Search

Background: The appropriate utilization of Breast MRI in breast cancer care remains controversial. As part of a quality improvement initiative for breast cancer screening and treatment, we sent out a survey to physicians who treat breast cancer patients. All respondents are participants in the ATHENA initiative, a program which unites physicians, researchers, and patients at the five University of California medical centers. Objective: To use the ATHENA infrastructure to perform a qualitative analysis of variations in breast cancer care. Methods: Surveys were sent to 50 physicians in the ATHENA network whose practices are focused on breast cancer. Respondents were presented with clinical scenarios, and asked whether they would recommend MRI always/usually or sometimes/never. Differences were compared by Chi square. Results: 39 physicians completed the survey (78% response rate). Of these physicians 29% were surgeons, 26% radiation oncologists and 45% medical oncologists. Athena physicians were more likely to order MRI for high risk screening of mutation carriers than not (85% yes vs. 15% no, p < 0.003) but not based on breast density alone or previous history of breast cancer. They were also more likely to order it for monitoring neo-adjuvant chemotherapy (70% yes vs. 30% no, p < 0.03). Although the majority answered that they would order a Breast MRI for new breast cancer the difference between responses was not significantly different (56% yes vs. 44%, p = 0.07). Conclusion: Athena physicians follow established published guidelines which demonstrate a benefit for Breast MRI screening for BRCA mutation carriers but not based on density or previous history of breast cancer. The Athena network allows a forum for new practice guidelines to be implemented as data becomes available to improve patient outcomes and utilize the best evidence for patient care, where both the patterns of MRI use as well as the outcomes of practice patterns will be evaluated prospectively. [ABSTRACT FROM AUTHOR]

NRG Oncology's Developmental Therapeutics and Radiation Therapy Subcommittee assembled an interdisciplinary group of investigators to address barriers to successful early phase clinical trials of novel combination therapies involving radiation. This Policy Review elucidates some of the many challenges associated with study design for early phase trials combining radiotherapy with novel systemic agents, which are distinct from drug-drug combination development and are often overlooked. We also advocate for potential solutions that could mitigate or eliminate some of these barriers, providing examples of specific clinical trial designs that could help facilitate efficient and effective evaluation of novel drug-radiotherapy combinations., Competing Interests: Declaration of interests JMB received grants or contracts from the National Institutes of Health (NIH); royalties or licences from UpToDate; and has a leadership or fiduciary role in other board, society, committee, or advocacy group (paid or unpaid) for the American Society for Radiation Oncology (ASTRO) and is on the Board of Directors as Science Council Chair. SEF reports ongoing research with Novartis and Bayer; received consulting fees from Lantheas, Progenics, Blue Earth, Bayer, Astellas, Pfizer, and Jaansen; payment or honoraria as a speaker for Lantheas, Progenics, Blue Earth, Bayer, Astellas, Pfizer, and Jaansen; participates on an advisory board at Lantheas, Progenics, Blue Earth, Bayer, Astellas, Pfizer, and Jaansen; and has a leadership or fiduciary role in other board, society, committee, or advocacy group, paid or unpaid on the board of chancellors at the American College of Radiology. SKJ received grants or contracts from the National Cancer Institute, Merck, Beigene, Guardant, and Adlai made to their institution; consulting fees from Merck, AstraZeneca, Beigene, Radialogica, Syntactx, and IMX; payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from ASTRO; is a senior editor at the International Journal of Radiation Biology Physics; received payment for expert testimony from Dechert; support for attending meetings and travel from ASTRO, AstraZeneca, and Merck; and participation on a data safety monitoring board for Advarra. RJK declares ongoing committee role at ASTRO and ongoing senior editor role at International Journal of Radiation Oncology Biology Physics; received grants or contracts from NIH and Bridge Bio to their institution; received consulting fees from HunaTek and Guidepoint Global; has patents planned, issued, or pending with University of Wisconsin; and has leadership or fiduciary role in other board, society, committee, or advocacy group, unpaid with ASTRO. SHL received grants from Beyond Spring, STCube Pharmaceuticals, and Nektar Therapeutics; consulting fees from XRAD Therapeutics; support for attending meetings and travel from AstraZeneca; participated on an advisory board for AstraZeneca and Creatv Microtech; and has stock or stock options from Seek Diagnostics. AMM received consulting fees from AstraZeneca, Merck, Varian Medical Systems, Kortuc, and Siemens; payment for expert testimony from Arizona Legal Group; support for attending meetings and travel from NRG Oncology; and has a leadership or fiduciary role in other board, society, committee, or advocacy group, paid or unpaid at American Brachytherapy Society. JM declares in the last 36 months grants or contracts from NIH, Merck, BMS, Genentech, Incyte, Trisalus, Transgene, and EMD Serono; consulting fees from GLG and