bluuebunny/crossref_metadata_2025_split huggingface dataset:
SU‐F‐P‐09: A Global Medical Physics Collaboration for Implementation of Modern Radiotherapy in Botswana
Authors: Makufa R , Bvochora‐Nsingo M , Karumekayi T , Schneider RJ , Efstathiou JA , Dryden‐Peterson S , Odom A , Shulman A , Pipman Y , Gierga DP 
Published: July 2016

Purpose:The global burden of cancer is considerable, particularly in low and middle‐income countries. Massachusetts General Hospital (MGH) and Botswana‐Harvard AIDS Institute have partnered with the oncology community and government of Botswana to form BOTSOGO (BOTSwana Oncology Global Outreach) to address the rising burden of cancer in Botswana. Currently, radiation therapy (RT) is only available at a single linear accelerator (LINAC) in Gaborone Private Hospital (GPH). BOTSOGO worked to limit the absence of RT during a LINAC upgrade and ensure a safe transition to modern radiotherapy techniques.Methods:The existing Elekta Precise LINAC was decommissioned in November 2015 and replaced with a new Elekta VERSA‐HD with IMRT/VMAT/CBCT capability. Upgraded treatment planning and record‐and‐verify systems were also installed. Physicists from GPH and MGH collaborated during an intensive on‐site visit in Botswana during the commissioning process. Measurements were performed using newly purchased Sun Nuclear equipment. Photon beams were matched with an existing model to minimize the time needed for beam modeling and machine down time. Additional remote peer review was also employed. Independent dosimetry was performed by irradiating OSLDs, which were subsequently analyzed at MGH.Results:Photon beam quality agreed with reference data within 0.2%. Electron beam data agreed with example clinical data within 3%. Absolute dose calibration was performed using both IAEA and AAPM protocols. Absolute dose measurements with OSLDs agreed within 5%. Quentry cloud‐based software was installed to facilitate remote review of treatment plans. Patient treatments resumed in February 2016. The time without RT was reduced, therefore likely resulting in reduced patient morbidity/mortality.Conclusion:A global physics collaboration was utilized to commission a modern LINAC in a resource‐constrained setting. This can be a useful model in other areas with limited resources. Further use of technology and on‐site exchanges will facilitate the introduction of more advanced techniques in Botswana.We acknowledge funding support from the AAPM International Educational Activities Committee and the NCI Federal Share Proton Beam Program Income Grant.
SU‐F‐P‐11: Long Term Dosimetric Stability of 6 TomoTherapy Systems
Authors: Smilowitz J , Dunkerley D , Geurts M , Hill P , Yadav P 
Published: July 2016

Purpose:The dosimetric stability of six TomoTherapy units was analyzed to investigate changes in performance over time and with system upgrades.Methods:Energy and output were tracked using monitor chamber signal, onboard MVCT detector signal and external ion chamber measurements. The systems (and monitoring periods) include 3 Hi‐Art (67, 61 and 65 mos.), 2 HDA (29 and 25 mos.) and one research unit (7 mo.). Dose Control Stability system (DCS) was installed on 4 systems. Output stability is reported as deviation from reference monitor chamber signal for all systems, and from an external chamber for 4 systems. Energy stability was monitored using the relative (center versus off‐axis) MVCT detector signal and/or the ratio of chamber measurements at 2 depths. The results from the clinical systems were used to benchmark the stability of the research unit, which has the same linear accelerator but runs at a higher dose rate.Results:The output based on monitor chamber data of all six systems is very stable. Non‐ DCS had a standard deviation of 1.7% and 1.8%. As expected, DCS systems had improved standard deviation: 0.003–0.05%. The energy was also very stable for all units. The standard deviation in exit detector flatness was 0.02–0.3%. Ion chamber output and 20/10 cm ratios supported these results. The stability for the research system, as monitored with a variety of metrics, is on par with the existing systems.Conclusion:The output and energy of six TomoTherapy units over a total of almost 10 years is quite stable. For each system, the results are consistent between the different measurement tools and techniques, proving not only the dosimetric stability, but that these quality parameters can be confirmed with various metrics. A research unit operating at a higher dose rate performed as well as the clinical treatment units.University of Wisconsin and Accuray Inc. (vendor of TomoTherapy systems) have a research agreement which supplies funds for research to the University. This project was partially supporting with these funds.
SU‐F‐P‐24: Radiological Disperse Device
Authors: Alam R 
Published: July 2016

