Accuracy of deformable image registration for contour propagation in adaptive lung radiotherapy

Nicholas Hardcastle,Wouter Van Elmpt,Karl Bzdusek,Dirk De Ruysscher,Wolfgang A Tomé

doi:10.1186/1748-717x-8-243

Abstract

BackgroundDeformable image registration (DIR) is an attractive method for automatic propagation of regions of interest (ROIs) in adaptive lung radiotherapy. This study investigates DIR for automatic contour propagation in adaptive Non Small Cell Lung Carcinoma patients.MethodsPre and mid-treatment fan beam 4D-kVCT scans were taken for 17 NSCLC patients. Gross tumour volumes (GTV), nodal-GTVs, lungs, esophagus and spinal cord were delineated on all kVCT scans. ROIs were propagated from pre- to mid-treatment images using three DIR algorithms. DIR-propagated ROIs were compared with physician-drawn ROIs on the mid-treatment scan using the Dice score and the mean slicewise Hausdorff distance to agreement (MSHD). A physician scored the DIR-propagated ROIs based on clinical utility.ResultsGood agreement between the DIR-propagated and physician drawn ROIs was observed for the lungs and spinal cord. Agreement was not as good for the nodal-GTVs and esophagus, due to poor soft-tissue contrast surrounding these structures. 96% of OARs and 85% of target volumes were scored as requiring no or minor adjustments.ConclusionsDIR has been shown to be a clinically useful method for automatic contour propagation in adaptive radiotherapy however thorough assessment of propagated ROIs by the treating physician is recommended.

Highlights

Deformable image registration (DIR) is an attractive method for automatic propagation of regions of interest (ROIs) in adaptive lung radiotherapy
Anatomical changes are often observed during radiotherapy treatment of lung cancer; both normal tissues and tumor volumes can deform over time as a response to the radiation therapy
There has been limited investigation of DIR for automatic propagation of ROIs in adaptive lung radiotherapy where significant anatomical changes due to disease progression or response to radiotherapy may be observed between images; Lu et al investigated automated ROI propagation between Kilovoltage computed tomography (kVCT) and Megavoltage computed tomography (MVCT) scans in the Tomotherapy adaptive lung radiotherapy paradigm [18]

Summary

Introduction

Deformable image registration (DIR) is an attractive method for automatic propagation of regions of interest (ROIs) in adaptive lung radiotherapy. Anatomical changes are often observed during radiotherapy treatment of lung cancer; both normal tissues and tumor volumes can deform over time as a response to the radiation therapy. This can impact the delivered dose when using highly conformal treatment techniques. Automatic propagation of target and OAR contours between two image sets is an attractive approach to reducing adaptive radiotherapy resource requirements [7]. The aim of this study was to evaluate the clinical utility of three theoretically different DIR algorithms for the purpose of propagating contours from pre- to mid-treatment lung kVCT scans in the adaptive radiotherapy setting

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