Performance validation of deformable image registration in the pelvic region

V Zambrano,H Furtado,D Georg,D Fabri,M Stock,J Gora,W Birkfellner,C Lutgendorf-Caucig,R Mayer

doi:10.1093/jrr/rrt045

Abstract

Patients undergoing radiotherapy will inevitably show anatomical changes during the course of treatment. These can be weight loss, tumour shrinkage, and organ motion or filling changes. For advanced and adaptive radiotherapy (ART) information about anatomical changes must be extracted from repeated images in order to be able to evaluate and manage these changes. Deformable image registration (DIR) is a tool that can be used to efficiently gather information about anatomical changes. The aim of the present study was to evaluate the performance of two DIR methods for automatic organ at risk (OAR) contour propagation. Datasets from ten gynaecological patients having repeated computed tomography (CT) and cone beam computed tomography (CBCT) scans were collected. Contours were delineated on the planning CT and on every repeated scan by an expert clinician. DIR using our in-house developed featurelet-based method and the iPlan® BrainLab treatment planning system software was performed with the planning CT as reference and a selection of repeated scans as the target dataset. The planning CT contours were deformed using the resulting deformation fields and compared to the manually defined contours. Dice's similarity coefficients (DSCs) were calculated for each fractional patient scan structure, comparing the volume overlap using DIR with that using rigid registration only. No significant improvement in volume overlap was found after DIR as compared with rigid registration, independent of which image modality or DIR method was used. DIR needs to be further improved in order to facilitate contour propagation in the pelvic region in ART approaches.

Highlights

The standard approach for treatment planning in conventional radiation therapy, intensity-modulated radiotherapy (IMRT) or particle beam therapy is based on a single ‘snapshot’ computed tomography (CT) as the basis for treatment planning
In this paper we evaluated the performance of our in-house-developed featurelet-based Deformable image registration (DIR) approach using clinical datasets from gynaecological patients, and we benchmarked this evaluation against the iPlan® BrainLab treatment planning system (TPS) DIR software
Results are shown as volume overlap percentage (DSC) before and after DIR (RR and DIR columns respectively) and Dice’s similarity coefficients (DSCs) improvement, which is the difference between the DIR and RR values

Summary

Introduction

The standard approach for treatment planning in conventional radiation therapy, intensity-modulated radiotherapy (IMRT) or particle beam therapy is based on a single ‘snapshot’ computed tomography (CT) as the basis for treatment planning. It is well known and documented that during the course of treatment the patient’s anatomy can change due to organ filling, tumour shrinkage, weight loss, etc. The management of organ motion and organ deformation has become a key aspect in advanced radiation therapy where steep dose gradients are applied, since such anatomical variations may lead to significant changes in the dose delivery to the tumour and to the surrounding healthy tissues with respect to the original and intended treatment plans. Several groups have studied anatomical changes using both phantoms and clinical data, showing the potential of adaptive treatment radiotherapy (ART) to optimize organ-at-risk (OAR) sparing when using highly conformal precision radiotherapy techniques [1,2,3,4,5]. Adapting the original treatment plan to the given anatomy every day or week can be a very time-consuming approach.

Objectives

Methods

Results

Discussion

Conclusion