Purpose:We are now living in a society of constant fear of terrorism. This topic is pertaining to give a general knowledge of what is a radiological dispersion device or RDD and in case of its detonation, what are the options open to public for a safe action in terms of reducing the exposure and knowing the proper steps. These RDD are also called dirty bombs.Methods:Compared to nuclear weapons, dirty bombs are easy to make. In order for a terrorist organization to construct and detonate a dirty bomb, it must acquire radioactive material by stealing it or buying it through legal or illegal channels. Possible RDD material could come from the millions of radioactive sources used in the industry, for medical purposes and in academic applications mainly for researches. These are, americium‐241, californium‐252, caesium‐137, cobalt‐60, iridium‐192, plutonium‐238, polonium‐210, radium‐226 and strontium‐90.Results:Prompt detection of the type of radioactive material used will greatly assist advising people on the protective measures, like sheltering in place, or quickly leaving the immediate area. The effects of radiation are determined by:°the amount of radiation absorbed by body°the type of radiation °the distance from the radiation to an individual°the means of exposure absorbed by the skin, inhaled, or ingested; and length of time exposed.Conclusion:In any facility it is now much more important to keep a log list of all radioactive materials in use. In case there is a dirty bomb explosion, the chaos and economic cost could be enormous. The economic cost for the evaluation of the contamination, survey of people and surroundings and the after treatment, decontamination cost and effort will be a big challenge in any country. So awareness and preparation is the start to face this new type of challenge.
SU‐F‐P‐27: The Study of Actual DVH for Target and OARs During the Radiotherapy of Non‐Small Cell Lung Cancer
Authors: Ma C , Yin Y 
Published: July 2016

Purpose:To analyze the changes of the volume and dosimetry of target and organs at risk (OARs) by comparing the daily CBCT images and planning CT images of the patients with Non‐Small Cell Lung Cancer (NSCLC) and analyze the difference between planned dose and accumulated dose.Methods:This study retrospectively analyzed eight cases of non‐small cell lung cancer patients who accepted CRT or IMRT treatment and KV‐CBCT. For each patient, the prescription dose was 60Gy and the fraction dose was 2Gy. Deform the daily CBCT images to planning CT images by the mapping of registration to compare the planning dose with cumulative dose of targets and organs at risk in RayStation.Results:The average volume of GTV of 8 patients with CBCT was 88.26% of the original volume. The average plan dose of GTV was 64.49±2.40Gy. The accumulated dose of GTV was 60.13±2.70Gy (P≤0.05). The average volume of PTV to reach the prescription dose was 95.59% for original plan and 81.47% for accumulated plan (P≤0.05). The volume changes of the left and right lung of the original volume was 88.95% and 80.32%, respectively. The average dose of the left and right lung of original plan was 9.31±1.75Gy and 4.33±1.10Gy, respectively(P≥0.05). The average accumulated dose was 9.63±1.96Gy and 4.63±1.36Gy, respectively(P≥0.05). The average plan dose and accumulated dose of heart was 6.88±1.70Gy and 6.38±0.91Gy, respectively (P≥0.05). The average plan maximum dose and accumulated dose for spinal cord was 24.62±5.91Gy and 26.00±5.14Gy, respectively (P≥0.05).Conclusion:The changes of target anatomical structure with NSCLC make difference between the planned dose and cumulative dose. With the dose deformation method, the dose gap can be found between planning dose and delivery dose.
SU‐F‐P‐33: Combining Research and Professional Practice in the Clinical Setting: A Medical Physicist Personal Experience
Authors: L&oacutepez‐Tarjuelo J 
Published: July 2016

