exclusion Chromatography (SEC) from 2 mL of plasma and characterized them via immunoblotting, flow cytometry, and transmission electron microscopy. The concentration and size of EVs were measured using Tunable Resistive Pulse Sensing (TRPS). We compared EV levels in 50 glioblastoma (GBM) patients pre-surgery with those in non-GBM controls, which included 100 healthy individuals and 50 patients with brain malignancies that present similarly to GBM in neuroimaging studies. Longitudinal assessments of plasma EVs were performed in 44 GBM patients by comparing pre-operative and post-operative samples taken 72 hours after surgery. Additionally, we analyzed surface markers on GBM and non-GBM plasma EVs using MACSPlex and conducted proteomic analyses via mass spectrometry in 27 GBM patients and 38 healthy individuals.

RESULTS

We found higher concentrations and mean sizes of plasma EVs in GBM patients compared to controls, with a noticeable decrease post-operatively. Multiplex flow cytometry indicated universal expression of CD9, CD63, and CD81 across all samples, with significant enrichment of CD63 and CD81 in GBM plasma EVs. The expression profiles of the other 34 markers were similar across all samples, suggesting dilution of tumor-derived EVs among non-tumor EVs. However, T-cell markers CD8 and HLA-DRDPDQ were more prevalent on GBM-derived EVs. Proteomic analysis identified over 2,000 proteins in all samples, with 117 being upregulated in GBM samples, predominantly within the complement cascade pathways.

CONCLUSION

Our findings suggest that monitoring circulating EV levels provides a reliable, non-invasive method for the differential diagnosis and follow-up of GBM patients. The combined analysis of EV concentration, size, and proteome offers potential as promising biomarkers for longitudinal monitoring of GBM, supporting the implementation of liquid biopsy in GBM care.
P09.03.B ASSESSMENT OF RESPONSE TO LOMUSTINE-TEMOZOLOMIDE CHEMOTHERAPY IN ADDITION TO RADIOTHERAPY IN PATIENTS WITH NEWLY DIAGNOSED GLIOBLASTOMA USING FET PET
Authors: Werner J , Wollring M M , Tscherpel C , Rosen E K , Ceccon G , Stetter I , Lohmann P , Weller J , Stoffels G , Baues C , Celik E , Mottaghy F M , Goldbrunner R , Herrlinger U , Fink G R , Langen K , Galldiks N
Published: October 2024

BACKGROUND

We examined the value of O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET for early response assessment in patients with newly diagnosed glioblastoma and methylated O6-methylguanine-DNA methyltransferase promoter treated with lomustine-temozolomide chemotherapy in addition to radiotherapy.

MATERIAL AND METHODS

Thirty-one patients (29-74 years) were treated according to the CeTeG/NOA-09 phase-3 trial. FET PET and anatomical MRI were performed at baseline and follow-up after the third cycle. We obtained mean and maximum tumor-to-brain ratios (TBR) and metabolic tumor volumes (MTV). Thresholds derived from FET PET were defined using receiver operating characteristic analyses to predict progression-free survival (PFS) of ≥12 months. The predictive value of FET PET parameters was subsequently evaluated using univariate and multivariate survival estimates. MRI response assessment was based on the RANO 1.0 criteria. FET PET data were also used to estimate response according to the PET RANO 1.0 criteria.

RESULTS

Patients received a median number of 6 cycles of lomustine-temozolomide chemotherapy (3-6 cycles). After treatment initiation, the median follow-up was 17.2 months (7.2-59.4 months). As of April 2024, we confirmed tumor progression according to the RANO 1.0 criteria in 24 patients (77%). After three cycles of lomustine-temozolomide chemotherapy, a reduced mean TBR value by ≥10% predicted a significantly longer PFS (31.0 vs. 10.4 months; P=0.039). In contrast, changes in maximum TBR values, MTV, the RANO 1.0 criteria, and the PET RANO 1.0 criteria were not predictive for response (P>0.05). Multivariate survival analysis revealed that changes in mean TBR values predicted a significantly prolonged PFS independent of age, the extent of resection, and the Karnofsky Performance Status (P=0.036; HR, 3.892; 95% CI, 1.242-17.230).