Guidepoint; payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from the Association of Northern California Oncologists; participation on a data safety monitoring board or advisory board at Multiplex Thera; and stock or stock options from Multiplex Thera. SPP received grants or contracts from Amgen, AstraZeneca, MedImmune, A2bio, Bristol Myers Squibb, Eli Lilly, Fate Therapeutics, Gilead, Iovance, Merck, Pfizer, and Roche Genentech; and consulting fees from Amgen, AstraZeneca, BeiGene, Bristol Myers Squibb, Certis, Eli Lilly, Jazz, Genentech, Illumina, Merck, Pfizer, Signatera, and Tempus. SS received grants or contracts from Merck, Regeneron, Exelixis, and Innovio; payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from Exelixis and Medscape; and participated on a data safety monitoring board or advisory board at Luminos, Eisai, and Naveris. MX-W received grants or contracts from NCI; consulting fees from Eli Lilly and Novocure; and participated on a data safety monitoring board or advisory board for Eli Lilly. ZSZ has a leadership or fiduciary role in other board, society, committee, or advocacy group, paid or unpaid at the American Board of Radiology. KRP and PAT-S are employed by the NIH. TMW declares no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)

Background: 3D neural network dose predictions are useful for automating brachytherapy (BT) treatment planning for cervical cancer. Cervical BT can be delivered with numerous applicators, which necessitates developing models that generalize to multiple applicator types. The variability and scarcity of data for any given applicator type poses challenges for deep learning., Purpose: The goal of this work was to compare three methods of neural network training-a single model trained on all applicator data, fine-tuning the combined model to each applicator, and individual (IDV) applicator models-to determine the optimal method for dose prediction., Methods: Models were produced for four applicator types-tandem-and-ovoid (T&O), T&O with 1-7 needles (T&ON), tandem-and-ring (T&R) and T&R with 1-4 needles (T&RN). First, the combined model was trained on 859 treatment plans from 266 cervical cancer patients treated from 2010 onwards. The train/validation/test split was 70%/16%/14%, with approximately 49%/10%/19%/22% T&O/T&ON/T&R/T&RN in each dataset. Inputs included four channels for anatomical masks (high-risk clinical target volume [HRCTV], bladder, rectum, and sigmoid), a mask indicating dwell position locations, and applicator channels for each applicator component. Applicator channels were created by mapping the 3D dose for a single dwell position to each dwell position and summing over each applicator component with uniform dwell time weighting. A 3D Cascade U-Net, which consists of two U-Nets in sequence, and mean squared error loss function were used. The combined model was then fine-tuned to produce four applicator-specific models by freezing the first U-Net and encoding layers of the second and resuming training on applicator-specific data. Finally, four IDV models were trained using only data from each applicator type. Performance of these three model types was compared using the following metrics for the test set: mean error (ME, representing model bias) and mean absolute error (MAE) over all dose voxels and ME of clinical metrics (HRCTV D90% and D 2cc of bladder, rectum, and sigmoid), averaged over all patients. A positive ME indicates the clinical dose was higher than predicted. 3D global gamma analysis with the prescription dose as reference value was performed. Dice similarity coefficients (DSC) were computed for each isodose volume., Results: Fine-tuned and combined models showed better performance than IDV applicator training. Fine-tuning resulted in modest improvements in about half the metrics, compared to the combined model, while the remainder were mostly unchanged. Fine-tuned MAE = 3.98%/2.69%/5.36%/3.80% for T&O/T&R/T&ON/T&RN, and ME over all voxels = -0.08%/-0.89%/-0.59%/1.42%. ME D 2cc were bladder = -0.77%/1.00%/-0.66%/-1.53%, rectum = 1.11%/-0.22%/-0.29%/-3.37%, sigmoid = -0.47%/-0.06%/-2.37%/-1.40%, and ME D90 = 2.6%/-4.4%/4.8%/0.0%. Gamma pass rates (3%/3 mm) were 86%/91%/83%/89%. Mean DSCs were 0.92%/0.92%/0.88%/0.91% for isodoses ≤ 150% of prescription., Conclusions: 3D BT dose was accurately predicted for all applicator types, as indicated by the low MAE and MEs, high gamma scores and high DSCs. Training on all treatment data overcomes challenges with data scarcity in each applicator type, resulting in superior performance than can be achieved by training on IDV applicators alone. This could presumably be explained by the fact that the larger, more diverse dataset allows the neural network to learn underlying trends and characteristics in dose that are common to all treatment applicators. Accurate, applicator-specific dose predictions could enable automated, knowledge-based planning for any cervical brachytherapy treatment., (© 2024 American Association of Physicists in Medicine.)

Immunotherapeutic agents have revolutionized cancer treatment over the past decade. However, most patients fail to respond to immunotherapy alone. A growing body of preclinical studies highlights the potential for synergy between radiation therapy and immunotherapy, but the outcomes of clinical studies have been mixed. This review summarizes the current state of immunotherapy and radiation combination therapy across cancers, highlighting existing challenges and promising areas for future investigation., (Copyright © 2024 Elsevier Inc. All rights reserved.)

