Alveolar soft part sarcoma (ASPS) is a rare soft tissue sarcoma with high metastatic potential and limited response to systemic therapy. Biomarkers that predict which patients may benefit from emerging immune checkpoint inhibitors (ICIs) continue to surface. We report a case of stage IV ASPS with extensive pulmonary metastases and high PD-L1 expression that exhibited a marked response to atezolizumab, a PD-L1 antagonist. A 35-year-old man presented to an outside institution in October 2023 with a painless, progressively enlarging left thigh mass. Magnetic resonance imaging (MRI) demonstrated a 7.5 × 4.5 × 14 cm heterogeneous intramuscular lesion. Chest computed tomography (CT) revealed innumerable bilateral pulmonary metastases. Transthoracic biopsy of a pulmonary nodule confirmed stage IV ASPS with strong nuclear TFE3 positivity, Cathepsin K positivity, retained INI1 expression, and PD-L1 expression in 90-100% of malignant cells. The primary lesion was not characterized separately. Following transfer to our institution, atezolizumab was initiated in December 2023. At 3 months, chest CT demonstrated a marked regression of pulmonary metastases. Many resolved completely while others showed significant interval decrease in size. At 8 months, chest CT demonstrated further regression in size, number, and density of the pulmonary metastases. Only micronodules remained. At 12 months, chest CT demonstrated that all remaining pulmonary micronodules were stable without new or progressive disease. The primary lesion was treated with neoadjuvant hypofractionated radiotherapy and wide local resection. Post-operative histopathology of the primary lesion demonstrated >99% tumor necrosis with negative margins. This patient achieved a partial response of the primary thigh mass per Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 and an immune partial response per immune RECIST (iRECIST). Moreover, this patient experienced a near-complete resolution of pulmonary metastatic disease sustained for 27 months despite an extensive metastatic burden. This case illustrates that substantial disease burden does not preclude meaningful, durable response to ICIs. Moreover, it raises the possibility that high PD-L1 expression may contribute to immune evasion. However, this observation was based on a metastatic biopsy. Prospective acquisition of standardized PD-L1 assay data, fusion-variant genotyping, and tumor-infiltrating lymphocyte profiles in future cases could inform individualized prognostication.

Pelvic organ prolapse occurring shortly after hysterectomy is rare but may complicate adjuvant external beam radiation therapy (EBRT) in endometrial cancer. Delivering EBRT in the presence of prolapse may increase radiation exposure to adjacent organs and treatment-related toxicity, whereas surgical correction can delay adjuvant therapy. We describe a technically feasible, nonsurgical approach using a vaginal pessary to restore pelvic anatomy and facilitate EBRT planning. Pessary-assisted repositioning improved target delineation and reduced high-dose exposure to the bladder, vagina, and rectum without delaying treatment or causing toxicity. This Technical Report highlights a simple, patient-centered strategy to optimize radiation therapy delivery in complex posthysterectomy anatomy.

BACKGROUND AND PURPOSE:Stereotactic body radiotherapy (SBRT) is increasingly used for localized prostate cancer, but data on SBRT with pelvic nodal irradiation in patients with high-risk disease remain limited. We report late genitourinary (GU) and gastrointestinal (GI) toxicities and clinical outcomes in patients with high-risk prostate cancer treated with SBRT in 5 fractions to the prostate and pelvic lymph nodes. MATERIALS AND METHODS:We reviewed 101 patients with high-risk prostate cancer treated with SBRT between August 2019 and May 2023. Treatment consisted of 36.25 Gy in 5 fractions to the prostate with a simultaneous dose of 25 Gy to the pelvic lymph nodes. Patients received 6 to 18 months of androgen deprivation therapy. Toxicity was prospectively assessed according to CTCAE version 4.0. Late toxicity was defined as events occurring ≥ 3 months after SBRT. Survival outcomes were estimated using Kaplan-Meier methods. RESULTS:All patients had a minimum follow-up of 24 months. With a median follow-up of 43.8 months (range 26-70 months), late grade 1 and 2 GI toxicity occurred in 4 patients (4%), including three cases of rectal bleeding and one case of fecal incontinence. Late grade 1 and 2 GU toxicity occurred in 13 patients (13%), including 5 grade 2 events (5%). No grade ≥ 3 GI or GU toxicity was observed. The 5-year actuarial biochemical recurrence-free survival was 89.5%, with distant metastasis-free survival of 96.2% and overall survival of 98.8%. CONCLUSION:SBRT delivered in five fractions with pelvic nodal irradiation appears feasible and associated with low rates of late GU and GI toxicity in patients with high-risk prostate cancer. Ongoing randomized trials will provide definitive evidence regarding the role of SBRT with pelvic nodal irradiation in this population.