CONCLUSION

Our results suggest that FET PET is clinically valuable for identifying responders to lomustine-temozolomide chemotherapy in addition to radiotherapy early after treatment initiation. The evaluation of FET PET’s value in predicting a significantly longer overall survival is ongoing.
P09.04.A BASELINE MR PERFUSION IMAGING OF BRAIN METASTASES PRIOR TO SRS (STARBEAM-X STUDY)
Authors: Dobeson C B , Lewis J , Bhatnagar P , Birkbeck M , West S
Published: October 2024

BACKGROUND

Following treatment with SRS, radionecrosis and tumour progression often have similar appearances on conventional MR imaging, yet have different management approaches. The STARBEAM-X study (Study of assessment of radionecrosis in brain metastases using MR perfusion imaging) has been designed with the aim of assessing the clinical application of baseline MR perfusion imaging prior to SRS as part of the radiotherapy planning process, with the hypothesis that baseline perfusion imaging will aid post-treatment imaging interpretation by enhancing our understanding of how a metastasis’ perfusion characteristics change following treatment with SRS. In this report, we present the participants’ imaging data as proof of feasibility of baseline MR perfusion imaging.

MATERIAL AND METHODS

Participants underwent baseline MR perfusion (DSC) imaging on Siemens Magnetom Sola 1.5T scanner as part of their radiotherapy planning imaging. Relative cerebral blood volume (rCBV) perfusion maps were calculated in Syngo.Via software and interpretation performed by an expert neuroradiologist.

RESULTS

39 patients underwent baseline MR perfusion - 25 (64.1%) were female, 14 (35.9%) were male. The composition of primary tumour sites were as follows: non-small cell lung cancer (NSCLC) - 14 (35.9%), breast - 10 (25.6%), renal - 5 (12.8%), melanoma - 6 (15.4%), ovary - 2 (5.1%), oesophagus - 1 (2.6%), colorectal - 1 (2.6%). Median age on the date of the MRI scan was 65.71 years (range 35.7 - 81.5 years, SD=11.57). 76 metastatic lesions were assessed in total. 14 (35.9%) patients were receiving systemic treatment at the time of MR perfusion scan. Of the 76 lesions treated, 51 (67.1%) were deemed assessable on perfusion imaging. Of the 51 assessable lesions - median volume was 0.821cm3 (mean 2.49cm3, range 0.19 - 12.75cm3, SD 3.09). Median rCBV ratio across all lesions was 3.24 (range 0.68 - 23.3, SD = 4.16). Median rCBV stratified to tumour site - NSCLC 2.845, breast 4.96, renal 5.88, ovary 4.95, melanoma 5.445 and colorectal 3.39. 24 lesions were not suitable for calculation of perfusion values - median volume was 0.069cm3 (mean 0.128cm3, range 0.011cm3 - 1.027cm3, SD 0.202). In 22 (91.7%) the documented reason for this was due to the peripheral nature of the lesion and overlap with normal brain vasculature.

CONCLUSION

At least two thirds of metastatic brain lesions are suitable for assessment with baseline perfusion MR imaging - factors that impact on suitability are size, peripheral location and proximity to vessels. Participant numbers in this initial study are too low to assess associations between lesional perfusion characteristics and primary tumour site. In individual participants with multiple brain metastases, there was wide variability in perfusion characteristics across the different lesions.
P09.07.A EMERGING TRENDS IN NEURO-ONCOLOGY: THE RECENT ADVANCES OF AMIDE PROTON TRANSFER WEIGHTED (APTW) AND ARTERIAL SPIN LABELLING (ASL) IN BRAIN TUMOUR IMAGING
Authors: Shah M , Awuah W , Sanker V , Tan J , Aderinto N , Ahluwalia A , Poornaselvan J , Ohenewaa Tenkorang P , Darko K , Abdul-Rahman T , Atallah O , Duvuru S
Published: October 2024

BACKGROUND

Accurate diagnosis of brain tumours is crucial for improving patient outcomes. Current diagnostic methods such as MRI and CT scans have limitations in differentiating tumour types and defining margins. Recent advances in radiological modalities, specifically Amide Proton Transfer Weighted (APTw) and Arterial Spin Labelling (ASL) imaging, offer promising avenues to overcome these challenges.

MATERIAL AND METHODS

A systematic review of papers published between 2000 and 2024 that met the inclusion criteria was undertaken using several databases, including PubMed, EMBASE, Google Scholar, the Cochrane Library, and Scopus. Key terms such as “amide proton transfer weighted,” “arterial spin labelling,” “neuro-oncology,” and “brain tumours” were consistently employed.