There are more than 13,000 new cases of cervical cancer each year in the United States and approximately 245,000 survivors. External beam radiation and brachytherapy are the front-line treatment modalities, and 60% of patients develop vaginal damage and constriction, i.e., stenosis of the vaginal vault, greatly impeding sexual function. The incidence of vaginal stenosis (VS) following radiotherapy (RT) for anorectal cancer is 80%. VS causes serious quality of life (QoL) and psychological issues, and while standard treatment using self-administered plastic dilators is effective, acceptance and compliance are often insufficient. Based on published patient preferences, we have pursued the design of a soft inflatable dilator for treating radiotherapy-induced vaginal stenosis (VS). The critical component of the novel device is the dilator balloon wall material, which must be compliant yet able to exert therapeutic lateral force levels. We selected a commercially available silicone elastomer and characterized its stress-strain characteristics and hyperelastic properties. These parameters were quantified using uniaxial tensile testing and digital image correlation (DIC). Dilator inflation versus internal pressure was modeled and experimentally validated in order to characterize design parameters, particularly the dilator wall thickness. Our data suggest that an inflatable silicone elastomer-based vaginal dilator warrants further development in the context of a commercially available, well-tolerated, and effective device for the graded, controlled clinical management of radiotherapy-induced VS.

Background: Concurrent chemoradiotherapy has been the standard of care for locally advanced cervical cancer for over 20 years; however, 30-40% of treated patients have recurrence or progression within 5 years. Immune checkpoint inhibition has improved outcomes for patients with PD-L1 positive metastatic or recurrent cervical cancer. We assessed the benefit of adding durvalumab, a PD-L1 antibody, with and following chemoradiotherapy for locally advanced cervical cancer., Methods: The CALLA randomised, double-blind, phase 3 trial included 105 hospitals across 15 countries. Patients aged at least 18 years with previously untreated locally advanced cervical cancer (adenocarcinoma, squamous, or adenosquamous; International Federation of Gynaecology and Obstetrics [FIGO] 2009 stage IB2-IIB lymph node positive, stage ≥III any lymph node status) and WHO or Eastern Cooperative Oncology Group performance status of 0 or 1 were randomly assigned (1:1) through an interactive web response system using a permuted block size of 4 to receive durvalumab (1500 mg intravenously once every 4 weeks) or placebo with and following chemoradiotherapy, for up to 24 cycles. Chemoradiotherapy included 45 Gy external beam radiotherapy at 5 fractions per week concurrent with intravenous cisplatin (40 mg/m 2 ) or carboplatin (area under the concentration-time curve 2) once weekly for 5 weeks, followed by image-guided brachytherapy (high-dose rate, 27·5-30 Gy or low-dose/pulse-dose rate, 35-40 Gy). Randomisation was stratified by disease stage status (FIGO stage and node status) and geographical region. Chemoradiotherapy quality was continuously reviewed. The primary endpoint was progression-free survival, assessed by the investigator using Response Evaluation Criteria in Solid Tumors, version 1.1, in the intention-to-treat population. Safety was assessed in patients who received at least one dose of study treatment. This study is registered with ClinicalTrials.gov, NCT03830866., Findings: Between Feb 15, 2019, and Dec 10, 2020, 770 women were randomly assigned (385 to durvalumab and 385 to placebo; median age 49 years [IQR 41-57]). Median follow-up was 18·5 months (IQR 13·2-21·5) in the durvalumab group and 18·4 months (13·2-23·7) in the placebo group. At data cutoff, median progression-free survival had not been reached (95% CI not reached-not reached) for either group (HR 0·84; 95% CI 0·65-1·08; p=0·17); 12-month progression-free survival was 76·0% (71·3-80·0) with durvalumab and 73·3% (68·4-77·5) with placebo. The most frequently reported grade 3-4 adverse events in both groups were anaemia (76 [20%] of 385 in the durvalumab group vs 56 [15%] of 384 in the placebo group) and decreased white blood cells (39 [10%] vs 49 [13%]). Serious adverse events occurred for 106 (28%) patients who received durvalumab and 89 (23%) patients who received placebo. There were five treatment-related deaths in the durvalumab group (one case each of urinary tract infection, blood loss anaemia, and pulmonary embolism related to chemoradiotherapy only; one case of endocrine disorder related to durvalumab only; and one case of sepsis related to both durvalumab and chemoradiotherapy). There was one treatment-related death in the placebo group (pneumonia related to chemoradiotherapy)., Interpretation: Durvalumab concurrent with chemoradiotherapy was well tolerated in participants with locally advanced cervical cancer, however it did not significantly improve progression-free survival in a biomarker unselected, all-comers population. Concurrent durvalumab plus chemoradiotherapy warrants further exploration in patients with high tumoral PD-L1 