Soumya Ghose1, Lois Holloway2, Karen Lim3, Philip Chan4, Jacqueline Veera3, Shalini K Vinod5, Gary Liney6, Peter B Greer7, Jason Dowling8. 1. Australian e-Health Research Centre, Royal Brisbane and Women's Hospital, Commonwealth Scientific and Industrial Research Organization, Brisbane, Queensland 4029, Australia. Electronic address: soumya.ghose@csiro.au. 2. Department of Radiation Oncology, Liverpool Hospital, Elizabeth Street, Liverpool, New South Wales 2170, Australia; Institute of Medical Physics, Sydney University, City Road, Darlington, New South Wales 2008, Australia; Centre For Medical Radiation Physics, University of Wollongong, Northfields Avenue, Wollongong, New South Wales 2522, Australia; South Western Clinical School, University of New South Wales, Sydney, New South Wales 2170, Australia. 3. Department of Radiation Oncology, Liverpool Hospital, Elizabeth Street, Liverpool, New South Wales 2170, Australia. 4. Royal Brisbane and Women's Hospital, Butterfield Street, Herston, Queensland 4029, Australia; School of Medicine, University of Queensland, 288 Herston Road, Herston, Brisbane, Queensland 4006, Australia. 5. Department of Radiation Oncology, Liverpool Hospital, Elizabeth Street, Liverpool, New South Wales 2170, Australia; South Western Clinical School, University of New South Wales, Sydney, New South Wales 2170, Australia; University of Western Sydney, Richmond, New South Wales 2753, Australia. 6. Ingham Institute for Applied Medical Research, Liverpool Hospital, 1 Campbell Street, Liverpool, New South Wales 2170, Australia. 7. Department of Radiation Oncology, Calvary Mater Newcastle Hospital, Edith Street, Waratah, New South Wales 2298, Australia; Department of Physics, University of Newcastle, Callaghan, New South Wales 2308, Australia. 8. Australian e-Health Research Centre, Royal Brisbane and Women's Hospital, Commonwealth Scientific and Industrial Research Organization, Brisbane, Queensland 4029, Australia.
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 2-4mm 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.
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 2-4mm 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.
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