Three‐dimensional quantitative evaluation method of nonrigid registration algorithms for adaptive radiotherapy

Abstract

Purpose: Current radiotherapy is progressing to the concept of adaptive radiotherapy, which implies the adaptation of planning along the treatment course. Nonrigid registration is an essential image processing tool for adaptive radiotherapy and image guided radiotherapy, and the threedimensional (3D) nature of the current radiotherapy techniques requires a 3D quantification of the registration error that existing evaluation methods do not cover appropriately. The authors present a method for 3D evaluation of nonrigid registration algorithms' performance, based on organ delineations, capable of working with near-spherical volumes even in the presence of concavities. Methods: The evaluation method is composed by a volume shape description stage, developed using a new ad hoc volume reconstruction algorithm proposed by the authors, and an error quantification stage. The evaluation method is applied to the organ delineations of prostate and seminal vesicles, obtained by an automatic segmentation method over images of prostate cancer patients treated with intensity modulated radiation therapy. Results: The volume reconstruction algorithm proposed has been shown to accurately model complex 3D surfaces by the definition of clusters of control points. The quantification method, inspired by the Haussdorf-Chebysev distance, provides a measure of the largest registration error per control direction, defining a valid metric for concave-convex volumes. Summarizing, the proposed evaluation methodology presents accurate results with a high spatial resolution in a negligible computation time in comparison with the nonrigid registration time. Conclusions: Experimental results show that the metric selected for quantifying the registration error is of utmost importance in a quantitative evaluation based on measuring distances between volumes. The accuracy of the volume reconstruction algorithm is not so relevant as long as the reconstruction is tight enough on the actual volume of the organ. The new evaluation method provides a smooth and accurate volume reconstruction for both the reference and the registered organ, and a complete 3D description of nonrigid registration algorithms' performance, resulting in a useful tool for study and comparison of registration algorithms for adaptive radiotherapy.

Performance of commercially available deformable image registration platforms for contour propagation using patient‐based computational phantoms: A multi‐institutional study

“…In this scenario, characterized by low image contrast, the regularization term of the algorithms failed to preserve the anatomy of the ROIs adjacent to the bladder, extending the deformation well beyond its support. Accuracy values proximal to the more reliable situation depicted by DVF1 have been found in mono‐institutional studies on self‐made software …”

“…In recent years, DIR has been extensively implemented in multiple RT applications: contour propagation, dose summation in IGART, [33][34][35][36] organ motion modeling on 4D scans 26,27,37 and multimodal image registration. 38,39 Although many commercial platforms are available, there is a lack of solid methods to provide DIR QA, resulting in fuzzy knowledge concerning the accuracy and reproducibility of these systems in typical clinical settings.…”

“…Accuracy values proximal to the more reliable situation depicted by DVF1 have been found in mono-institutional studies on self-made software. [35][36][37]…”

Methodology for registration of distended rectums in pelvic CT studies

“…(4) Previous works have indicated that a DSC > 0.7 shows a satisfactory overlapping between two volumes 5, 23, 24 and the same value was used in the case of OVI. 14 Furthermore, the evaluation method previously proposed by the authors 25 is applied to the contours of the prostate to determine the influence of a better registration of the rectum in the automatic delineation of the prostate. This methodology allows the representation of the spatial distribution of the error around the reference prostate, showing the delineation variability with respect to the relative position on the prostate.…”

“…This methodology allows the representation of the spatial distribution of the error around the reference prostate, showing the delineation variability with respect to the relative position on the prostate. 5,25…”