expression. Rigorous monitoring ensured high chemoradiotherapy compliance with advanced technology and allowed patients to receive optimal care., Funding: AstraZeneca., Competing Interests: Declaration of interests BJM reports institutional research funding from Novartis, Amgen, Genentech, Lilly, Janssen, Array BioPharma, Tesaro, Morphotek, Pfizer Advaxis, AstraZeneca, ImmunoGen, Regeneron, and Nucana. Honoraria from Agenus, Akeso Biopharma, Amgen, Aravive, AstraZeneca, Clovis Oncology, Eisai, Genmab/Seattle Genetics, ImmunoGen, Iovance Biotherapeutics, Merck, Mersana, Pfizer, Puma Biotechnology, Regeneron, Roche/Genentech, TESARO/GKS, Vascular Biogenics, GOG Foundation, Elevar Therapeutics, Novocure, Gradalis, Karyopharm Therapeutics, Bayer, EMD Merck, Macrogenics, Sorrento Therapeutics, US Oncology, and Myriad Pharmaceuticals; a leadership position for US Oncology; speakers’ bureau participation for Roche/Genentech, AstraZeneca, Clovis Oncology, Eisai, TESARO/GSK, and Merck; served in a consulting or advisory role for Agenus, Akeso Biopharma, Amgen, Aravive, AstraZeneca, Clovis Oncology, Eisai, Genmab/Seattle Genetics, GOG Foundation, ImmunoGen, Iovance Biotherapeutics, Merck, Mersana, Myriad Pharmaceuticals, Pfizer, Puma Biotechnology, Regeneron, Roche/Genentech, TESARO/GSK, Vascular Biogenics, Gradalis, Karyopharm Therapeutics, Sorrento Therapeutics, Novocure, Bayer, Elevar Therapeutics, EMD Merck, Gradalis, and US Oncology. TT reports personal fees from AstraZeneca, Chugai, JGOG, and Zeria, outside the submitted work. JCVL reports funding, provision of study material, medical writing, and processing charges for the present work and grants from AstraZeneca; consulting fees and honoraria from AstraZeneca and Bristol Myers Squibb outside the submitted work; travel support from AstraZeneca, Merck Sharp and Dohme, Novartis, and Pfizer; served as an advisor for AstraZeneca; grants for clinical research from AstraZeneca, Bristol Myers Squibb, Janssen, Merck Sharp and Dohme, Novartis, Roche, and Sanofi, outside the submitted work. RS-F received an institutional research grant from Merck Sharp and Dohme and served at an advisory board for Merck Sharp and Dohme; and received lecture honoraria from AstraZeneca, Bristol Myers Squibb, Medison, Merck Sharp and Dohme, Neopharm, Novartis, and Roche, outside the submitted work. UM reports institutional grants from Varian Medical Systems and was a RT Steering Committee member for CALLA study. MdPED reports institutional funding from AstraZeneca for the present work and served as an advisor for AstraZeneca, outside the submitted work. SL has received payment or honoraria for lectures, presentations, speakers’ bureaus, manuscript writing, or educational events and participated on a data safety monitoring board or advisory board for AstraZeneca, Bristol Myers Squibb Boehringer Ingelheim, Merck, Roche, and Novartis, and has a leadership or fiduciary role for Iylon Precision Oncology. FJRG reports support for the present work from AstraZeneca, grants from AstraZeneca, Janssen, Lilly Company, Merck Sharp and Dohme, Roche, and Sanofi; travel support from BioGentec, and an unpaid leadership role with the Comite de Etica e Investigacion del Hospital Civil de Guadalajara, outside the submitted work. NV reports personal research funding from AstraZeneca, Merck Sharp and Dohme, and Roche; Consulting fees or honoraria from Tecnofarma, MSD, and Roche; and is currently the Vice President of the Peruvian Mastology society, outside the submitted work. DA reports funding for this clinical trial was made to his institute from AstraZeneca; an institutional grant from Takeda Pharmaceutical; consulting fees from AbbVie; honoraria from AstraZeneca, AbbVie, MSD, Takeda Pharmaceutical, and Chugai; participated in an advisory board for Takeda Pharmaceutical, AstraZeneca, and MSD; and was the president of the Asian Society of Gynecologic Oncology, the Chairperson of the Japan Society of Gynecologic Oncology, and the Vice President of the Japan Gynecologic Oncology Group. ML reports grants for clinical research from AstraZeneca, Bristol Myers Squib, Merck Sharp and Dohme, and Roche; consulting fees, honoraria, and travel support from Roche, outside the submitted work. J-YL reports personal research funding from AstraZeneca and Merck Sharp and Dohme; institutional funding from Clovis Oncology, Immunogen, Janssen Oncology, Merck, Merck Sharp and Dohme, and Synthon; served an advisory role for AstraZeneca, Merck Sharp and Dohme, Roche, and Takeda. FR reports personal fees from AstraZeneca. YR reports subcontract funding from NIH SBIR grant R44CA254844, compensation from Medical Physics Journal Editorial as the Deputy Editor, and personal fees from AstraZeneca for case review. SW is an employee and shareholder at AstraZeneca and has patents at GlaxoSmithKline UK Ltd and AstraZeneca. AL and HD are employees and shareholders at AstraZeneca. ATN received medical writing support for this manuscript funded by AstraZeneca, is a shareholder and was an employee of AstraZeneca during this study; and is a current employee at Merck. JM reports honoraria and consulting fees from AstraZeneca, Varian Medical Systems, Merck, Primmune, Agenus Bio; grants from NRG Oncology; royalties