Deep learning based linear energy transfer calculation for proton therapy.

Objective.This study aims to address the limitations of traditional methods for calculating linear energy transfer (LET), a critical component in assessing relative biological effectiveness (RBE). Currently, Monte Carlo (MC) simulation, the gold-standard for accuracy, is resource-intensive and slow for dose optimization, while the speedier analytical approximation has compromised accuracy. Our objective was to prototype a deep-learning-based model for calculating dose-averaged LET (LETd) using patient anatomy and dose-to-water (DW) data, facilitating real-time biological dose evaluation and LET optimization within proton treatment planning systems.Approach. 275 4-field prostate proton Stereotactic Body Radiotherapy plans were analyzed, rendering a total of 1100 fields. Those were randomly split into 880, 110, and 110 fields for training, validation, and testing. A 3D Cascaded UNet model, along with data processing and inference pipelines, was developed to generate patient-specific LETddistributions from CT images and DW. The accuracy of the LETdof the test dataset was evaluated against MC-generated ground truth through voxel-based mean absolute error (MAE) and gamma analysis.Main results.The proposed model accurately inferred LETddistributions for each proton field in the test dataset. A single-field LETdcalculation took around 100 ms with trained models running on a NVidia A100 GPU. The selected model yielded an average MAE of 0.94 ± 0.14 MeV cm-1and a gamma passing rate of 97.4% ± 1.3% when applied to the test dataset, with the largest discrepancy at the edge of fields where the dose gradient was the largest and counting statistics was the lowest.Significance.This study demonstrates that deep-learning-based models can efficiently calculate LETdwith high accuracy as a fast-forward approach. The model shows great potential to be utilized for optimizing the RBE of proton treatment plans. Future efforts will focus on enhancing the model's performance and evaluating its adaptability to different clinical scenarios.

Proton versus photon craniospinal irradiation for adult medulloblastoma: A dosimetric, toxicity, and exploratory cost analysis.

Background: This study aimed to determine whether proton craniospinal irradiation (CSI) decreased the dose to normal tissue and resulted in less toxicity than photon CSI for adult patients. Methods: This single-institution retrospective analyzed differences in radiation doses, acute toxicity, and cost between proton and CSI for adult medulloblastoma patients. Results: Of 39 total patients, 20 were treated with photon CSI prior to 2015, and 19 were treated with proton CSI thereafter. Median age was 28 years (range 18-66). The molecular subtype was most commonly sonic hedgehog (68%). Patients most commonly received 36 Gy CSI in 20 fractions with a boost to 54-55.8 Gy (92%). Proton CSI delivered significantly lower mean doses to cochleae, lacrimal glands, lens, parotid glands, pharyngeal constrictors, esophagus, lungs, liver, and skin (all P < .001). Patients receiving proton CSI had significantly lower rates of acute dysphagia of any grade (5% versus 35%, P = .044) and decreased median weight loss during radiation (+1.0 versus -2.8 kg, P = .011). Weight loss was associated with acute hospitalization (P = .009). Median follow-up was 2.9 and 12.9 years for proton and photon patients, respectively, limiting late toxicity and outcome comparisons. At the last follow-up, 5 photon patients had died (2 of progressive disease, 3 without recurrence ages 41-63) and 21% had experienced major cardiovascular events. At 10 years, 89% were alive and 82% were recurrence free. Conclusions: This study demonstrates dosimetric improvements with proton CSI, potentially leading to decreased acute toxicity including dysphagia and weight loss during treatment.

Cost effectiveness of treatment strategies for high risk prostate cancer.

BACKGROUND: Patients with high-risk prostate cancer (HRPC) have multiple accepted treatment options. Because there is no overall survival benefit of one option over another, appropriate treatment must consider patient life expectancy, quality of life, and cost. METHODS: The authors compared quality-adjusted life years (QALYs) and cost effectiveness among treatment options for HRPC using a Markov model with three treatment arms: (1) external-beam radiotherapy (EBRT) delivered with 20 fractions, (2) EBRT with 23 fractions followed by low-dose-rate (LDR) brachytherapy boost, or (3) radical prostatectomy alone. An exploratory analysis considered a simultaneous integrated boost according to the FLAME trial (ClinicalTrials.gov identifier NCT01168479). RESULTS: Treatment strategies were compared using the incremental cost-effectiveness ratio (ICER). EBRT with LDR brachytherapy boost was a cost-effective strategy (ICER, $20,929 per QALY gained). These results were most sensitive to variations in the biochemical failure rate. However, the results still demonstrated cost effectiveness for the brachytherapy boost paradigm, regardless of any tested parameter ranges. Probabilistic sensitivity analysis demonstrated that EBRT with LDR brachytherapy was favored in 52% of 100,000 Monte Carlo iterations. In an exploratory analysis, EBRT with a simultaneous integrated boost was also a cost-effective strategy, resulting in an ICER of $62,607 per QALY gained; however, it was not cost effective compared with EBRT plus LDR brachytherapy boost. CONCLUSIONS: EBRT with LDR brachytherapy boost may be a cost-effective treatment strategy compared with EBRT alone and radical prostatectomy for HRPC, demonstrating high-value care. The current analysis suggests that a reduction in biochemical failure alone can result in cost-effective care, despite no change in overall survival.

Assessment of Familiarity With Work-up Guidelines for Bone and Soft Tissue Sarcoma Among Primary Care Practitioners in Minnesota.

OBJECTIVE: To assess familiarity with sarcoma guidelines among primary care practitioners (PCPs) in Minnesota. PARTICIPANTS AND METHODS: Surveys were distributed at 2 educational conferences held in Minnesota on April 16-17, 2015, and October 24, 2015. The PCPs were asked a series of questions about their current practice, past experience with sarcoma, and familiarity with sarcoma guidelines. They were then given a series of case presentations and asked to indicate if they would pursue a sarcoma work-up given the information provided. RESULTS: The study group included 80 physicians and 32 nurse practitioners (NPs). Over their careers (median, 14 years), physicians reported seeing a mean of 2.2 cases of soft tissue sarcoma and 0.7 cases of bone sarcoma. The NPs reported seeing a mean of 0.7 and 0.2 cases, respectfully, over their careers (median, 8 years). Both physicians and NPs reported low familiarity with sarcoma guidelines. When challenged with case presentations for which urgent referral to a sarcoma specialist is recommended, more than 50% of PCPs did not indicate that they would refer patients. The PCPs who had previous experience with soft tissue sarcoma and bone sarcoma estimated that only 17% and 23% of their patients, respectively, were diagnosed within 1 month of presentation. The most reported reason for a delayed diagnosis was the PCP advising the patient to "watch and wait." CONCLUSION: Minnesota PCPs have seen very few cases of sarcoma and report low familiarity with sarcoma guidelines. When challenged with case presentations, PCPs made decisions inconsistent with established guidelines. This study supports ongoing efforts to increase sarcoma awareness.