BACKGROUND:As auto-segmentation tools become integral to radiotherapy, more commercial products emerge. However, they may not always suit our needs. One notable example is the use of adult-trained commercial software for the contouring of organs at risk (OARs) of pediatric patients. PURPOSE:This study aimed to compare three auto-segmentation approaches in the context of pediatric craniospinal irradiation (CSI): commercial, out-of-the-box, and in-house. METHODS:CT scans from 142 pediatric patients undergoing CSI were obtained from St. Jude Children's Research Hospital (training: 115; validation: 27). A test dataset comprising 16 CT scans was collected from the McGill University Health Centre. All images underwent manual delineation of 18 OARs. LimbusAI v1.7 served as the commercial product, while nnU-Net was trained for benchmarking. Additionally, a two-step in-house approach was pursued where smaller 3D CT scans containing the OAR of interest were first recovered and then used as input to train organ-specific models. Three variants of the U-Net architecture were explored: a basic U-Net, an attention U-Net, and a 2.5D U-Net. The dice similarity coefficient (DSC) assessed segmentation accuracy, and the DSC trend with age was investigated (Mann-Kendall test). A radiation oncologist determined the clinical acceptability of all contours using a five-point Likert scale. RESULTS:Differences in the contours between the validation and test datasets reflected the distinct institutional standards. The lungs and left kidney displayed an increasing age-related trend of the DSC values with LimbusAI on the validation and test datasets. LimbusAI contours of the esophagus were often truncated distally and mistaken for the trachea for younger patients, resulting in a DSC score of less than 0.5 on both datasets. Additionally, the kidneys frequently exhibited false negatives, leading to mean DSC values that were up to 0.11 lower on the validation set and 0.07 on the test set compared to the other models. Overall, nnU-Net achieved good performance for body organs but exhibited difficulty differentiating the laterality of head structures, resulting in a large variation of DSC values with the standard deviation reaching 0.35 for the lenses. All in-house models generally had similar DSC values when compared against each other and nnU-Net. Inference time on the test data was between 47-55 min on a Central Processing Unit (CPU) for the in-house models, while it was 1h 21m with a V100 Graphics Processing Unit (GPU) for nnU-Net. CONCLUSIONS:LimbusAI could not adapt well to pediatric anatomy for the esophagus and the kidneys. When commercial products do not suit the study population, the nnU-Net is a viable option but requires adjustments. In resource-constrained settings, the in-house model provides an alternative. Implementing an automated segmentation tool requires careful monitoring and quality assurance regardless of the approach.