from Springer Medical Books for published work; and support for attending meetings and travel from NRG Oncology. XW, RT, MM, QZ, COK, SV, RS, YK, W-FC, and GK have nothing to disclose., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Purpose: In select cases of locally advanced cervical cancer, a hybrid brachytherapy (HBT) approach consisting of a combined intracavitary (IC)/insterstitial (IS) implant can yield improved target coverage and/or decreased organ at risk dose compared to IC techniques while limiting invasiveness compared to IS techniques., Methods and Materials: The technique involves placement of transvaginal and/or perineal needles in addition to the tandem and ring/ovoids using either a specialized applicator or free-hand placement. Following applicator and needle placement, brachytherapy may then be planned using principles similar to IC or IS techniques. During treatment planning, it can be helpful to obtain both MRI and CT imaging, as plastic MRI-compatible needles do not show up well on MRI., Results: In patients where acceptable target coverage cannot be achieved using IC alone or doses to nearby OAR are too high, HBT should be evaluated. HBT can improve both dose to target and OAR while sparing patients the morbidity of perineal template-based interstitial brachytherapy. Specific scenarios where HBT may be preferred include bulky residual primary tumor especially with poor response to EBRT, extension into the lateral parametrium, vaginal extension of tumor, and an asymmetric target. Use of HBT can typically permit extension of dose coverage by an additional 1-2 cm beyond what can be achieved with an IC alone technique., Conclusion: HBT allows for improved therapeutic ratio by improving target volume coverage and/or lowering doses to OARs. Brachytherapists should be trained on the practical aspects of administering HBT to be able to offer a less invasive and impactful treatment option when appropriate., (Copyright © 2023 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.)

Background: Physician explanation of gynecologic brachytherapy can be overwhelming or induce patient anxiety, and may be time-constrained given clinical limitations. We report the first randomized trial of an educational video intervention in gynecologic brachytherapy on patient-reported outcomes., Methods: Between February 2020 and January 2022, 80 gynecologic cancer patients prescribed brachytherapy were randomly assigned to either standard informed consent (Arm A) or a supplemental 16 min brachytherapy educational video (https://vimeo.com/403385455/d0716e3cc8) via the internet (Arm B). Primary outcome was treatment-related distress (National Comprehensive Cancer Network (NCCN) distress scale scored 0 (no distress) to 10 (maximum distress)). Secondary outcome was patient satisfaction (summated Likert-scale scored 11-55). Surveys were administered at baseline, after first treatment, and prior to brachytherapy completion., Results: All patients completed the prescribed brachytherapy. In Arm B, 19/40 (48%) patients and 10/40 (25%) patients' family/friends viewed the video. For patients that completed all surveys (Arm A n=29, Arm B n=28), there was no difference between arms in the sociodemographic, clinical, or treatment variables. Distress scores were low at baseline (Arm A median 4, Arm B median 4, p=0.65) and there was no detectable change in distress between arms on surveys 1 and 2 (β 0.36, p=0.67) or surveys 1 and 3 (β -1.02, p=0.29) in multivariable analysis. Satisfaction scores were high at baseline (Arm A median 54, Arm B median 54.5, p=0.64) and there was no detectable change in satisfaction between arms on surveys 1 and 2 (β 0.22, p=0.93) or surveys 1 and 3 (β 0.63, p=0.85) in multivariable analysis., Conclusions: Among patients randomized to an educational video tool for gynecologic brachytherapy, approximately 50% of the cohort and 25% of the cohort's family/friends used the video. Overall, patients had low distress scores and high satisfaction scores with no significant differences between the standard and video intervention arms. Further work is needed to understand factors contributing to gynecologic brachytherapy anxiety., Trial Registration Number: NCT04363957., Competing Interests: Competing interests: DB received honorarium from Varian Medical Systems outside the submitted work. DR received honorarium from Vision RT and Radformation outside the submitted work. DS serves as a consultant for Merit Medical Inc and Varian Medical Systems outside the submitted work. JM serves as a consultant for Astra Zeneca, NRG Oncology, GOG Foundation, Varian Medical Systems, Primmune, Merck; serves as co-chair for NRG Oncology Cervix Co-Chair; serves as board member for GOG Foundation outside the submitted work. All remaining authors have declared no conflicts of interest., (© IGCS and ESGO 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective . Adaptive Radiotherapy (ART) is an emerging technique for treating cancer patients which facilitates higher delivery accuracy and has the potential to reduce toxicity. However, ART is also resource-intensive, Requiring extra human and machine time compared to standard treatment methods. In this analysis, we sought to