Purpose:To initiate a discussion on the current and evolving role of Medical Physicists based on author's professional and research experience in patient safety and quality control.Methods:Several professionals of the departments of Medical Physics and Radiation Oncology, chiefly devoted to clinical tasks, began a research program on patient safety and quality control in a framework provided by the implementation of intraoperative radiotherapy (IORT). We performed studies on virtual simulation for IORT, in vivo dosimetry, failure mode and effect analysis (FMEA), statistical process control (SPC), and receiver operating characteristics of dosimetric equipment. This was done with the support of our research foundation and different grants while continuing with our departmental clinical routine involving about 1600 annual treatments with two linacs and different brachytherapy techniques.Results:We published 5 papers in international journals in the last two years. This author conducted a doctoral research which resulted in a dissertation in 2015. The extra time spent after treatments was essential to succeed. Funding and support achieved via our foundation played a crucial role; but this would have not been possible without punctual external mentoring and partnership. FMEA conclusions were able to be implemented only with staff commitment; however, conclusions concerning equipment cannot be easily communicated to manufacturers. These tasks required extra training in the appropriated methods.Conclusion:Research needed the support of a dedicated foundation, which would have been very difficult to obtain with the sole participation of our departments. FMEA and SPC results may need engagement of staff and manufacturers, respectively, hard to achieve without strong recommendations or even a regulatory framework. All these fields need evolution of Medical Physicists’ roles and additional training. Devotion to both clinical tasks and research could be unfeasible for Medical Physicists in the clinical setting without the appropriate rearrangement of their schedules and tasks.Supported by grants IPT‐300000‐2010‐3 and PI11/01659. ERDF funds and Spanish Government.
SU‐F‐P‐38: Professional Practice Evaluation and Quality Improvement
Authors: Rong J 
Published: July 2016

Purpose:In 2008, The Joint Commission (JC) implemented a standard mandating clearly defined quality improvement metrics to be factored into the evaluation of medical practitioners’ professional performance as part of the process of granting and maintaining medical staff privileges in a hospital. Specifically, there are two processes for a credentialed medical staff member to go through: Ongoing Professional Practice Evaluation (OPPE) and Focused Professional Practice Evaluation (FPPE). This is an unfamiliar area to many of our medical physicists. The process of implementing Professional Practice Evaluation (PPE) into clinical practice is rather complex. It requires a considerable amount of work and collaboration. The quality metrics are typically different for physicists than physicians, and are specialty specific (therapy physicists vs. imaging physicists). However, in the future, some clinical medical physicists will likely be involved in this process for quality improvement. This presentation will provide an update to clinical medical physicists regarding OPPE and FPPE as well as discuss how to implement PPE in medical physics practice.Methods:Provide an overall of JC requirements and OPPE/FPPE.Discuss quality improvement metrics for clinical medical physicists.Evaluate methods/tools for meaningful data collection.Demonstrate the process of implementing PPE into clinical practice.Results:By understanding the concepts of OPPE and FPPE and the JC requirements, the clinical medical physicists will be better prepared for going through the credentialing process and achieving quality improvement.Conclusion:Sooner or later the clinical medical physicists will likely be involved in the process of PPE. It is challenging but also an opportunity for the medical physicists to become members of medical staffs of their institutions. AAPM as a group should start preparing for and/or implementing PPE in their clinical practices for achieving quality improvement.
SU‐F‐R‐44: Modeling Lung SBRT Tumor Response Using Bayesian Network Averaging
Authors: Diamant A , El Naqa I , Ybarra N , Seuntjens J 
Published: July 2016

Purpose:The prediction of tumor control after a patient receives lung SBRT (stereotactic body radiation therapy) has proven to be challenging, due to the complex interactions between an individual's biology and dose‐volume metrics. Many of these variables have predictive power when combined, a feature that we exploit using a graph modeling approach based on Bayesian networks. This provides a probabilistic framework that allows for accurate and visually intuitive predictive modeling. The aim of this study is to uncover possible interactions between an individual patient's characteristics and generate a robust model capable of predicting said patient's treatment outcome.Methods:We investigated a cohort of 32 prospective patients from multiple institutions whom had received curative SBRT to the lung. The number of patients exhibiting tumor failure was observed to be 7 (event rate of 22%). The serum concentration of 5 biomarkers previously associated with NSCLC (non‐small cell lung cancer) was measured pre‐treatment. A total of 21 variables were analyzed including: dose‐volume metrics with BED (biologically effective dose) correction and clinical variables. A Markov Chain Monte Carlo technique estimated the posterior probability distribution of the potential graphical structures. The probability of tumor failure was then estimated by averaging the top 100 graphs and applying Baye's rule.Results:The optimal Bayesian model generated throughout this study incorporated the PTV volume, the serum concentration of the biomarker EGFR (epidermal growth factor receptor) and prescription BED. This predictive model recorded an area under the receiver operating characteristic curve of 0.94(1), providing better performance compared to competing methods in other literature.Conclusion:The use of biomarkers in conjunction with dose‐volume metrics allows for the generation of a robust predictive model. The preliminary results of this report demonstrate that it is possible to accurately model the prognosis of an individual lung SBRT patient's treatment.
SU‐F‐R‐47: Quantitative Shape Relationship Analysis of PTV Modification for Critical Anatomy Sparing and Its Impact On Pathologic Response for Neoadjuvant Stereotactic Radiotherapy for Pancreatic Cancer
Authors: Cheng Z , Rosati L , Chen L , Robertson S , Moore J , Peng L , Mian O , Narang A , Hacker‐Prietz A , Herman J , McNutt T 
Published: July 2016