Purpose: This study aims to evaluate the performance of Atlas and neural network autosegmentation methods and develop a knowledge-based quality assurance (QA) tool for pediatric craniospinal irradiation (CSI). Methods and Materials: Autosegmentation was performed on 63 CSI patients using 3 methods: Atlas, commercial artificial intelligence (AI), and in-house AI. The performance of these methods was analyzed using 13 quantitative metrics, comprising 6 overlap and 7 distance metrics, across 13 critical organs and a linear mixed-effect model analysis was performed. Additionally, a knowledge-based QA tool was developed by leveraging distinctive computed tomography number distributions from 100 CSI patients for each organ, using the kernel density estimation (KDE) method to ensure robust error detection and validation. The QA tool was tested on 50 CSI cases by comparing baseline KDEs from 100 CSI patients. Results: The linear mixed-effect analysis showed that the in-house AI outperformed both the Atlas and commercial AI methods in overlap and distance metrics. The in-house AI outperformed the commercial AI with a higher average overlap of 0.01 ± 0.01 and surpassed the Atlas method by 0.02 ± 0.01. In terms of distance metrics, the in-house AI matched the commercial AI (–0.31 ± 0.72 mm) and exceeded the Atlas method by 3.10 ± 0.68 mm. Paired t-tests showed the in-house AI was superior to the Atlas in 13.0% of cases, while the Atlas outperformed the in-house method in 8.9% of comparisons. Similarly, the in-house AI was better than the commercial AI in 35.3% of tests, with the commercial AI outperforming in 32.7%. The QA tool results demonstrated that 100% agreement with baseline KDEs occurred in 46.4% of tests for Atlas, 46.5% for the commercial AI, and 60.7% for the in-house AI. Conclusions: The in-house AI excelled over the Atlas and commercial AI methods in autosegmentation accuracy for pediatric CSI patients. Furthermore, a knowledge-based QA tool enables clinicians to detect and correct gross errors in autosegmentation.

INTRODUCTION:High-dose rate brachytherapy (HDRB) monotherapy has proven effective in managing low- and intermediate-risk prostate cancer (IRPC). This study aims to evaluate patterns of relapse, treatment-related toxicity, and tumor control in patients with IRPC treated with a single fraction of HDRB monotherapy. METHODOLOGY:We reviewed IRPC patients treated with HDRB monotherapy delivered as a single 21 Gy fraction between January 2015 and December 2021. Clinical data, treatment parameters, and outcomes were extracted from medical records. Radiological local recurrences diagnosed by a blinded genitourinary radiologist were confirmed by biopsy. We performed dosimetric analysis of recurrent intraprostatic nodules. Toxicities were graded using CTCAE v4. We report 3- and 5-year biochemical relapse-free survival (bRFS), locoregional relapse-free survival (LRRFS), and overall survival (OS). RESULTS:87 patients were included (median follow-up: 51.1 months). Biochemical failure occurred in 24.1 % of patients, including local relapse in 16.1 %. Using Cox proportional-hazards model, higher baseline PSA and unfavorable intermediate-risk (UIR) category were associated with an increased local relapse risk (HR 1.2 [95 % CI 1.0-1.42], p = 0.013; HR 4.52 [95 % CI 1.4-14.1], p = 0.01, respectively), whereas a greater prostatic volume receiving 100 % of the prescription dose was protective (HR 0.85 [95 % CI 0.75-0.96]). Dosimetric analyses of recurrences (D98% = 21.6 Gy, D90% = 23.7 Gy, Dmean = 30.6 Gy) showed no association with failure. The 5-year bRFS rate for favorable intermediate-risk (FIR) patients was 83.4 %, and for UIR patients 59.3 %. The 5-year LRRFS rate was 82.6 % for FIR and 76.9 % for UIR patients. The 5-year OS was 96.6 %. Acute grade ≥ 3 genitourinary toxicities occurred in 5.7 % of patients, and late grade ≥ 3 toxicity in 1.1 %. No grade ≥ 2 gastrointestinal toxicity was observed. CONCLUSION:A single 21 Gy fraction of HDR brachytherapy monotherapy for IRPC appears feasible and safe, yielding a 5-year bRFS of 83.4 % for FIR and 59.3 % for UIR patients. Patterns of failure were not attributable to inadequate dosimetric coverage. Higher baseline PSA levels and UIR classification were associated with an increased risk of local failure.