predict the subset of node-negative cervical cancer patients with the greatest benefit from ART, so resources might be properly allocated to the highest-yield patients. Approach . CT images, initial plan data, and on-treatment Cone-Beam CT (CBCT) images for 20 retrospective cervical cancer patients were used to simulate doses from daily non-adaptive and adaptive techniques. We evaluated the coefficient of determination (R 2 ) between dose and volume metrics from initial treatment plans and the dosimetric benefits to theBowelV40Gy,BowelV45Gy,BladderDmean,andRectumDmeanfrom adaptive radiotherapy using reduced 3 mm or 5 mm CTV-to-PTV margins. The LASSO technique was used to identify the most predictive metrics forBowelV40Gy.The three highest performing metrics were used to build multivariate models with leave-one-out validation forBowelV40Gy. Main results . Patients with higher initial bowel doses were correlated with the largest decreases in BowelV40Gyfrom daily adaptation (linear best fit R 2 = 0.77 for a 3 mm PTV margin and R 2 = 0.8 for a 5 mm PTV margin). Other metrics had intermediate or no correlation. Selected covariates for the multivariate model were differences in the initialBowelV40GyandBladderDmeanusing standard versus reduced margins and the initial bladder volume. Leave-one-out validation had an R 2 of 0.66 between predicted and true adaptiveBowelV40Gybenefits for both margins. Significance . The resulting models could be used to prospectively triage cervical cancer patients on or off daily adaptation to optimally manage clinical resources. Additionally, this work presents a critical foundation for predicting benefits from daily adaptation that can be extended to other patient cohorts., (© 2023 IOP Publishing Ltd.)

Purpose: To estimate local control, survival, and toxicity associated with a 3-fraction (3F) image-guided brachytherapy (IGBT) regimen compared to longer fraction (LF) for cervical cancer., Methods: 150 patients treated between 2015-2020 with 3F (24Gy in 3 fractions) or LF (28...30 Gy in 4-5 fractions) were reviewed. The primary outcome was 2-year local failure. We compared overall survival (OS), disease-free survival (DFS), hospitalizations, and toxicity., Results: There were 32 patients in the 3F group and 118 in the LF group, with a median follow up of 22 months. The 3F had worse performance status (p = 0.01) but otherwise similar characteristics. The 2-year local failure rate was 3.6% (95% CI 0%, 10.6%) for 3F, and 7.5% (95% CI 2.4%, 12.6%) for LF. The univariable hazard ratio (HR) for local failure for 3F was 0.43 (0.05, 3.43; p = 0.43). Moreover, 2 of 32 (6.3%) 3F patients experienced Grade ...3 toxicity compared to 7 of 118 (5.9%) LF patients (p = 1.0), with no difference in hospitalization within 2 years (p = 0.66) and no treatment-related deaths., Conclusions: Local control was excellent, with long term survival and toxicity similar between the groups. These findings support consideration of 3F., (Copyright © 2023. Published by Elsevier Inc.)

Objective . To lay the foundation for automated knowledge-based brachytherapy treatment planning using 3D dose estimations, we describe an optimization framework to convert brachytherapy dose distributions directly into dwell times (DTs). Approach . A dose rate kernelḋ(r,θ,φ)was produced by exporting 3D dose for one dwell position from the treatment planning system and normalizing by DT. By translating and rotating this kernel to each dwell position, scaling by DT and summing over all dwell positions, dose was computed ( D calc ). We used a Python-coded COBYLA optimizer to iteratively determine the DTs that minimize the mean squared error between D calc and reference dose D ref , computed using voxels with D ref 80%-120% of prescription. As validation of the optimization, we showed that the optimizer replicates clinical plans when D ref = clinical dose in 40 patients treated with tandem-and-ovoid (T&O) or tandem-and-ring (T&R) and 0-3 needles. Then we demonstrated automated planning in 10 T&O using D ref = dose predicted from a convolutional neural network developed in past work. Validation and automated plans were compared to clinical plans using mean absolute differences (MAD=1N∑n=1Nabsxn-xn') over all voxels ( x n = Dose, N = #voxels) and DTs ( x n = DT, N = #dwell positions), mean differences (MD) in organ D 2cc and high-risk CTV D90 over all patients (where positive indicates higher clinical dose), and mean Dice similarity coefficients (DSC) for 100% isodose contours. Main results . Validation plans agreed well with clinical plans (MAD dose = 1.1%, MAD DT = 4 s or 0.8% of total plan time, D 2cc MD = -0.2% to 0.2% and D90 MD = -0.6%, DSC = 0.99). For automated plans, MAD dose = 6.5% and MAD DT = 10.3 s (2.1%). The slightly higher clinical metrics in automated plans ( D 2cc MD = -3.8% to 1.3% and D90 MD = -5.1%) were due to higher neural network dose predictions. The overall shape of the automated dose distributions were similar to clinical doses (DSC = 0.91). Significance . Automated planning with 3D dose predictions could provide significant time savings and standardize treatment planning across practitioners, regardless of experience., (© 2023 Institute of Physics and Engineering in Medicine.)