RESULTS

APTw and ASL techniques play pivotal roles in brain tumour diagnostics, offering unique insights into molecular composition and vascular perfusion patterns, respectively. APTw facilitates differentiation between tumour subtypes, providing crucial data on aggressiveness and therapy response, while ASL evaluates tumour vascularisation, aiding therapeutic decisions, especially for anti-angiogenic treatments. These non-invasive methods enhance patient safety and comfort compared to invasive procedures like biopsy. ASL’s efficacy in distinguishing radiation necrosis from recurrent cancer, with a sensitivity of 94%, surpasses that of FDG PET and DSC. Furthermore, APTw-CEST imaging shows promise in evaluating treatment effects and delineating tumour borders, particularly in distinguishing gliomas from meningiomas. The combination of APTw and ASL enhances diagnostic accuracy, especially in differentiating tumour types or assessing treatment response, with the “APTw-ASL mismatch” emerging as a novel biomarker for specific tumour types like pilocytic astrocytomas. However, challenges such as technical complexities and limited accessibility exist but can be addressed through standardisation and technological advancements.

CONCLUSION

The clinical role of APTw and ASL imaging extends beyond diagnosis, aiding in intraoperative monitoring, complication detection, and seizure prediction. Collaborative efforts are needed to refine these techniques and overcome technical challenges, ensuring their wider clinical application and reliability. Despite challenges, their integration into clinical practice could revolutionise neuro-oncology by providing valuable insights into tumour biology and guiding personalised treatment strategies. Further research and standardisation efforts are essential to maximise the clinical utility of these advanced imaging techniques.
P09.13.A METABOLIC ACTIVITY OF PROTON RADIATION THERAPY RELATED EFFECTS IN GLIOMAS MEASURED WITH [18F]FET PET IMAGING
Authors: Madsen K , Muhic A , Scheie D , Rasmussen R , Carlsen J , Vestergaard A , Henriksen O , Law I
Published: October 2024

BACKGROUND

Proton radiation therapy (PRT) has since 2019 become a treatment option alongside photon therapy in Denmark. PRT reduces doses to normal brain structures and for gliomas PRT has been considered in oligodendroglioma WHO grade 2-3 (O2-3) and astrocytoma IDH mutated WHO grade 2-4 (A2-4). Concerns have been raised regarding the frequency of treatment-related effects. The aim of this study is to investigate the association between pathology results and metabolic activity when progression is suspected on MRI after PRT in glioma.

MATERIAL AND METHODS

Forty-nine patients from Rigshospitalet, Copenhagen, Denmark suffering from glioma were treated with PRT until October 2022 (mean age 41 years, range 23-65), and followed for a minimum 1.5 years until April 2024. Progression was suspected in 20 patients clinically and/or at MRI, of which 13 patients fulfilled the criteria of the study: a [18F]FET PET scan followed by first subsequent pathology assessment after PRT (biopsy n=8 and resection n=5, mean delay after PET imaging 18 days (range 1-50 days), mean interval after PRT 1.6 years (range 0.3-3.3 years). The initial pathology of gliomas were O3 n=5, A2 n=1, A3 n=5, A4 n=2. PET scans were performed 20 min after injection of approximately 200 MBq [18F]FET. The maximal metabolic activity relatively to healthy appearing cortex (TBRmax) was calculated for the suspicious lesion.

RESULTS

Tumor relapse was found in four patients (subsequent pathology A3 n=1, A4 n=3) with corresponding TBRmax of mean 3.1 (range 2.3-4.3). Pathology showed only treatment related effects in eight patients (initial pathology O3 n=5, A3 n=2 A4 n=1), with corresponding TBRmax of mean 1.8 (range 1.6-2.3), though one of these patients died 2.3 years later from tumor relapse. Mixed reactive changes and A2 tumor were found in the resected tissue of one patient with corresponding TBRmax of 1.6. Thus, the metabolic activity was significantly higher in tumor tissue compared to treatment-related effects using Students t-test, p=0.02 when classifying mixed as relapse (p= 0.002 when excluding mixed), and ROC AUC was 0.80 providing sens/spec of 80%/88% at an optimal TBRmax cut-off at 2.2.

