Radiological imaging has a critical role in the diagnosis of sarcomas and in evaluating therapy response assessment. The current gold standard for response assessment in solid tumors is the Response Evaluation Criteria in Solid Tumors, which evaluates changes in tumor size as a surrogate endpoint for therapeutic efficacy. However, tumors may undergo necrosis, changes in vascularization or become cystic in response to therapy, with no significant volume changes; thus, size assessments alone may not be adequate. Such morphological changes may give rise to radiographic phenotypes that are not easily detected by human operators. Fortunately, recent advances in high-performance computing and machine learning algorithms have enabled deep analysis of radiological images to extract features that can provide richer information about intensity, shape, size or volume, and texture of tumor phenotypes. There is growing evidence to suggest that these image-derived or “radiomic features” are sensitive to biological processes such as necrosis and glucose metabolism. Thus, radiomics could prove to be a critical tool for assessing treatment response and may present an integral complement to existing response criteria, opening new avenues for patient assessment in sarcoma trials.

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Purpose: To determine the Planning Target Volume (PTV) margin for Hypofractionated Partial Breast Irradiation (HPBI) using the van Herk formalism (M=2.5∑+0.7σ). HPBI is a novel technique intended to provide local control in breast cancer patients not eligible for surgical resection, using 40 Gy in 5 fractions prescribed to the gross disease. Methods: Setup uncertainties were quantified through retrospective analysis of cone‐beam computed tomography (CBCT) data sets, collected prior to (prefraction) and after (postfraction) treatment delivery. During simulation and treatment, patients were immobilized using a wing board and an evacuated bag. Prefraction CBCT was rigidly registered to planning 4‐dimensional computed tomography (4DCT) using the chest wall and tumor, and translational couch shifts were applied as needed. This clinical workflow was faithfully reproduced in Pinnacle (Philips Medical Systems) to yield residual setup and intrafractional error through translational shifts and rigid registrations (ribs and sternum) of prefraction CBCT to 4DCT and postfraction CBCT to prefraction CBCT, respectively. All ten patients included in this investigation were medically inoperable; the median age was 84 (range, 52–100) years. Results: Systematic (and random) setup uncertainties (in mm) detected for the left‐right, craniocaudal and anteroposterior directions were 0.4 (1.5), 0.8 (1.8) and 0.4 (1.0); net uncertainty was determined to be 0.7 (1.5). Rotations >2° in any axis occurred on 8/72 (11.1%) registrations. Conclusion: Preliminary results suggest a non‐uniform setup margin (in mm) of 2.2, 3.3 and 1.7 for the left‐right, craniocaudal and anteroposterior directions is required for HPBI, given its immobilization techniques and online setup verification protocol. This investigation is ongoing, though published results from similar studies are consistent with the above findings. Determination of margins in breast radiotherapy is a paradigm shift, but a necessary step in moving towards hypofractionated regiments, which may ultimately redefine the standard of care for this select patient population.

rated whether proposed definitions fell within the range of standard practice patterns with both discrete choice and free-text responses. ROs also rated the adequacy of a proposed evaluation scheme that involved pre-targeting discussions and post-targeting review between the CSRT and a RO mentor when grades of no change, minor change or major change would be assigned to CSRT fields and target volumes. Benefits/Challenges: Compliance among the radiation oncologists to complete the survey was challenging. Since the surveys were collected by their administrative assistants, it was an issue to determine which RO's completed the survey and which had not. The survey did however help to define the range of standard practice patterns at TOH for field placement and target volume definition for bone metastases requiring conventional palliative RT. Impact: Most ROs deemed the proposed list of anatomic sites as comprehensive and the evaluation scheme as adequate. Most ROs deemed the proposed field and target definitions as falling within or partially falling within the range of standard practice patterns. Specific points of free-text discussion included field borders for vertebral metastases that included adjacent uninvolved levels or dissected vertebral bodies, the confidence with which CTVs for bone metastases can be defined, the exclusion of presumed uninvolved vertebral lateral processes from CTVs, and the need to include definitions for post-operative RT. This benchmark has informed the design of an ongoing scheme to evaluate CSRT competency for these skills.

were (1) construction of a prototype high-speed proton residual range detector, (2) analysis of the range detector test beam and simulation data, and (3) construction and testing of a high-speed proton tracking detector prototype. Results: We have built a prototype residual range detector with all the features required. The prototype meets our requirements of high-speed operation and optimal resolution. The performance in test proton beams agrees very well with detailed Geant4 simulations. (Detailed graphs, figures, and data will be presented at the meeting). Conclusion: The combination of high performance, simple monolithic construction, and reduced electronics channel count will enable us to design a low-cost system, which will allow us to start testing strategies to optimize PBT treatments and maintain patient throughput. Use of a proton beam for imaging and range determination appears feasible, practical, and economical. This "apples to apples" comparison could prove superior to the use of X rays for imaging and range determination in certain aspects. Tests are now underway using our prototype.