Brachytherapy is a critical component of the definitive management of cervical cancer and allows for the safe delivery of about half of the total effective radiation dose needed for optimal outcomes. Moreover, the dose distribution of brachytherapy is highly conformal, allowing for a therapeutic index currently unmatched by alternative techniques. However, a modern brachytherapy program requires special equipment, infrastructure, and procedural expertise. Unfortunately, multiple lines of evidence suggest that brachytherapy is currently underutilized in the United States. In this review, we examine the importance of brachytherapy, contemporary recommendations, and avenues for growth., (Published by Elsevier Inc.)

Purpose: Evaluate a cone-beam computed tomography (CBCT)-based daily adaptive platform in cervical cancer for multiple endpoints: (1) physics contouring accuracy of daily CTVs, (2) CTV coverage with adapted plans and reduced PTV margins versus non-adapted plans with standard-of-care (SOC) margins, (3) dosimetric improvements to CTV and organs-at-risk (OARs), and (4) on-couch time., Methods and Materials: Using a Varian Ethos™ emulator and KV-CBCT scans, we simulated the doses 15 retrospective cervical cancer patients would have received with/without online adaptation for five fractions. We compared contours and doses from SOC plans (5-15 mm CTV-to-PTV margins) to adapted plans (3 mm margins). Auto-segmented CTVs and OARs were reviewed and edited by trained physicists. Physics-edited targets were evaluated by an oncologist. Time spent reviewing and editing auto-segmented structures was recorded. Metrics from the CTV (D99%), bowel (V45Gy, V40Gy), bladder (D50%), and rectum (D50%) were compared., Results: The physician approved the physics-edited CTVs for 55/75 fractions; 16/75 required reductions, and 4/75 required CTV expansions. CTVs were encapsulated by unadapted, SOC PTVs for 56/75 (72%) fractions-representative of current clinical practice. CTVs were completely covered by adapted 3 mm PTVs for 71/75 (94.6%) fractions. CTV D99% values for adapted plans were comparable to non-adapted SOC plans (average difference of -0.9%), while all OAR metrics improved with adaptation. Specifically, bowel V45Gy and V40Gy decreased on average by 87.6 and 109.4 cc, while bladder and rectum D50% decreased by 37.7% and 35.8%, respectively. The time required for contouring and calculating an adaptive plan for 65/75 fractions was less than 20 min (range: 1-29 min)., Conclusions: Improved dose metrics with daily adaption could translate to reduced toxicity while maintaining tumor control. Training physicists to perform contouring edits could minimize the time physicians are required at adaptive sessions improving clinical efficiency. All emulated adaptive sessions were completed within 30 min however extra time will be required for patient setup, image acquisition, and treatment delivery., (© 2022 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine.)

Methods: This retrospective study evaluated patients who received three-fraction accelerated partial breast irradiation (APBI) via brachytherapy for breast cancer between January 2016 and April 2020. Inclusion criteria included age ≥18 years and early-stage unilateral breast cancer with negative lymph nodes. We evaluated acute toxicity (<6 weeks), late toxicity (≥6 weeks), and cosmetic outcomes. Frequencies of each variable were calculated. Cancer-specific outcomes were determined via the Kaplan-Meier method., Results: Thirty consecutive patients received three-fraction APBI of 2,250 cGy over 2 d. All cancers were stage T2 or less. Median time to last follow-up was 22 months. Local recurrence-free survival was 95.8% at 22 months. Seventeen (56.7%) patients reported an acute toxicity event. All were grade 1 except one patient with grade 2 (fatigue). No patient experienced ≥ grade 3 acute toxicity. One (3.3%) patient reported grade 3 late toxicity (tissue fibrosis). No patients had breast edema, fat necrosis, or non-healing wounds. There were no ≥ grade 3 cosmetic events., Discussion: Three-fraction APBI via brachytherapy was successful in preventing disease recurrence and death in this study, with still limited follow-up. Although acute and late toxicities or adverse cosmetic outcomes were seen, very few were grade 2 or higher and compare favorably to those reported in prior 10-fraction APBI studies., Conclusions: This study provides early single institutional evidence that three-fraction APBI may become a feasible treatment alternative., (Copyright © 2022 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.)