CONCLUSION

The prevalence of treatment-related effects verified by histopathology was 16% in the patients treated with PRT during at least 1.5 year follow-up. A significantly lower metabolic activity was found in the treatment-related effects compared to tumor relapse measured with [18F]FET PET imaging. Indicating that [18F]FET PET imaging may be a valuable diagnostic tool to discriminate between relapse and treatment-related effects at an early stage after PRT. However, in our experience, reactive changes often expand over time and the metabolic intensity might accordingly increase later in the progress after PRT. For investigating this, systematic repeated [18F]FET PET imaging is needed.
P09.15.A SATURATION TRANSFER MRI ENABLES EARLY DETECTION OF CANCER LESIONS IN THE CNS
Authors: Lehman N , Chudzik A , Lam W W , Rola R , Stanisz G J
Published: October 2024

BACKGROUND

Chemical exchange saturation transfer (CEST) MRI provides chemical-group-specificity (e.g., amide, guanidinium, and aliphatic) to exchangeable protons in dissolved proteins. Magnetization transfer (MT) MRI is sensitive to water bound to macromolecules, e.g., myelin and collagen. The major objective of the study was to identify the chemical exchange saturation transfer- and magnetization transfer-derived magnetic resonance images that have high contrast between orthotopic U87 tumours and normal-appearing brain.

MATERIAL AND METHODS

U-87 MG glioblastoma cell line-derived xenografts were implanted in RNU nude rats (n=9). Animals were divided into two groups based on the scanning schedule. The rats were imaged using 7 tesla scanner (PharmaScan; Bruker BioSpin) at three time points for all animals: 3-5, 7-9, and 11-13 days after implantation. Single-slice saturation-transfer-weighted CEST (saturation amplitude: 0.5 and 2 µT) and MT (3 and 5 µT) contrast Z-spectra and T1 and T2 maps were acquired. The MT Z-spectra and T1 map were fitted to a two-pool quantitative MT model to estimate the T2 of the free and macromolecular-bound water molecules, the relative macromolecular pool size (M0, MT), and the magnetization exchange rate from the macromolecular pool to the free pool.

RESULTS

Statistically significant differences, by pairwise Wilcoxon signed-rank tests with Holm-Bonferroni adjustment, were found. The differences between enhancing lesion and contralateral cortex for the magnetization transfer ratio with 2 µT saturation at 3.6 ppm frequency offset (corresponding to the amide chemical group) and M0, MT are both strongly significant (p < 0.001) at all time points.

CONCLUSION

MT and CEST are a promising method of identifying the earliest time points of glioblastoma development. Such an early image biomarker of neoplasia may allow for improved treatment outcomes leading to reduced recurrence events.
P10.02.A A NOVEL APPROACH CONCERNING MEDICAL EDUCATION ON AI AND ML THROUGH THE ASNR MICCAI BRATS 2023 BRAIN METASTASES CHALLENGE
Authors: Janas A , Gkampenis A , Yordanov N , Fehringer P , Krantchev K , Moawad A W , Baid U , Link K E , Velichko Y S , LaBella D , Kofler F , Calabrese E , Shafique U , Conte G , Saluja R , Tahon N H , Maleki N , Abayazeed A , Aneja S , Nada A , Li H , Foltyn M , Bakas S , Rudie J ,   BraTS-METS Challenge 2023 Group, Aboian M
Published: October 2024

BACKGROUND

Artificial intelligence (AI) and machine learning (ML) are in the process of being integrated into modern healthcare, especially in imaging data-dependent fields like Radiology. Unfortunately, data shows that the acquaintance of physicians and medical students with AI is far from sufficient. Therefore, we implemented an educational chapter within the ASNR MICCAI BraTS 2023 Brain Metastases Challenge. Its purpose is to educate medical students on the basics of AI and ML application in the diagnostic imaging and apply deliberate learning approach to teach biology and physics of MRI imaging of brain metastases.