Purpose:Stereotactic body radiation therapy (SBRT) may be used to increase surgery candidacy in borderline resectable (BRPC) and locally advanced (LAPC) pancreatic cancer. However, the planning target volume (PTV) may need to be limited to avoid toxicity when the gross tumor volume (GTV) is anatomically involved with surrounding critical structures. Our study aims to characterize the coverage of GTV and investigate the association between modified PTV and pathologic (pCR) or near pathologic (npCR) complete response rates determined from the surgical specimen.Methods:Patients treated with neoadjuvant pancreas SBRT followed by surgery from 2010–2015 were selected from Oncospace. Overlap volume histogram (OVH) analysis was performed to determine the extent of compromise of the PTV from both the GTV and a standard target (GTV+3mm). Subsequently, normalized overlap volume (%) was calculated for: (1) GTV‐PTV, and (2) GTV+3mm expansion‐PTV. A logistic regression model was used to identify the association between the overlap ratios and ≥ npCR(pCR/npCR) stratified by active breathing control (ABC) versus free‐breathing status.Results:Eighty‐one (BRPC: n=42, LAPC: n=39) patients were available for analysis. Nearly 40% (31/81) had ≥npCR and 75% (61/81) were able to complete ABC. Mean coverage of the GTV‐PTV was 92.6% (range, 59.9%–100%, SD = 8.68) and coverage of the GTV+3mm expansion‐PTV was 85. 2% (range, 59.9% −100.0%, SD= 8.67). Among the patients with ABC, every 10% increase in GTV coverage doubled the odds to have ≥npCR (OR = 1.82, p=0.06). Coverage of GTV+3mm expansion was not associated with ≥npCR regardless of ABC status.Conclusion:Preferential sparing of critical anatomy over GTV‐PTV coverage with ABC management suggests worse ≥npCR rates for neoadjuvant SBRT in BRPC and LAPC. Limiting the GTV and GTV+3mm expansion in free‐breathing patients was not associated with pathologic response perhaps due to larger GTV definitions as a result of motion artifacts in free‐breathing CT scans.Collaboration with Toshiba, Elekta, and Phillips
SU‐F‐R‐50: Radiation‐Induced Changes in CT Number Histogram During Chemoradiation Therapy for Pancreatic Cancer
Authors: Chen X , Schott D , Song Y , Li D , Hall W , Erickson B , Li X 
Published: July 2016

Purpose:In an effort of early assessment of treatment response, we investigate radiation induced changes in CT number histogram of GTV during the delivery of chemoradiation therapy (CRT) for pancreatic cancer.Methods:Diagnostic‐quality CT data acquired daily during routine CT‐guided CRT using a CT‐on‐rails for 20 pancreatic head cancer patients were analyzed. All patients were treated with a radiation dose of 50.4 in 28 fractions. On each daily CT set, the contours of the pancreatic head and the spinal cord were delineated. The Hounsfiled Units (HU) histogram in these contourswere extracted and processed using MATLAB. Eight parameters of the histogram including the mean HU over all the voxels, peak position, volume, standard deviation (SD), skewness, kurtosis, energy, and entropy were calculated for each fraction. The significances were inspected using paired two‐tailed t‐test and the correlations were analyzed using Spearman rank correlation tests.Results:In general, HU histogram in pancreatic head (but not in spinal cord) changed during the CRT delivery. Changes from the first to the last fraction in mean HU in pancreatic head ranged from −13.4 to 3.7 HU with an average of −4.4 HU, which was significant (P<0.001). Among other quantities, the volume decreased, the skewness increased (less skewed), and the kurtosis decreased (less sharp) during the CRT delivery. The changes of mean HU, volume, skewness, and kurtosis became significant after two weeks of treatment. Patient pathological response status is associated with the changes of SD (ΔSD), i.e., ΔSD= 1.85 (average of 7 patients) for good reponse, −0.08 (average of 6 patients) for moderate and poor response.Conclusion:Significant changes in HU histogram and the histogram‐based metrics (e.g., meam HU, skewness, and kurtosis) in tumor were observed during the course of chemoradiation therapy for pancreas cancer. These changes may be potentially used for early assessment of treatment response.
SU‐F‐R‐55: Early Detection of Treatment Induced Bone Marrow Injury During Chemoradiation Therapy Using Quantitative CT
Authors: Chen X , Song Y , Erickson B , Li X 
Published: July 2016