Radiomics has been applied to predict recurrence in several disease sites, but current approaches are typically restricted to analyzing tumor features, neglecting nontumor information in the rest of the body. The purpose of this work was to develop and validate a model incorporating nontumor radiomics, including whole-body features, to predict treatment outcomes in patients with previously untreated locoregionally advanced cervical cancer. Methods: We analyzed 127 cervical cancer patients treated definitively with chemoradiotherapy and intracavitary brachytherapy. All patients underwent pretreatment whole-body 18 F-FDG PET/CT. To quantify effects due to the tumor itself, the gross tumor volume (GTV) was directly contoured on the PET/CT image. Meanwhile, to quantify effects arising from the rest of the body, the planning target volume (PTV) was deformably registered from each planning CT to the PET/CT scan, and a semiautomated approach combining seed-growing and manual contour review generated whole-body muscle, bone, and fat segmentations on each PET/CT image. A total of 965 radiomic features were extracted for GTV, PTV, muscle, bone, and fat. Ninety-five patients were used to train a Cox model of disease recurrence including both radiomic and clinical features (age, stage, tumor grade, histology, and baseline complete blood cell counts), using bagging and split-sample-validation for feature reduction and model selection. To further avoid overfitting, the resulting models were tested for generalization on the remaining 32 patients, by calculating a risk score based on Cox regression and evaluating the c-index (c-index > 0.5 indicates predictive power). Results: Optimal performance was seen in a Cox model including 1 clinical biomarker (whether or not a tumor was stage III-IVA), 2 GTV radiomic biomarkers (PET gray-level size-zone matrix small area low gray level emphasis and zone entropy), 1 PTV radiomic biomarker (major axis length), and 1 whole-body radiomic biomarker (CT bone root mean square). In particular, stratification into high- and low-risk groups, based on the linear risk score from this Cox model, resulted in a hazard ratio of 0.019 (95% CI, 0.004, 0.082), an improvement over stratification based on clinical stage alone, which had a hazard ratio of 0.36 (95% CI, 0.16, 0.83). Conclusion: Incorporating nontumor radiomic biomarkers can improve the performance of prognostic models compared with using only clinical and tumor radiomic biomarkers. Future work should look to further test these models in larger, multiinstitutional cohorts., (© 2022 by the Society of Nuclear Medicine and Molecular Imaging.)

Purpose: The purpose of this work was to develop a knowledge-based dose prediction system using a convolution neural network (CNN) for cervical brachytherapy treatments with a tandem-and-ovoid applicator., Methods: A 3D U-NET CNN was utilized to make voxel-wise dose predictions based on organ-at-risk (OAR), high-risk clinical target volume (HRCTV), and possible source location geometry. The model comprised 395 previously treated cases: training (273), validation (61), test (61). To assess voxel prediction accuracy, we evaluated dose differences in all cohorts across the dose range of 20-130% of prescription, mean (SD) and standard deviation (σ), as well as isodose dice similarity coefficients for clinical and/or predicted dose distributions. We examined discrete Dose-Volume Histogram (DVH) metrics utilized for brachytherapy plan quality assessment (HRCTV D90%; bladder, rectum, and sigmoid D2cc) with ΔD x =D x,actual -D x,predicted mean, standard deviation, and Pearson correlation coefficient further quantifying model performance., Results: Ranges of voxel-wise dose difference accuracy (δD¯±σ) for 20-130% dose interval in training (test) sets ranged from [-0.5% ± 2.0% to +2.0% ± 14.0%] ([-0.1% ± 4.0% to +4.0% ± 26.0%]) in all voxels, [-1.7% ± 5.1% to -3.5% ± 12.8%] ([-2.9% ± 4.8% to -2.6% ± 18.9%]) in HRCTV, [-0.02% ± 2.40% to +3.2% ± 12.0%] ([-2.5% ± 3.6% to +0.8% ± 12.7%]) in bladder, [-0.7% ± 2.4% to +15.5% ± 11.0%] ([-0.9% ± 3.2% to +27.8% ± 11.6%]) in rectum, and [-0.7% ± 2.3% to +10.7% ± 15.0%] ([-0.4% ± 3.0% to +18.4% ± 11.4%]) in sigmoid. Isodose dice similarity coefficients ranged from [0.96,0.91] for training and [0.94,0.87] for test cohorts. Relative DVH metric prediction in the training (test) set were HRCTV ΔD¯ 90 ±σ ΔD  = -0.19 ± 0.55Gy (-0.09 ± 0.67 Gy), bladder ΔD¯ 2cc ±σ ΔD = -0.06 ± 0.54Gy (-0.17 ± 0.67 Gy), rectum ΔD¯ 2cc ±σ ΔD = -0.03 ± 0.36Gy (-0.04 ± 0.46 Gy), and sigmoid ΔD¯ 2cc ±σ ΔD = -0.01 ± 0.34Gy (0.00 ± 0.44 Gy)., Conclusions: A 3D knowledge-based dose predictions provide voxel-level and DVH metric estimates that could be used for treatment plan quality control and data-driven plan guidance., (Copyright © 2022 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.)