MATERIAL AND METHODS

Pilot group of 15 medical students from EU was expanded to 150, to include radiology residents and research associates. Fundamentals of MR imaging and process of lesion segmentation was taught through lectures and written guides. Trainees were involved in refining preprocessed cases to create ground truth segmentations for AI algorithm training within BraTS-METS Challenge. The annotators received individual support through question and answer sessions and expert reviews. Lectures specifically targeted to AI, ML, ethics, and Open Science introduced trainees to field experts. Specific skills related to building and publishing databases suitable for ML algorithm training, including all necessary preprocessing steps such as quality control, skull stripping, and normalization, were developed throughout the training process. Alternative methods for education, including #BraTSBrainMetsTeachingPearls Twitter series were also implemented which offered in-depth guidance on interpreting the imaging features of brain metastases and the ability to interact with imaging content.

RESULTS

Participants reported an enhanced understanding of neuroradiology, particularly in identifying imaging features of brain metastases. Their gained proficiency in ML/AI empowers them to efficiently assess existing models or replicate the workflow of model training. The early clinical exposure and extensive ML/AI lectures were highly valued, providing deeper insights into the applications and limitations of these technologies. The educational strategy combining constructivist principles with practical experience proved highly beneficial, equipping them with skills relevant to both research and clinical practice.

CONCLUSION

Insufficient integration of AI and ML in medical education necessitates effective and early training. Adopting a constructivist approach has equipped students with vital skills in Open Science, database development, and model training, preparing them to fully utilize these technologies while understanding their limitations.
P10.04.A A STRATEGY FOR MULTIMODAL INTEGRATION OF TRANSCRIPTOMICS, PROTEOMICS, AND RADIOMICS DATA FOR THE PREDICTION OF RECURRENCE IN PATIENTS WITH IDH-MUTANT GLIOMAS
Authors: Chouleur T , Etchegaray C , Villain L , Saut O , Bikfalvi A ,   GliomaPRD Consortium
Published: October 2024

BACKGROUND

Isocitrate dehydrogenase-mutant gliomas are lethal brain cancers that impair quality of life in young adults. Although less aggressive than glioblastomas, IDH-mutant gliomas invariably progress to incurable disease with unpredictable recurrence. A better classification of patient risk of recurrence is needed.

MATERIAL AND METHODS

We describe a multimodal analytical pipeline integrating imaging, transcriptomic, and proteomic profiles using machine learning.

RESULTS

1) description of the biological characteristics of IDH-mutant glioma subtypes categorized by positron emission tomography (PET) and histology, 2) integration of positron emission tomography (PET) metrics in the classification of IDH-mutant gliomas, and 3) improvement of patient stratification with novel signatures of patient risk of recurrence based on gene expression, protein level, and imaging.

CONCLUSION

We provide herein a useful road-map for the stratification of IDH-mutant glioma patients and their risk of recurrence, which will lead to better monitoring of the clinical evolution of the disease.
P10.08.A AUTOMATED LONGITUDINAL TREATMENT RESPONSE ASSESSMENT OF BRAIN TUMORS: A SYSTEMATIC REVIEW
Authors: Shi T , Linares C , Vercauteren T , Booth T
Published: October 2024

BACKGROUND

Longitudinal assessment of tumor burden using imaging helps to determine whether there has been a response to treatment both in trial and real-world settings. From a clinical trial perspective, the time to develop disease progression (progression free survival) is an important endpoint. However, longitudinal response assessment is time-consuming and subject to interobserver variability. Automated response assessment techniques based on machine learning (ML) promise to enhance accuracy and reduce reliance on expert manual measurement. This systematic review evaluates the quality and performance accuracy of recently published studies.

MATERIAL AND METHODS

Following PRISMA guidelines and the CLAIM checklist, we searched PUBMED, EMBASE, and Web of Science for articles from January 2010 to November 2023. Our PROSPERO-registered study (CRD42024496126) focused on adult brain tumor treatment response assessment studies using ML methodologies. We determined the extent of development and validation of the automated tools and employed QUADAS-2 for study appraisal.

RESULTS

Eighteen studies, including fifteen retrospective and three prospective studies, were included. Data extracted from each study included information on the dataset, automated steps within the pipeline, automated models (referred to as index tests), and reference standards. Only limited conclusions are appropriate given the high bias risk and applicability concerns (particularly in relation to reference standards and patient selection), and the low level of evidence.

