Citations

AbstractBackgroundBolus materials have been used for decades in radiotherapy. Most frequently, these materials are utilized to bring dose closer to the skin surface to cover superficial targets optimally. While cavity filling, such as nasal cavities, is desirable, traditional commercial bolus is lacking, requiring other solutions. Recently, investigators have worked on utilizing 3D printing technology, including commercially available solutions, which can overcome some challenges with traditional bolus.PurposeTo utilize failure modes and effects analysis (FMEA) to successfully implement a comprehensive 3D printed bolus solution to replace commercial bolus in our clinic using a series of open‐source (or free) software products.Methods3D printed molds for bespoke bolus were created by exporting the DICOM structures of the bolus designed in the treatment planning system and manipulated to create a multipart mold for 3D printing. A silicone (Ecoflex 00–30) mixture is poured into the mold and cured to form the bolus. Molds for sheet bolus of five thicknesses were also created. A comprehensive FMEA was performed to guide workflow adjustments and QA steps.ResultsThe process map identified 39 and 30 distinct steps for the bespoke and flat sheet bolus workflows, respectively. The corresponding FMEA highlighted 119 and 86 failure modes, with 69 shared between the processes. Misunderstanding of plan intent was a potential cause for most of the highest‐scoring failure modes, indicating that physics and dosimetry involvement early in the process is paramount.ConclusionFMEA informed the design and implementation of QA steps to guarantee a safe and high‐quality comprehensive implementation of silicone bolus from 3D printed molds. This approach allows for greater adaptability not afforded by traditional bolus, as well as potential dissemination to other clinics due to the open‐source nature of the workflow.

AbstractPurposeTo assess the practicality of employing a commercial knowledge‐based planning tool (RapidPlan) to generate adapted intact prostate and prostate bed volumetric modulated arc therapy (VMAT) plans on iterative cone‐beam computed tomography (iCBCT) datasets.Methods and materialsIntact prostate and prostate bed RapidPlan models were trained utilizing planning data from 50 and 44 clinical cases, respectively. To ensure that refined models were capable of producing adequate clinical plans with a single optimization, models were tested with 50 clinical planning CT datasets by comparing dose‐volume histogram (DVH) and plan quality metric (PQM) values between clinical and RapidPlan‐generated plans. The RapidPlan tool was then used to retrospectively generate adapted VMAT plans on daily iCBCT images for 20 intact prostate and 15 prostate bed cases. As before, DVH and PQM metrics were utilized to dosimetrically compare scheduled (iCBCT Verify) and adapted (iCBCT RapidPlan) plans. Timing data was collected to further evaluate the feasibility of integrating this approach within an online adaptive radiotherapy workflow.ResultsModel testing results confirmed the models were capable of producing VMAT plans within a single optimization that were overall improved upon or dosimetrically comparable to original clinical plans. Direct application of RapidPlan on iCBCT datasets produced satisfactory intact prostate and prostate bed plans with generally improved target volume coverage/conformality and rectal sparing relative to iCBCT Verify plans as indicated by DVH values, though bladder metrics were marginally increased on average. Average PQM values for iCBCT RapidPlans were significantly improved compared to iCBCT Verify plans. The average time required [in mm:ss] to generate adapted plans was 06:09 ± 02:06 (intact) and 07:12 ± 01:04 (bed).ConclusionThis study demonstrated the feasibility of leveraging RapidPlan to expeditiously generate adapted VMAT intact prostate and prostate bed plans on iCBCT datasets. In general, adapted plans were dosimetrically improved relative to scheduled plans, emphasizing the practicality of the proposed approach.

Abstract The ZRSR2 gene is a member of the spliceosome gene family which are frequently mutated in myeloid neoplasms. ZRSR2 mutations (ZRSR2m) occur in less than 5% of MDS, CMML, and AML. Our study included 164 ZRSR2m patients (98.8% males) and 98 ZRSR2wt MDS control cohort. In the ZRSR2m group, there were 53 MDS (32%), 39 CCUS (24%), 33 MPN (20%), 23 MDS/MPN overlap (14%), 15 AML (9%), and 1 MPAL (0.6%). Most MDS patients were the low blast subtype (n=37, 70%). Twenty-seven MDS patients (51%), and 23 CCUS patients (59%) had absolute monocyte count ≥0.5 x109/L and 18 of 23 MDS/MPN overlap were CMML (78%). Mutations in ZRSR2 were spread across the entire gene. The median number of co-mutations was 2, with TET2 (51%) and ASXL1 (32%) being the most common. U2AF1 and SRSF2, previously described as mutually exclusive with ZRSR2, were found in 10.4% of patients. Median overall survival (OS) was 51 months, and significantly varied among MNs (p=0.004). ZRSR2m MDS patients had better mOS than the MDS control cohort with ZRSR2wt (35 vs 22 months, p=0.013). ZRSR2m patients with isolated TET2 co-mutation and higher hemoglobin showed improved survival, while patients with RUNX1m, higher WBC count showed worse OS.

