Open Access Research

A multi-institution evaluation of deformable image registration algorithms for automatic organ delineation in adaptive head and neck radiotherapy

Nicholas Hardcastle123*, Wolfgang A Tomé134, Donald M Cannon1, Charlotte L Brouwer5, Paul WH Wittendorp5, Nesrin Dogan6, Matthias Guckenberger7, Stéphane Allaire8, Yogish Mallya9, Prashant Kumar9, Markus Oechsner7, Anne Richter7, Shiyu Song6, Michael Myers6, Bülent Polat7 and Karl Bzdusek10

Author Affiliations

1 Department of Human Oncology, University of Wisconsin-Madison, Madison, WI, USA

2 Department of Physical Sciences, Peter MacCallum Cancer Centre, Locked Bag 1 A’Beckett St., Melbourne, VIC, 8006, Australia

3 Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW, Australia

4 Departments of Medical Physics and Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA

5 Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands

6 Department of Radiation Oncology, Virginia Commonwealth University Medical Center, Richmond, VA, USA

7 Department of Radiation Oncology, University Hospital Würzburg, Würzburg, Germany

8 Radiation Medicine Program, Princess Margaret Hospital, Toronto, ON, Canada

9 Philips Electronics India Pvt. Ltd., Philips Innovation Campus, Bangalore, India

10 Philips Radiation Oncology Systems, Madison, WI, USA

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Radiation Oncology 2012, 7:90  doi:10.1186/1748-717X-7-90

Published: 15 June 2012

Abstract

Background

Adaptive Radiotherapy aims to identify anatomical deviations during a radiotherapy course and modify the treatment plan to maintain treatment objectives. This requires regions of interest (ROIs) to be defined using the most recent imaging data. This study investigates the clinical utility of using deformable image registration (DIR) to automatically propagate ROIs.

Methods

Target (GTV) and organ-at-risk (OAR) ROIs were non-rigidly propagated from a planning CT scan to a per-treatment CT scan for 22 patients. Propagated ROIs were quantitatively compared with expert physician-drawn ROIs on the per-treatment scan using Dice scores and mean slicewise Hausdorff distances, and center of mass distances for GTVs. The propagated ROIs were qualitatively examined by experts and scored based on their clinical utility.

Results

Good agreement between the DIR-propagated ROIs and expert-drawn ROIs was observed based on the metrics used. 94% of all ROIs generated using DIR were scored as being clinically useful, requiring minimal or no edits. However, 27% (12/44) of the GTVs required major edits.

Conclusion

DIR was successfully used on 22 patients to propagate target and OAR structures for ART with good anatomical agreement for OARs. It is recommended that propagated target structures be thoroughly reviewed by the treating physician.

Keywords:
Deformable image registration; Adaptive radiotherapy; Head and neck cancer