CONCLUSION

The study highlights ML’s potential in improving brain tumor longitudinal treatment response assessment. Interpretation is limited due to study bias and limited evidence of generalizability. Prospective studies with external datasets validating the latest neuro-oncology criteria are now required.
P10.12.B DEEP LEARNING-BASED NORMALIZATION AND UNMIXING OF HYPERSPECTRAL IMAGES FOR BRAIN TUMOR SURGERY
Authors: Black D , Gill J , Xie A , Liquet B , Di Ieva A , Stummer W , Suero Molina E
Published: October 2024

BACKGROUND

Hyperspectral Imaging (HSI) for fluorescence-guided brain tumor resection enables better visualization of differences between tissues. This can maximize brain tumor resection, improving patient outcomes. However, much of the processing in HSI uses simplified models that are unable to capture the non-linear, wavelength-dependent phenomena that must be modeled for accurate recovery of fluorophore abundances. To overcome these challenges, measured spectra are normalized to account for artifacts and spectrally unmixed to isolate the protoporphyrin IX (PpIX) signal, which indicates malignant tissue. Existing methods are simplistic and based on phantoms and are unable to account for nonlinear effects such as multiple scattering or the inhomogeneous optical properties of the tissue. We propose a deep learning (DL)-based pipeline encompassing normalization and unmixing, which can fully account for the nonlinear effects and produce more accurate distributions of fluorophore abundances.

MATERIAL AND METHODS

This study proposes two deep learning models for correction and unmixing, which can capture these effects. Both models use autoencoder-like architectures. While one is trained with protoporphyrin IX (PpIX) concentration labels, the other is semi-supervised, learning hyperspectral unmixing self-supervised and then learning to correct the spectra for optical and geometric effects using a white-light reflectance spectrum in a few-shot manner. The models were evaluated on phantom and pig-brain data with known PpIX concentration.

RESULTS

The supervised and semi-supervised models achieved Pearson correlation coefficients (phantom, pig-brain) between known and computed PpIX concentrations of (0.997, 0.990) and (0.98, 0.91), respectively, whereas the classical approach achieved (0.93, 0.82). On human data, the semi-supervised model gives qualitatively more realistic results than the classical method, better reducing the variance in PpIX abundance over biopsies that should be relatively homogeneous.

CONCLUSION

These results show promise for using deep learning to improve HSI in fluorescence-guided neurosurgery.
P10.20.B MODELING UNCERTAINTY IN INDIVIDUAL PREDICTIONS OF COGNITIVE FUNCTIONING FOR UNTREATED GLIOMA PATIENTS USING BAYESIAN REGRESSION AND CLINICAL VARIABLES
Authors: Boelders S M , Nicenboim B , Postma E O , Ong L S , Gehring K
Published: October 2024

BACKGROUND

Cognitive functioning is increasingly considered when making treatment decisions for patients with a glioma in view of a personalized onco-functional balance (balancing survival against the preservation of function). Previous research using machine-learning models found that predicting pre-operative cognitive functioning based on clinical variables resulted in accurate predictions for some, but inaccurate predictions for other patients. Therefore, the current study sets out to use Bayesian models to improve predictions while also providing estimates of uncertainty for each individual prediction.

MATERIAL AND METHODS

Pre-operative cognitive functioning was predicted for 340 patients with a glioma across eight cognitive tests. This was done using six increasingly complex Bayesian regression models including hierarchical models conditioned on tumor grade. Models used a comprehensive set of predictors associated with cognitive functioning in the literature. Point-wise predictions were compared against one another and previous work using machine learning. The best-performing model (R2) was interpreted and examples of how Bayesian prediction models can be applied in clinical practice were provided.

RESULTS

Bayesian models outperformed the machine-learning models used in previous work. Predictions, however, remained uncertain. The best-performing model allowed coefficients and intercepts to differ across tumors with a different grade while pulling the estimates toward the population mean. Moreover, the best-performing model included regularizing priors, causing it to use most variables for prediction while not relying strongly on any variable.