PURPOSE:High dose rate (HDR) prostate brachytherapy (BT) procedure requires image-guided needle insertion. Given that general anesthesia is often employed during the procedure, minimizing overall planning time is crucial. In this study, we explore the clinical feasibility and time-saving potential of artificial intelligence (AI)-driven auto-reconstruction of transperineal needles in the context of ultrasound (US)-guided prostate BT planning. METHODS AND MATERIALS:This study included a total of 102 US-planned BT images from a single institution and split into 3 groups: 50 for model training and validation, 11 to evaluate reconstruction accuracy (test set), and 41 to evaluate the AI tool in a clinical implementation (clinical set). Reconstruction accuracy for the test set was evaluated by comparing the performance of AI-derived and manually reconstructed needles from 5 medical physicists on the 3D-US scans after treatment. The needle total reconstruction time for the clinical set was defined as the timestamp difference from scan acquisition to the start of dose calculations and was compared with values recorded before the clinical implementation of the AI-assisted tool. RESULTS:A mean error of (0.44 ± 0.32) mm was found between the AI-reconstructed and the human consensus needle positions in the test set, with 95.0% of AI needle points falling below 1 mm from their human-made counterparts. Post-hoc analysis showed that only one of the human observers' reconstructions were significantly different from the others including the AIs. In the clinical set, the AI algorithm achieved a true positive reconstruction rate of 93.4% with only 4.5% of these needles requiring manual corrections from the planner before dosimetry. Total time required to perform AI-assisted catheter reconstruction on clinical cases was on average 15.2 min lower (P < .01) compared with procedure without AI assistance. CONCLUSIONS:This study demonstrates the feasibility of an AI-assisted needle reconstructing tool for 3D-US-based HDR prostate BT. This is a step toward treatment planning automation and increased efficiency in HDR prostate BT.

Purpose: We aimed to determine if ultrahypofractionated radiation therapy (UHYPO-RT) delivering 6 Gy x 5 fractions yields similar tumor necrosis compared with conventional radiation therapy (CONV-RT) with 2 Gy x 25 fractions in soft tissue sarcoma. The clinical significance of tumor necrosis on loco-regional recurrence-free survival (LRFS), distant disease-free survival (DDFS), and overall survival (OS) were assessed. Methods and Materials: Patients with localized soft tissue sarcoma treated with CONV-RT or UHYPO-RT followed by surgery were included. Good response was defined as tumor necrosis >= 90%, and poor response as <90%. The Mann-Whitney U test compared median tumor necrosis. x2 analysis was used for categorical variables. The Kaplan-Meier function estimated LRFS, DDFS, and OS. Results: A total of 64 patients received CONV-RT, and 45 received UHYPO-RT. The median tumor size was 7.0 cm, with the lower extremity being the most common site (55%). Myxofibrosarcoma (39%) and undifferentiated pleomorphic sarcoma (16%) were the most frequent histologies. The median time from radiation therapy to surgery was 35 days. There was a significant difference in median tumor necrosis between CONV-RT and UHYPO-RT, with rates of 40% and 60%, respectively (P = .022). Patients receiving UHYPORT had a higher percentage of tumor necrosis at the 90% cutoff, achieving 27% compared with 6% for CONV-RT (P = .003). At a median follow-up of 32 months, 12 patients (9%) experienced loco-regional recurrence, 24 patients (19%) faced distant failure, and 19 patients (15%) died of metastatic disease. Patients with <90% necrosis had higher rates of loco-regional (13% vs 0%, P = .207) and distant failure (25% vs 0%, P = .021). Three-year LRFS was 86% for <90% necrosis and 100% for >= 90% necrosis (P = .160). DDFS was 75% for <90% necrosis versus 100% for >= 90% (P = .036). OS rates were 79% and 93%, respectively (P = .290). Conclusions: Preoperative RT with UHYPO-RT was associated with a higher rate of tumor necrosis >= 90% than CONV-RT. Our data suggest that more extensive necrosis is associated with better clinical outcomes. (c) 2024 American Society for Radiation Oncology. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

