Assessing the feasibility of adaptive planning for prostate radiotherapy using Smartadapt deformable image registration. (February 2019) - Marin Anaya, Virginia; Fairfoul, Jamie
Highlights: A method for geometric and dosimetric analysis of SmartAdapt is proposed. Geometric results for deformable registration are worse than for rigid registration. SmartAdapt tends to under-contour the prostate and rectum. The deformed prostate tends to overestimate the need for re-planning. The deformed rectum tends to underestimate the need for re-planning. Abstract: Background: The purpose of this study is to assess the feasibility of adaptive planning for prostate cancer using SmartAdapt deformable image registration (DIR), in an effort to reduce the effect of patient-specific variations. Methods: 18 prostate patients (74 Gy in 37 fractions) were selected. Each patient had a planning CT and cone-beam CT (CBCT) images acquired at different fractions. For each fraction, the planning CT was registered to the CBCT image dataset using SmartAdapt. A rigid registration was performed prior to the DIR. The manual contours on the CBCT images by the clinician were used as reference. For the geometric analysis, various evaluation metrics were used to compare the volumes for both rigid and DIR. For the dosimetric analysis, the initial treatment plan was recalculated on the smartadapted structures, using Eclipse. Several Dose-Volume Histogram (DVH) points were used for the evaluation. Results: The results of the geometric analysis indicate that DIR can result in worse evaluation metrics than rigid registration alone. In general, SmartAdapt tends to under-contour the volumes. The difference in DVH points between the deformed and the reference prostate was worse than the difference between the planning CT and the reference, overestimating the need for re-planning. However, there was a tendency for the deformed rectum to underestimate the need for re-planning. Conclusions: After cautious analysis of the results, it has been decided not to implement SmartAdapt clinically to trigger adaptive decisions