Radiotherapy delivery error detection with electronic portal imaging device (EPID)-based in vivo dosimetry

• Published in: Chinese medical journal Vol. 136; no. 8; pp. 998 - 1000
• Main Authors: Yang, Xueying, Geng, Lisheng, Huang, David, Li, Kaiwen, Zhuang, Hongqing, Cai, Jing, Yang, Ruijie
• Format: Journal Article
• Language: English
• Published: China Lippincott Williams & Wilkins Ovid Technologies 20.04.2023; Lippincott Williams & Wilkins; Wolters Kluwer
• Subjects: Algorithms; Classification; Correspondence; Dosimetry; Electronics; Error correction & detection; In Vivo Dosimetry; Investigations; Methods; Monte Carlo simulation; Neural networks; Phantoms, Imaging; Radiation therapy; Radiometry - methods; Radiotherapy Dosage; Radiotherapy, Intensity-Modulated - methods; Italy; Netherlands; United States > US; China
• ISSN: 0366-6999; 2542-5641
• DOI: 10.1097/CM9.0000000000002665

[...]there is no guarantee that the dose delivered to the patient is the same as planned, due to the patient's anatomical change, setup uncertainty, and organ motion during treatments. [...]in vivo dosimetry (IVD) has been recommended as part of routine IMRT to monitor the actual dose delivered to the patient, detect the source of errors, and assist in adaptive therapy. [...]a method that can quickly detect and classify the error source is highly desirable and needed. [...]it is difficult to obtain anatomical error data from actual treatment to set the "ground truth" to train and test ML/DL models. [...]the proposed ML/DL models in existing studies are based entirely on simulations, which have limited applicability to the real situation. [...]the error classification system based on ML/DL models can only identify those errors in relation to which they have been trained.