BACKGROUND AND PURPOSE:Artificial intelligence (AI) may extract prognostic information from MRI for localized prostate cancer. We evaluate whether AI-derived prostate and gross tumor volume (GTV) are associated with toxicity and oncologic outcomes after radiotherapy. MATERIALS AND METHODS:We conducted a retrospective study of patients, who underwent radiotherapy between 2010 and 2017. We trained an AI segmentation algorithm to contour the prostate and GTV from patients treated with external-beam RT, and applied the algorithm to those treated with brachytherapy. AI prostate and GTV volumes were calculated from segmentation results. We evaluated whether AI GTV volume was associated with biochemical failure (BF) and metastasis. We evaluated whether AI prostate volume was associated with acute and late grade 2+ genitourinary toxicity, and International Prostate Symptom Score (IPSS) resolution for monotherapy and combination sets, separately. RESULTS:We identified 187 patients who received brachytherapy (monotherapy (N = 154) or combination therapy (N = 33)). AI GTV volume was associated with BF (hazard ratio (HR):1.28[1.14,1.44];p < 0.001) and metastasis (HR:1.34[1.18,1.53;p < 0.001). For the monotherapy subset, AI prostate volume was associated with both acute (adjusted odds ratio:1.16[1.07,1.25];p < 0.001) and late grade 2 + genitourinary toxicity (adjusted HR:1.04[1.01,1.07];p = 0.01), but not IPSS resolution (0.99[0.97,1.00];p = 0.13). For the combination therapy subset, AI prostate volume was not associated with either acute (p = 0.72) or late (p = 0.75) grade 2 + urinary toxicity. However, AI prostate volume was associated with IPSS resolution (0.96[0.93, 0.99];p = 0.01). CONCLUSION:AI-derived prostate and GTV volumes may be prognostic for toxicity and oncologic outcomes after RT. Such information may aid in treatment decision-making, given differences in outcomes among RT treatment modalities.

Purpose/Objective(s) Stereotactic ablative body radiotherapy (SABR) is an emerging non-invasive treatment option for primary renal cell carcinoma (RCC). This study presents findings on the efficacy and toxicity in patients with RCC who underwent treatment at a single center using SABR to the lesion in the kidney. Materials/Methods We retrospectively evaluated the charts of patients treated with ablative RT doses to the kidney. Information was collected on demographic and clinical data, treatment planning, oncological outcomes, and image response evaluation (Response Evaluation Criteria in Solid Tumors [RECIST] v1.1). Survival outcomes were analyzed using Kaplan-Meier estimates and Cox proportional-hazards regression. Data on toxicity are reported according to Common Terminology Criteria for Adverse Events version 4.0, and urinary function was monitored through pre- and post-treatment estimated Glomerular Filtration Rate (eGFR) and creatinine levels. Results Between 2011 and 2023, a total of 72 patients were identified, and 21 patients were excluded from this analysis due to primary transitional cell carcinoma histology. Among the 51 patients analyzed, seven presented with metastatic RCC. The median follow-up was 30 months (interquartile range [IQR] = 13–75), and the median age was 78 years (IQR = 69–84). The median tumor size was 4.48 cm (IQR = 3.27–4.87 cm), and sixteen had hilar involvement. Patients were treated with different dose-fractionation schemes chosen by the treating radiation oncologist: 40 Gy in five fractions (69%), 45 Gy in three fractions (6%), or 24-26 Gy in one fraction (25%); depending on the size and location of the lesion. The mean (± SD) estimated glomerular filtration (eGFR) rate before SABR was 48.8 ± 13.1 mL per minute, which decreased by 3.5 ± 8.2 mL per minute (P = 0.005). The mean (± standard deviation) serum creatinine levels before SABR were 124.3 ± 99.3 µmol/L, which increased by 8.2 ± 36.6 µmol/L (P = 0.077). No patient required dialysis during follow-up. The 2-year OS, LRFS, and DMFS are 81.3%, 93.3%, and 87.7%, respectively. There were no grade 3 toxic effects or treatment-related deaths and only one (2%) patient developed an acute grade 2 chest pain. Conclusion SABR is a safe and effective non-invasive treatment for primary RCC with minimal impact on renal function and very limited side effects. Our data support SABR as a viable option for patients unwilling or unfit to undergo surgery.