CONCLUSION

Bayesian models resulted in better predictions than machine learning models while also providing estimates of uncertainty for individual predictions. For the best possible predictions, tumors with a different grade are best modeled as different, yet related. Moreover, a holistic view of patients’ cognitive functioning is necessary. The uncertainty in individual predictions exemplifies the importance of measures of uncertainty for clinical practice.
P11.03.A BRAIN METASTATIC LESIONS IN THE FRONTAL LOBE NEGATIVELY IMPACT PATIENT ENGAGEMENT
Authors: David S , Cialdella F , Nagtegaal S H J , van Grinsven E E , Philippens M E P , Verhoeff J J C
Published: October 2024

BACKGROUND

Brain metastases (BMs) significantly affect patients’ cognition, which can alter their ability to make informed decisions regarding treatment or engagement in scientific studies. In the COIMBRA (NCT05267158) study, we prospectively collect data from patients with BMs, including clinical assessments, radiological data, and patient-reported outcomes (PROs) pre- and post-radiotherapy. After enrolling in the trial, patients can make a number of decisions to participate in data collection efforts, such as engaging in QoL questionnaires. Here, we explore how lesion distributions or the disconnected white matter, known as the disconnectome, correlates with patient consent to QoL questionnaires.

MATERIAL AND METHODS

Between April 2019 and April 2023, 377 patients with BMs gave consent for COIMBRA and were referred for stereotactic radiosurgery. Of them, 276 consented to provide PROs, while 101 chose not to participate. The T1 MRIs, along with the gross tumor volumes (GTVs) were nonlinearly registered the MNI brain template, using EasyReg from Freesurfer. We used the BCBtoolkit to calculate the disconnected white matter areas. Voxelwise statistical comparison between the PRO consented and non-consented groups was performed with PALM. Family-wise error rate correction was performed to adjust for multiple comparison correction, p-value <0.05 was applied for significance.

RESULTS

The lesion-based analyses revealed a cluster of 3098 mm3, which significantly associated with PRO non-consent, predominantly located in the frontal lobe, specifically within the Frontal Pole (FP) and Cingulate Gyrus (CG), as well as part of the right Middle FG and the Insular Cortex. The disconnectome analysis identified a cluster of 7718 mm3, with disconnections in both sides of the anterior division of the CG, extending to FP and Superior FG. White matter tracts in the Anterior Thalamic Radiation and Forceps Minor are disrupted on both sides. The prefrontal subthalamic regions on both sides also show disconnections. There are no regions identified by either analysis method that show more lesions in the PRO consented group.

CONCLUSION

BM lesions in specific frontal lobe regions and disruptions in related white matter tracts significantly lowered patients’ consent fill-in QoL questionnaires. Data collection in research studies, particularly concerning aspects of patients’ mental health, typically relies on voluntary acts such as neuropsychological assessments or the collection of PROs. However, when patients cannot or are unable to participate in such efforts, due to their condition influenced by for example the lesion location, the results are likely to be biased. Clinicians may consider these ‘neural barriers’ in the design of studies and data collection methods, potentially integrating more observational or caregiver-reported measures to obtain evaluation of the patient’s condition.
P11.11.B VALIDITY RELATED EVIDENCE FOR COGSTATE TASKS IN PATIENTS WITH BRAIN METASTASES
Authors: Wefel J S , Tawbi H A , Sulman E P , Sullaway C M , Thomas A L , Noll K R , Tang C , Ferrarotto R , Welsh J , Guha-Thakurta N , Glitza I C , Diab A , Patel S P , Wong M K , Davies M A , Burton E , Chung C , Li J
Published: October 2024

BACKGROUND

Digital approaches to measuring and monitoring cognitive function (CF) are of interest as screening measures to enhance clinical care and clinical research. Validity related evidence for such measures is required prior to adopting these in practice and trials. Four investigator-initiated clinical trials evaluated CF in patients with brain metastases (BM) with both clinically validated CF tests and experimental computerized CogState (CS) tasks. Construct validity of the CS tasks was evaluated.

MATERIAL AND METHODS

140 pts with BM who completed both CF testing and computerized CS tasks prior to treatment were included. Within sample mean/SD were used to convert raw to standardized test scores. The following domains and tests were evaluated: Processing Speed (CS Detection, TMTA, TMTB, Coding), Attention (CS Identification, Digit Span, Coding, TMTA, TMTB), Working Memory (CS One Back, Digit Span), and Learning and Memory (CS One Card Learning and International Shopping List, HVLT-R). Spearman correlations were computed between CF tests and CS tasks, with significance set at the 0.01 level. Impairment was classified as a z-score ≤-1.5 and concordance rates were examined between HVLT-R and ISL.

