A review of segmentation and deformable registration methods applied to adaptive cervical cancer radiation therapy treatment planning

Ghose, Soumya, Holloway, Lois, Lim, Karen, Chan, Philip, Veera, Jacqueline, Vinod, Shalini K., Liney, Gary, Greer, Peter B. and Dowling, Jason (2015) A review of segmentation and deformable registration methods applied to adaptive cervical cancer radiation therapy treatment planning. Artificial Intelligence in Medicine, 64 2: 75-87. doi:10.1016/j.artmed.2015.04.006

Attached Files (Some files may be inaccessible until you login with your UQ eSpace credentials)
Name Description MIMEType Size Downloads
UQ362642_OA.pdf Full text (open access) application/pdf 2.37MB 2

Author Ghose, Soumya
Holloway, Lois
Lim, Karen
Chan, Philip
Veera, Jacqueline
Vinod, Shalini K.
Liney, Gary
Greer, Peter B.
Dowling, Jason
Title A review of segmentation and deformable registration methods applied to adaptive cervical cancer radiation therapy treatment planning
Journal name Artificial Intelligence in Medicine   Check publisher's open access policy
ISSN 1873-2860
0933-3657
Publication date 2015-06
Year available 2015
Sub-type Article (original research)
DOI 10.1016/j.artmed.2015.04.006
Open Access Status File (Author Post-print)
Volume 64
Issue 2
Start page 75
End page 87
Total pages 13
Place of publication Amsterdam, Netherlands
Publisher Elsevier BV
Collection year 2016
Language eng
Formatted abstract
Objective: Manual contouring and registration for radiotherapy treatment planning and online adaptation for cervical cancer radiation therapy in computed tomography (CT) and magnetic resonance images (MRI) are often necessary. However manual intervention is time consuming and may suffer from inter or intra-rater variability. In recent years a number of computer-guided automatic or semi-automatic segmentation and registration methods have been proposed. Segmentation and registration in CT and MRI for this purpose is a challenging task due to soft tissue deformation, inter-patient shape and appearance variation and anatomical changes over the course of treatment. The objective of this work is to provide a state-of-the-art review of computer-aided methods developed for adaptive treatment planning and radiation therapy planning for cervical cancer radiation therapy.

Methods: Segmentation and registration methods published with the goal of cervical cancer treatment planning and adaptation have been identified from the literature (PubMed and Google Scholar). A comprehensive description of each method is provided. Similarities and differences of these methods are highlighted and the strengths and weaknesses of these methods are discussed. A discussion about choice of an appropriate method for a given modality is provided.

Results: In the reviewed papers a Dice similarity coefficient of around 0.85 along with mean absolute surface distance of 2-4. mm for the clinically treated volume were reported for transfer of contours from planning day to the treatment day.

Conclusions: Most segmentation and non-rigid registration methods have been primarily designed for adaptive re-planning for the transfer of contours from planning day to the treatment day. The use of shape priors significantly improved segmentation and registration accuracy compared to other models.
Keyword B-spline registration
Cervical cancer radiation therapy
Statistical shape models
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
School of Medicine Publications
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 2 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 4 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Tue, 09 Jun 2015, 03:28:54 EST by System User on behalf of Scholarly Communication and Digitisation Service