Purpose:Acute hematologic toxicity associated with bone marrow injury is a common complication of chemoradiation therapy (CRT) for pelvic malignancies. In this work, we investigate the feasibility of using quantitative CT to detect bone marrow injury during CRT.Methods:Daily CTs were acquired during routine CT‐guided radiation therapy using a CT‐on‐rails for 15 cervical cancer patients. All patients treated with a radiation dose of 45.0 to 50.4 Gy in 1.8 Gy/fraction along with chemotherapy. For each patient, the contours of bone marrow were generated in L4, L5 and sacrum on the first daily CT and then populated to other daily CTs by rigid registration using MIM (MIM Software Inc., Cleveland, OH) with manual editing if possible. A series of CT texture parameters, including Hunsfield Unit (HU) histogram, mean HU, entropy, energy, in bone marrow contours were calculated using MATLAB on each daily CT and were correlated with the completed blood counts (CBC) collected weekly for each patient. The correlations were analyzed with Pearson correlation tests.Results:For all patient data analyzed, mean HU in bone marrow decreased during CRT delivery. From the first to the last fraction the average mean HU reduction is 58.1 ± 13.6 HU (P<0.01). This decrease can be observed as early as after first 5 fractions and is strongly associated with the changes of most CBC quantities, such as the reductions of white and blood cell counts (r=0.97, P=0.001). The reduction of HU is spatially varied.Conclusion:Chemoradiation induced bone marrow injury can be detected during the delivery of CRT using quantitative CT. Chemoradiation results in reductions in mean HU, which are strongly associated with the change in the pretrial blood cell counts. Early detection of bone marrow injury with commonly available CT opens a door to improve bone marrow sparing, reducing risk of hematologic toxicity.
SU‐F‐I‐01: Normalized Mean Glandular Dose Values for Dedicated Breast CT Using Realistic Breast‐Shaped Phantoms
Authors: Hernandez A , Boone J 
Published: July 2016

Purpose:To estimate normalized mean glandular dose values for dedicated breast CT (DgN‐CT) using breast CT‐derived phantoms and compare to estimations using cylindrical phantoms.Methods:Segmented breast CT (bCT) volume data sets (N=219) were used to measure effective diameter profiles and were grouped into quintiles by volume. The profiles were averaged within each quintile to represent the range of breast sizes found clinically. These profiles were then used to generate five voxelized computational phantoms (V1, V2, V3, V4, V5 for the small to large phantom sizes, respectively), and loaded into the MCNP6 lattice geometry to simulate normalized mean glandular dose coefficients (DgN‐CT) using the system specifications of the Doheny‐prototype bCT scanner in our laboratory. The DgN‐CT coefficients derived from the bCT‐derived breast‐shaped phantoms were compared to those generated using a simpler cylindrical phantom using a constant volume, and the following constraints: (1) Length=1.5*radius; (2) radius determined at chest wall (Rcw), and (3) radius determined at the phantom center‐of‐mass (Rcm).Results:The change in Dg‐NCT coefficients averaged across all phantom sizes, was ‐ 0.5%, 19.8%, and 1.3%, for constraints 1–3, respectively. This suggests that the cylindrical assumption is a good approximation if the radius is taken at the breast center‐of‐mass, but using the radius at the chest wall results in an underestimation of the glandular dose.Conclusion:The DgN‐CT coefficients for bCT‐derived phantoms were compared against the assumption of a cylindrical phantom and proved to be essentially equivalent when the cylinder radius was set to r=1.5/L or Rcm. While this suggests that for dosimetry applications a patient's breast can be approximated as a cylinder (if the correct radius is applied), this assumes a homogenous composition of breast tissue and the results may be different if the realistic heterogeneous distribution of glandular tissue is considered.Research reported in this paper was supported in part by the National Cancer Institute of the National Institutes of Health under award R01CA181081. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institue of Health.