Image Processing Pitfalls in Vendor Adaptive Radiotherapy Software with Tomotherapy-like Systems: Feedback from Clinical Case Reports

Abstract

Background: Adaptive radiotherapy (ART) has the potential to reduce the toxicities of radiotherapy and improve overall survival by considering variations in the patient's anatomy during the course of treatment. ART's first commercial solutions are now implemented in clinical radiotherapy departments. However, before they can be used safely with real patients, these solutions must be rigorously evaluated to precisely determine the limits of their use. Methods: In this paper, we evaluated an offline ART vendor system in 50 patients treated on tomotherapy- like systems for six months. Illustrated by numerous examples of head and neck, thoracic and abdominopelvic localizations, two limitations of image processing used in the ART workflow have been highlighted: deformable image registration (DIR) accuracy and the way the limited field of view (FOV) is compensated. This feedback from clinical experience makes it possible to identify topics of image processing research with strong clinical interest. Results: Current DIR method accuracy may be too weak for some clinical ART applications, and their improvement remains highly important, especially for multimodality registration. Improvements in contour propagation methods also remain crucial today. We showed that there is a need for the development of automatic DIR accuracy quantification methods to help streamline the ART process. Finally, the limited FOV of the onboard images may induce dose calculation errors, highlighting the need to develop new FOV extension methods. Conclusion: We have evaluated a vendor ART system, but some image processing pitfalls, such as DIR accuracy and the limited FOV of the onboard images, make its implementation into clinical practice difficult for the moment.