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Modeling dosimetric benefits from daily adaptive RT for gynecological cancer patients with and without knowledge-based dose prediction.
J Appl Clin Med Phys
January 2025
Department of Radiation Medicine and Applied Sciences, UC San Diego Health, La Jolla, California, USA.
Purpose: Daily online adaptive radiotherapy (ART) improves dose metrics for gynecological cancer patients, but the on-treatment process is resource-intensive requiring longer appointments and additional time from the entire adaptive team. To optimize resource allocation, we propose a model to identify high-priority patients.
Methods: For 49 retrospective cervical and endometrial cancer patients, we calculated two initial plans: the treated standard-of-care (Initial) and a reduced margin initial plan (Initial) for adapting with the Ethos treatment planning system.
Multi-institutional Knowledge-Based (KB) plan prediction benchmark models for whole breast irradiation.
Phys Med
January 2025
Medical Physics Dept IRCCS San Raffaele Scientific Institution Milano Italy.
Purpose: To train and validate KB prediction models by merging a large multi-institutional cohort of whole breast irradiation (WBI) plans using tangential fields.
Methods: Ten institutions (INST1-INST10, 1481 patients) developed their KB-institutional models for left/right WBI (ten models for right and eight models for left). The transferability of models among centers was assessed based on the overlap of the geometric Principal Component (PC1) of each model when applied to other institutions and/or on the presence of significantly different optimization policies.
Can knowledge-based planning models validated on ethnically diverse patients lead to global standardisation of external beam radiation therapy for locally advanced cervix cancer?
Radiother Oncol
December 2024
Department of Radiation Oncology, Advanced Centre for Treatment, Research and Education in Cancer, Tata Memorial Centre, Homi Bhabha National Institute, Kharghar, Navi Mumbai, Maharashtra, India. Electronic address:
Background And Purpose: Knowledge-based planning (KBP) can consistently and efficiently create high-quality Volumetric Arc Therapy (VMAT) plans for cervix cancer. This study describes the cross-validation of two KBP models on geographically distinct populations and their comparison to manual plans from 67 centers. The purpose was to determine the universal applicability of a generic KBP model.
View Article and Find Full Text PDFValidating knowledge-based volumetric modulated arc therapy plans with a multi-institution model (broad model) using a complete open-loop dataset for prostate cancer.
Phys Eng Sci Med
December 2024
Department of Medical Physics, Graduate School of Medical Sciences, Kindai University, 377-2 Onohigashi, Osakasayama-shi, Osaka, 589-8511, Japan.
This study examined the characteristics of the broad model (KBP) through a complete open-loop evaluation of volumetric modulated arc therapy (VMAT) plans for prostate cancer in 30 patients at two institutions. KBP, trained using 561 prostate cancer VMAT plans from five institutions with different treatment protocols, was shared with two institutions. The institutions were not involved in the creation of KBP.
View Article and Find Full Text PDFSynthesizing Efficiency Tools in Radiotherapy to Increase Patient Flow: A Comprehensive Literature Review.
Clin Med Insights Oncol
December 2024
Division of Radiation Oncology, Department of Radiation Sciences, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
The promise of novel technologies to increase access to radiotherapy in low- and middle-income countries (LMICs) is crucial, given that the cost of equipping new radiotherapy centres or upgrading existing machinery remains a major obstacle to expanding access to cancer treatment. The study aims to provide a thorough analysis overview of how technological advancement may revolutionize radiotherapy (RT) to improve level of care provided to cancer patients. A comprehensive literature review following some steps of systematic review (SLR) was performed using the Web of Science (WoS), PubMed, and Scopus databases.
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