Program Information
Contour Quality Assurance and Decision Support: Implications, Issues, and the State-Of-The-Art
J Kavanaugh1*, T Purdie2*, K Brock3*, (1) Washington University in St. Louis, St. Louis, MO, (2) The Princess Margaret Cancer Centre - UHN, Toronto, ON, (3) UT MD Anderson Cancer Center, Houston, TX
Presentations
8:30 AM : Dosimetric impact of contouring variability in Intensity Modulated Radiation Therapy - J Kavanaugh, Presenting Author8:50 AM : Contour Assessment for Quality Assurance and Data Mining - T Purdie, Presenting Author
9:10 AM : Advances and Challenges in Contour QA for Adaptive RT - K Brock, Presenting Author
TH-B-FS2-0 (Thursday, August 3, 2017) 8:30 AM - 9:30 AM Room: Four Seasons 2
The delineation (“contouring”) of target and normal healthy tissue structures in imaging data is an important part of the radiation therapy treatment planning process and a pivotal component of high quality patient care. Many manual, semi-automatic, and automatic approaches for contouring have been developed, but all of these are still prone to contouring errors. Errors from poorly drawn and/or incorrect contours can yield sub-optimal treatment plans which can result in mistreatments, both in terms of under-treatment of missed targets (potentially resulting in failed treatments and/or recurrences) and over-treatment of critical structures (resulting in radiation-induced sequelae). Due to the need to address these errors, the subsequent step of contouring review, including both quality assurance (QA) and decision support, is no less crucial to producing high quality treatment plans. Contour QA has become more pivotal in the age of intensity modulated radiation therapy (IMRT), knowledge-based treatment planning (KBP), and adaptive radiation therapy (ART) as well as the increased interest in the use of evidence-based medicine to enhance the quality and efficacy of radiation therapy through clinical trials. In IMRT planning, contouring errors can result in poorly optimized plans for individual patients, while for KBP approaches, errors in contouring can impact the entire models resulting in in sub-optimal plans for a large group of patients. In on-line ART, manual contour assessment and decision support is a major limitation to establishing an efficient clinical workflow. For evidence-based medicine trials, errors in contouring can result in inaccurate and/or inconsistent results, reducing the positive impact of the trials themselves. This symposium will discuss many aspects related to contour QA. First, the impact of contouring errors on plan quality for IMRT-based plans (including those derived by KBP techniques) will be elucidated to frame the importance of contour QA. Then, the current state-of-the-art (including automated and semi-automated approaches), limitations, and future directions of contour assessment, including those based in data mining, will be discussed. Finally contour QA issues related to the developing field of ART, for which on-line approaches require a high degree of efficiency in all parts of the treatment planning workflow will be described.
Learning Objectives:
1. Understand dosimetric implications of contouring errors and variability in Intensity Modulated Radiation Therapy (IMRT)
2. Understand the state-of-the-art in contour assessment for quality assurance including data mining-based techniques
3. Learn about specific advances and challenges in contour QA which relate to adaptive radiation therapy (ART)
Handouts
- 127-35510-418554-127661.pdf (J Kavanaugh)
- 127-35511-418554-126840.pdf (T Purdie)
- 127-35512-418554-126100.pdf (K Brock)
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