Purpose High dose rate (HDR) prostate brachytherapy (BT) procedure requires imaging to guide transperineal needle insertion, either with CT, MR, or ultrasound (US) imaging. US is occasionally favored for its streamlined workflow and when access to other imaging is limited. General anesthesia is often used throughout the procedure, thus minimizing overall planning time is crucial to mitigate potential complications and allow for better management of operating room time. In this study, we explore the accuracy and time-saving potential of AI-driven auto-reconstruction of transperineal needles in the context of US-guided prostate BT planning. Materials and Methods A total of 98 US BT cases from a single institution were used in this work. US images were acquired using a BK3000 US + E14CL4b endocavity biplane transducer and combined into 3D-US datasets using the Oncentra Prostate system from Elekta. Gray value histogram of each 3D-US image was normalized. The data was split into 3 groups: 50 for training and validation (training set), 11 to evaluate reconstruction accuracy (test set #1) and 37 to evaluate the AI tool in a clinical implementation (test set #2). A 3D-UNet machine learning network was used, using human-reconstructed needles during the BT procedure as the reference segmentation mask. Model training was performed using the PyTorch library version 2.0.1 on a NVIDIA Quadro RTX 6000 GPU using Dice loss and AdamW optimizer. A 10-fold cross-validation scheme was employed during training. Reconstruction accuracy for test set #1 was evaluated by having 4 medical physicists manually reconstructing needles on the 3D-US scan after treatments. Ground truth reference needle positions for each observer (AI included) were determined from the other 4 reconstructions using a weighted voting average inspired by the STAPLE algorithm. Reconstruction accuracy was evaluated by taking the root mean squared error from the center of each reconstructed needle to the center of the ground truth needle, on each image axial slice in which the needle was visible by both humans and AI. Interobserver variability was evaluated using one-way ANOVA and Tukey's HSD post-hoc test. The needle total reconstruction time for test set #2 was taken as the timestamp difference from scan acquisition to final modification of the plan before dose calculations. This value was compared to values of the 50 cases done before the clinical implementation of the AI-assisted tool using a two-sample z-test. For this phase, we also measured the true positive rate of needle reconstruction and the # of AI-reconstructed needles that were further adjusted by the human planner. Results A mean error of (0.47±0.31) mm was found between the AI-reconstructed and the ground truth needles in test set #1, with 95.2% of AI needle points falling below 1 mm from their human-made counterparts. One-way ANOVA showed statistical difference between observers (p < 0.01), but post-hoc analysis showed only one of the human observers was significantly different from the others including the AI (α = 0.05). In test set #2, the AI algorithm achieved a true positive reconstruction rate of 93.7% (i.e. an average of 1.02 needles was missed per scan). Of these AI-reconstructed needles, only 5.5% required manual corrections from the planner before needle tip adjustment (using the needle length exiting from the template). Total time required to perform AI-assisted catheter reconstruction on clinical cases was on average 20.6 min, a decrease of 13.8 min (p < 0.01) compared to manual needle reconstruction as performed before the AI tool introduction. Conclusions This study demonstrates the feasibility and performance of an AI tool for transperineal needles reconstruction during 3D-US based HDR prostate BT. AI-generated catheters were within interobserver variability for all but one physicist. This methodology is a step toward treatment planning automation and increased efficiency in BT procedures.