Purpose: This study aimed to develop a retrained large language model (LLM) tailored to the needs of HN cancer patients treated with radiotherapy, with emphasis on symptom management and survivorship care. Methods: A comprehensive external database was curated for training ChatGPT-4, integrating expert-identified consensus guidelines on supportive care for HN patients and correspondences from physicians and nurses within our institution’s electronic medical records for 90 HN patients. The performance of our model was evaluated using 20 patient post-treatment inquiries that were then assessed by three Board certified radiation oncologists (RadOncs). The rating of the model was assessed on a scale of 1 (strongly disagree) to 5 (strongly agree) based on accuracy, clarity of response, completeness s, and relevance. Results: The average scores for the 20 tested questions were 4.25 for accuracy, 4.35 for clarity, 4.22 for completeness, and 4.32 for relevance, on a 5-point scale. Overall, 91.67% (220 out of 240) of assessments received scores of 3 or higher, and 83.33% (200 out of 240) received scores of 4 or higher. Conclusion: The custom-trained model demonstrates high accuracy in providing support to HN patients offering evidence-based information and guidance on their symptom management and survivorship care.

7050 Background: The management of Richter transformation (RT) of CLL represents an unmet clinical need. We previously reported modest efficacy of pembrolizumab monotherapy in an initial cohort of patients with RT (Ding, et al, Blood 2017). Here we report updated results of this trial, including an expansion cohort and a combination therapy cohort. Methods: Patients with biopsy proven RT to diffuse large B-cell lymphoma were enrolled and treated with single agent pembrolizumab (200 mg IV Q3W). Patients with progressive disease (PD) or stable disease (SD) after 3 months of pembrolizumab monotherapy were allowed to add a B-cell receptor (BCR) kinase inhibitor. The primary end point was overall response rate (ORR). Results: A total of 26 patients with RT were enrolled (9 in initial cohort and 17 in expansion cohort). The median age was 68.5 years. Ten (38%) patients had del(17p) or TP53 mutation. The median number of prior lines of therapy was 3 (range 1-10). Fifteen (58%) patients had received ibrutinib previously (14 of whom had PD on ibrutinib). With pembrolizumab monotherapy (n=26), the ORR was 23.1%, with 2 (7.7%) complete response (CR), 4 (15.4%) partial response (PR), and 7 (26.9%) SD. Of the 6 patients with confirmed CR or PR, responses occurred after a median of 2 cycles of monotherapy. The median duration of response (DOR) was 3.2 months (95% CI 2.8-NA). The median progression-free survival (PFS) was 2.6 months (95% CI 1.6-3.6). Sixteen patients went on to receive a BCR kinase inhibitor (ibrutinib [n=15], idelalisib [n=1]) in combination with pembrolizumab, after SD or PD on pembrolizumab monotherapy. The ORR to combination therapy was 62.5%, with 4 (25.0%) CR and 6 (37.5%) PR. Of the 10 patients with confirmed CR or PR to combination therapy, responses occurred after a median of 4 cycles of therapy. The median DOR was 4.5 months (95% CI 1.6-NA). The median PFS was 7.6 months (95% CI 2.3-13.3). After a median follow-up of 50.4 (95% CI 34.0-56.0) months, the median overall survival (OS) for all 26 patients with RT was 11.6 months (95% CI 7.5-20.1), and the 2-year OS rate was 27%. Treatment-related adverse events (TRAEs) of any grade occurred in 24 (92%) patients, including anemia (54%), thrombocytopenia (58%), neutropenia (54%), leukopenia (35%), lymphopenia (23%), dyspnea (23%), diarrhea (19%), and nausea (23%). Treatment-related grade 3 or above AEs occurred in 21 (81%) patients, including neutropenia (38%), leukopenia (31%), thrombocytopenia (27%), anemia (15%), febrile neutropenia (12%), and lung infection (12%). Conclusions: This expanded analysis confirmed that pembrolizumab has modest single agent activity in RT. Combination therapy with pembrolizumab and a BCR kinase inhibitor is associated with increased efficacy (ORR >60%), similar to other reports. These results support further investigation of immune checkpoint inhibitor-based combination therapy in RT. Clinical trial information: NCT02332980 .