RESULTS

On average, pts were 58.3 years old(SD 12.9), completed 14.7 years of education(SD 3.0), 48% female, and 84% right-handed. Spearman correlation coefficients between CS tasks and related CF tests were weak to moderate for processing speed (rs=0.39-0.55) and attention (rs=0.34-0.56), weak for working memory (rs=0.28), and weak to strong for learning and memory (rs=0.36-0.69). Spearman correlations were stronger, while intraclass correlation coefficients were moderate, between the ISLT and HVLT-R TR (rs=0.69 and ICC=0.58) and ISLR and HVLT-R DR (rs=0.69 and ICC=0.58). Concordance rates of impairment for the most highly correlated and parallel measures of learning and memory were poor with no to minimal correspondence based on Cohen kappa coefficients (ISLT and HVLT-R TR k=0.11; ISLR and HVLT-R DR k=0.29).

CONCLUSION

Spearman correlations between CS tasks and clinically validated CF tests in similar domains were weak with the exception of highly parallel measures of verbal learning and memory. ICC were less robust and Cohen kappa coefficients was negligible for these measures of verbal learning and memory. The substantial lack of agreement in identifying abnormal episodic memory performance is concerning in terms of utilizing the CS ISL task as a surrogate for the HVLT-R. Further associations between clinical variables and these measures of CF will help to determine ability to assess clinically relevant differences due to disease burden. Longitudinal evaluations will further shed light on sensitivity to treatment and disease effects.
P12.03.B CAN COGNITIVE PERFORMANCE PREDICT NEUROTOXICITY INCIDENCE FOLLOWING CHIMERIC ANTIGEN RECEPTOR T-CELL THERAPY FOR LYMPHOMA?
Authors: Ursu R , Barsan C , Belin C , Cuzzubbo S , Carreau C , El Soudany M , Sivapragassame R , Cristinelli C , Di Blasi R , Ouedrani A , Caillat-Zucman S , Thieblemont C , Carpentier A
Published: October 2024

BACKGROUND

Chimeric antigen receptor T-cell (CAR-T) therapy has revolutionised the landscape of cancer treatment, particularly in haematological malignancies, and while these therapies have demonstrated significant efficacy against malignancies, they are associated with a spectrum of side effects. Cytokine Release Syndrome (CRS) and Immune Effector Cell-Associated Neurotoxicity Syndrome (ICANS) are unique to CAR-T cell therapy and distinguish it from other forms of autoimmune toxicity. Predicting which patients will develop neurotoxicity remains a challenge. The pattern of ICANS is cognitive dysfunction, suggesting a plausible relationship between cognitive status and neurotoxicity. Understanding the interplay between cognitive function and neurotoxicity may provide valuable insights for early detection. The primary endpoint of this study was to investigate whether the cognitive performance of patients at the time of leukapheresis is associated with the subsequent development of ICANS.

MATERIAL AND METHODS

We report here on a prospective study of an adult patient population with aggressive B-cell lymphoma treated with CAR-T cell therapy at our centre between May 2020 and November 2023. All patients underwent neurological examination, cerebral MRI and global cognitive assessment using the Montreal Cognitive Assessment (MoCA) test with a cut-off of less than 26 points. We retrospectively recorded total metabolic tumour volume (TMTV) and International Prognostic Index (IPI) at lymphodepletion. Biological data including lactate dehydrogenase (LDH), albumin, ferritin and C-reactive protein (CRP) were also collected at the time of treatment. A retrospective analysis of pre-infusion serum neurofilament light chain (NfL) levels at the time of the decision to proceed with CAR-T cell therapy and at the time of treatment was performed.

RESULTS

156 patients, median age 64 years (range 21 to 79 years), 55 females / 101 males, all treated for lymphoma, were included in this study. The mean MoCA score was 26 (range 12 to 30 points), 63 patients (40%) had a MoCA test below the cut-off at baseline. Following infusion of CAR T cells, 32% of patients developed ICANS within 6 days (grade 1-2: 72%; grade 3-4: 30%). The most common sign of neurotoxicity was cognitive impairment. In univariate analyses, the occurrence of ICANS was not significantly associated with baseline cognitive performance (p 0.58). As the study is ongoing, an update on the results will be available at the EANO meeting.

CONCLUSION

Neurotoxicity associated with CAR-T therapies occurs in one third of patients. This study does not suggest an association between the occurrence of ICANS and baseline cognitive performance. Despite progress in understanding the mechanisms underlying neurotoxicity, predicting its occurrence remains a challenge.