Purpose Drug-eluting stents are the first-line therapy for in-stent restenosis. However, intravascular brachytherapy (IVBT) is used to treat patients whose drug-eluting stents fail. Current clinical dosimetry for IVBT is water-based, i.e., the absorbed dose in the target volume is calculated by assuming that the patient's artery, calcified plaques, metallic stents, and off-centred guidewire from the IVBT delivery system are all water with unit mass density. We have previously developed a Monte Carlo-based dosimetry software, RapidBrachyIVBT, to account for these heterogeneities and allow for dose calculations on optical coherence tomography images (OCT). This study examines the impact of off-centred guidewires on dose inhomogeneity during irradiation, considering scenarios with multiple guidewires, often overlooked in previous studies. Multiple guidewires are used in cases where the source train passes through a bifurcation of blood vessels. Materials and Methods RapidBrachyIVBT, a Monte Carlo dosimetry software based on the Geant4 toolkit, including the Novoste Beta-Cath 3.5F IVBT device with a 90Sr90Y source train, was used. OCT images from a patient undergoing coronary IVBT for recurrent in-stent restenosis treated at Brigham and Women's Hospital (Boston, Massachusetts) were used to calculate the absorbed dose considering all heterogeneities compared to the dose calculated in water. The patient artery was segmented as water (lumen), fibrotic plaque (around the lumen), calcified plaque (behind the fibrotic plaque), smooth muscle (tunica media) and cobalt-alloy (stents). The source position was assumed to be at the origin of the image, where the OCT imaging device was placed. The guidewire positions were assumed to be at the exact locations used during imaging. Simulations were performed on the Digital Research Alliance of Canada Cedar computing cluster with 200 million decay events to yield less than 1% uncertainty on absorbed dose in the target volume, 2 mm from the source center. The absorbed dose was scored in rectangular voxels of 0.1 × 0.1 × 1.0 mm3 along a 42 mm length, which includes the stents, source train and an additional 2 mm margin. The prescribed dose was 23 Gy to the target volume. The dose homogeneity index, the maximum to minimum dose ratio in the target volume, was calculated in both water and patient cases. Results The dose difference between the water and patient-specific cases was up to 56.2%, 55.8%, and 64.6% in the target volume with one, two, and three guidewires, respectively. The mean dose at the target volume was reduced by 3.4% and an additional 4.1% when adding the second and third guidewire, respectively. The dose homogeneity index was 1.29 in water and 2.96, 2.94, and 3.33 for the respective patient-specific cases. Each guidewire added a cold spot around the IVBT source at the target volume. Conclusions The dose at the target volume in IVBT is significantly reduced when three guidewires are present. Limiting the number of guidewires present during irradiation would reduce cold spots and dose inhomogeneity at the target volume.

Purpose/Objective(s ): Serous endometrial carcinoma (SEC) is a high-risk histological subtype of endometrial neoplasia. The effectiveness of a variety of adjuvant therapies has previously been investigated in the treatment of such tumors, namely chemotherapy (CT), external beam radiotherapy (EBRT), and sequential chemotherapy and radiotherapy (CRT). However, optimal management of early-stage SEC still remains unclarified. In this study, we retrospectively evaluated the clinical outcomes, toxicities, and recurrence patterns of patients who underwent adjuvant treatment for early-stage SEC. Materials/Method s: We interrogated our institutional pathology database in order to retrospectively identify all cases of early-stage SEC (stage I-II; FIGO 2009) treated from 2002 to 2019. Demographic data, pathological characteristics, adjuvant treatments, recurrence patterns, survival status as well as toxicity data were documented until September 2023. Overall Survival (OS) and Disease-Free Survival (DFS) were computed using Kaplan-Meier estimates and Cox's Proportional Hazard model. Descriptive statistical analysis was used to report other data. Result s: 50 patients were identified. All of them underwent TAH+BSO and omentectomy, displaying mostly stage IA (60%), followed by IB (24%) and II (16%) disease. Median follow-up was 90.9 months (CRT group = 97.6 months, CT group = 28.3 months, RT group = 141.9 months). Most patients underwent adjuvant CRT (n = 36, 72%), followed by CT (n = 6, 12%), RT (n = 6, 12%) and observation (n = 2; excluded from analysis). 