A framework for automated contour quality assurance in radiation therapy including adaptive techniques

• Published in: Physics in medicine & biology Vol. 60; no. 13; pp. 5199 - 5209
• Main Authors: Altman, M B, Kavanaugh, J A, Wooten, H O, Green, O L, DeWees, T A, Gay, H, Thorstad, W L, Li, H, Mutic, S
• Format: Journal Article
• Language: English
• Published: England IOP Publishing 07.07.2015
• Subjects: adaptive radiation therapy; Aged; Automation; contouring; Female; Head and Neck Neoplasms - radiotherapy; Humans; Male; Middle Aged; Models, Theoretical; Organs at Risk - radiation effects; Pilot Projects; quality assurance; Quality Assurance, Health Care - standards; Radiotherapy Planning, Computer-Assisted - methods; Radiotherapy, Computer-Assisted; treatment planning
• ISSN: 0031-9155; 1361-6560
• DOI: 10.1088/0031-9155/60/13/5199

Contouring of targets and normal tissues is one of the largest sources of variability in radiation therapy treatment plans. Contours thus require a time intensive and error-prone quality assurance (QA) evaluation, limitations which also impair the facilitation of adaptive radiotherapy (ART). Here, an automated system for contour QA is developed using historical data (the 'knowledge base'). A pilot study was performed with a knowledge base derived from 9 contours each from 29 head-and-neck treatment plans. Size, shape, relative position, and other clinically-relevant metrics and heuristically derived rules are determined. Metrics are extracted from input patient data and compared against rules determined from the knowledge base; a computer-learning component allows metrics to evolve with more input data, including patient specific data for ART. Nine additional plans containing 42 unique contouring errors were analyzed. 40/42 errors were detected as were 9 false positives. The results of this study imply knowledge-based contour QA could potentially enhance the safety and effectiveness of RT treatment plans as well as increase the efficiency of the treatment planning process, reducing labor and the cost of therapy for patients.