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Radiation Oncology
Published in: Radiation Oncology 1/2014

Open Access 01-12-2014 | Research

Evaluation of an automatic segmentation algorithm for definition of head and neck organs at risk

Authors: David Thomson, Chris Boylan, Tom Liptrot, Adam Aitkenhead, Lip Lee, Beng Yap, Andrew Sykes, Carl Rowbottom, Nicholas Slevin

Published in: Radiation Oncology | Issue 1/2014

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Abstract

Background

The accurate definition of organs at risk (OARs) is required to fully exploit the benefits of intensity-modulated radiotherapy (IMRT) for head and neck cancer. However, manual delineation is time-consuming and there is considerable inter-observer variability. This is pertinent as function-sparing and adaptive IMRT have increased the number and frequency of delineation of OARs. We evaluated accuracy and potential time-saving of Smart Probabilistic Image Contouring Engine (SPICE) automatic segmentation to define OARs for salivary-, swallowing- and cochlea-sparing IMRT.

Methods

Five clinicians recorded the time to delineate five organs at risk (parotid glands, submandibular glands, larynx, pharyngeal constrictor muscles and cochleae) for each of 10 CT scans. SPICE was then used to define these structures. The acceptability of SPICE contours was initially determined by visual inspection and the total time to modify them recorded per scan. The Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm created a reference standard from all clinician contours. Clinician, SPICE and modified contours were compared against STAPLE by the Dice similarity coefficient (DSC) and mean/maximum distance to agreement (DTA).

Results

For all investigated structures, SPICE contours were less accurate than manual contours. However, for parotid/submandibular glands they were acceptable (median DSC: 0.79/0.80; mean, maximum DTA: 1.5 mm, 14.8 mm/0.6 mm, 5.7 mm). Modified SPICE contours were also less accurate than manual contours. The utilisation of SPICE did not result in time-saving/improve efficiency.

Conclusions

Improvements in accuracy of automatic segmentation for head and neck OARs would be worthwhile and are required before its routine clinical implementation.
Appendix
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Metadata
Title
Evaluation of an automatic segmentation algorithm for definition of head and neck organs at risk
Authors
David Thomson
Chris Boylan
Tom Liptrot
Adam Aitkenhead
Lip Lee
Beng Yap
Andrew Sykes
Carl Rowbottom
Nicholas Slevin
Publication date
01-12-2014
Publisher
BioMed Central
Published in
Radiation Oncology / Issue 1/2014
Electronic ISSN: 1748-717X
DOI
https://doi.org/10.1186/1748-717X-9-173

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