3-year OS and DFS were, respectively, 91% and 83% for CRT, 33% and 50% for CT, and 67% and 80% for RT. CRT had significantly better OS (HR 0.14, 95% CI = 0.04-0.52, p<0.005) and DFS (HR 0.25, 95% CI = 0.07-0.97, p = 0.05) than CT alone. There were no significant OS or DFS benefits for RT when compared to CT or CRT. Recurrences were mostly distant (9 events; 8 CRT, 1 CT), followed by synchronous locoregional and distant relapse (3 events; 2 RT, 1 CRT). Locoregional recurrences were also observed (2 events; CT). Acute G3-4 toxicities were primarily hematologic (n = 12, 8 CRT, 4 CT), followed by gastrointestinal (n = 2, CRT) and genitourinary (n = 1, CT). Late G3-4 toxicities were, similarly, chiefly hematologic (n = 2, CRT) and genitourinary (n = 1, CT). Conclusio n: Our data underlines the challenge of effectively treating early-stage SEC, as overall disease recurrence remains high despite adjuvant treatment. CRT appears to be superior to CT alone, but fails to demonstrate benefits when compared to RT. Considering that most recurrences were distant in nature, these results also highlight the necessity of developing better systemic therapeutic options.

BackgroundCoronary artery disease is the most common form of cardiovascular disease. It is caused by excess plaque along the arterial wall, blocking blood flow to the heart (stenosis). A percutaneous coronary intervention widens the arterial wall with the inflation of a balloon inside the lesion area and leaves behind a metal stent to prevent re-narrowing of the artery (restenosis). However, in-stent restenosis may occur due to damage to the arterial wall tissue, triggering neointimal hyperplasia, producing fibrotic and calcified plaques and narrowing the artery again. Drug-eluting stents, which slowly release medication to inhibit neointimal hyperplasia, are used to prevent in-stent restenosis but fail up to 20% of cases. Coronary intravascular brachytherapy (IVBT), which uses beta$\beta$-emitting radionuclides to prevent in-stent restenosis, is used in these failed cases to prevent in-stent restenosis. However, current clinical dosimetry for IVBT is water-based, and heterogeneities such as the guidewire of the IVBT device, fibrotic and calcified plaques and stents are not considered.PurposeThis study aimed to develop a Monte Carlo-based dose calculation software, accounting for patient-specific geometry from Optical Coherence Tomography (OCT) images.MethodsRapidBrachyIVBT, a Monte Carlo dose calculation software based on the Geant4 toolkit v. 10.02.p02, was developed and integrated into RapidBrachyMCTPS, a treatment planning system for brachytherapy applications. The only commercially available IVBT delivery system, the Novoste Beta-Cath 3.5F, with a 90Sr90Y$<^>{90}{\rm Sr}<^>{90}{\rm Y}$ source train, was modeled with 30, 40, and 60 mm source train lengths. The software was validated with published TG-149 parameters compared to Monte Carlo simulations in water. The dose calculation engine was tested with OCT images from a patient undergoing coronary IVBT for recurrent in-stent restenosis at Brigham and Women's Hospital in Boston, Massachusetts. Considering the heterogeneities, the images were segmented and used to calculate the absorbed dose to water and the absorbed dose to medium. The prescribed dose was normalized to 23 Gy at 2.0 mm from the source center, which is the target volume in IVBT.ResultsThe dose rate values in water obtained using RapidBrachyIVBT aligned with TG-149 consensus values, showing agreement within a range of 0.03% to 1.7%. Considering the heterogeneities present in the patient's OCT images, the absorbed dose in the entire artery segment was up to 77.5% lower, while within the target volume, it was up to 56.6% lower, compared to the dose calculated in a homogeneous water phantom.ConclusionRapidBrachyIVBT, a Monte Carlo dose calculation software for IVBT, was developed and successfully integrated into RapidBrachyMCTPS, a treatment planning system for brachytherapy applications, where accurate attenuation of the absorbed dose by heterogeneities is considered.