1. Radiotherapy Plan Quality Assurance in NRG Oncology Trials for Brain and Head/Neck Cancers: An AI-Enhanced Knowledge-Based Approach.
- Author
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Wang, Du, Geng, Huaizhi, Gondi, Vinai, Lee, Nancy Y., Tsien, Christina I., Xia, Ping, Chenevert, Thomas L., Michalski, Jeff M., Gilbert, Mark R., Le, Quynh-Thu, Omuro, Antonio M., Men, Kuo, Aldape, Kenneth D., Cao, Yue, Srinivasan, Ashok, Barani, Igor J., Sachdev, Sean, Huang, Jiayi, Choi, Serah, and Shi, Wenyin
- Subjects
GLIOMAS ,RADIOTHERAPY ,RESEARCH funding ,HEAD & neck cancer ,ARTIFICIAL intelligence ,DESCRIPTIVE statistics ,KNOWLEDGE base ,QUALITY assurance - Abstract
Simple Summary: Radiation therapy (RT) plans deviating from the standard could likely compromise the efficacy of a pre-specified intervention for any clinical trial due either to insufficient coverage of the target area and/or excessive radiation doses to healthy tissues. Knowledge-based machine learning tools utilize high-quality data and generate patient-specific optimization objectives that produce RT plans that comply better with treatment protocol specifications. In this study, we investigated the use of a knowledge-based planning (KBP) model to evaluate the quality of RT plans in two clinical trials, one for glioblastoma and the other for head and neck cancer. The outcomes of this research indicate that this tool can assist RT quality assessments in multi-center clinical trials. The quality of radiation therapy (RT) treatment plans directly affects the outcomes of clinical trials. KBP solutions have been utilized in RT plan quality assurance (QA). In this study, we evaluated the quality of RT plans for brain and head/neck cancers enrolled in multi-institutional clinical trials utilizing a KBP approach. The evaluation was conducted on 203 glioblastoma (GBM) patients enrolled in NRG-BN001 and 70 nasopharyngeal carcinoma (NPC) patients enrolled in NRG-HN001. For each trial, fifty high-quality photon plans were utilized to build a KBP photon model. A KBP proton model was generated using intensity-modulated proton therapy (IMPT) plans generated on 50 patients originally treated with photon RT. These models were then applied to generate KBP plans for the remaining patients, which were compared against the submitted plans for quality evaluation, including in terms of protocol compliance, target coverage, and organ-at-risk (OAR) doses. RT plans generated by the KBP models were demonstrated to have superior quality compared to the submitted plans. KBP IMPT plans can decrease the variation of proton plan quality and could possibly be used as a tool for developing improved plans in the future. Additionally, the KBP tool proved to be an effective instrument for RT plan QA in multi-center clinical trials. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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