A c c e p t e d M a n u s c r i p t Highlights This paper reviews the current state-of-the-art segmentation and deformable registration methods applied to cervical cancer adaptive radiation therapy planning. Strength and weaknesses of the registration and the segmentation methods are studied and analysed. Use of shape prior constraints can significantly reduce segmentation and registration errors. Use of tissue specific classification of tumour may reduce tumour segmentation error. *Highlights (for review)Page 2 of 30 A c c e p t e d M a n u s c r i p t Abstract ObjectiveManual contouring and registration for radiotherapy treatment planning and online adaptation for cervical cancer radiation therapy in computed tomography (CT) and magnetic resonance images (MRI) is 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. MethodsSegmentation 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. ResultsIn 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. ConclusionsMost 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 segmen- 1Page 3 of 30 A c c e p t e d M a n u s c r i p t tation and registration accuracy compared to other models.
Introduction: Magnetic Resonance Imaging (MRI) provides excellent soft tissue definition of pelvic tumours and organs. The aim of this study was to quantify differences in delineated clinical target volumes (CTVs) between computed tomography (CT) and MRI. Methods: Twenty patients with locally advanced gynaecological malignancies were recruited. Patients underwent dedicated MRI simulation following CT simulation. Four clinicians independently contoured each CT and MRI. CTV structures were contoured using the Radiation Therapy Oncology Group (RTOG) guidelines and lymph node CTV (LN-CTV) according to published guidelines. Interobserver variability was analysed using the dice similarity coefficient (DSC) and mean absolute surface distance (MASD). Results: Gross tumour volume delineation was more consistent on MRI compared to CT, the DSC improved from 0.77 on CT to 0.81 on MRI, P < 0.01. GTV volumes were significantly smaller on MRI compared to CT (MRI 92 cc vs. CT 117 cc, P < 0.01). The LN-CTV and combined CTV volumes were both significantly smaller on MRI compared to CT (LN-CTV: MRI 324 cc vs CT 354 cc, P < 0.01 and combined CTV: MRI 560 cc vs CT 600 cc, P < 0.01). The LN-CTV DSC was 0.75 for both MRI and CT, and the combined CTV DSC was 0.81 for MRI and 0.80 for CT, P = 0.27. Vagina and parametria volumes exhibited more variability compared to other structures. Conclusions: Magnetic Resonance Imaging contouring resulted in smaller and more consistently delineated volumes when compared to CT for most CTV structures. An MRI contouring atlas is provided to complement the existing RTOG contouring guidelines.
IntroductionMagnetic resonance imaging (MRI) is increasingly used for target volume delineation in radiotherapy due to its superior soft tissue visualisation compared to computed tomography (CT). The aim of this study was to assess the impact of a radiologist‐led workshop on inter‐observer variability in volume delineation on MRI.MethodsData from three separate studies evaluating the impact of MRI in lung, breast and cervix were collated. At pre‐workshop evaluation, observers involved in each clinical site were instructed to delineate specified volumes. Radiologists specialising in each cancer site conducted an interactive workshop on interpretation of images and anatomy for each clinical site. At post‐workshop evaluation, observers repeated delineation a minimum of 2 weeks after the workshops. Inter‐observer variability was evaluated using dice similarity coefficient (DSC) and volume similarity (VOLSIM) index comparing reference and observer volumes.ResultsPost‐workshop primary gross tumour volumes (GTV) were smaller than pre‐workshop volumes for lung with a mean percentage reduction of 10.4%. Breast clinical target volumes (CTV) were similar but seroma volumes were smaller post‐workshop on both supine (65% reduction) and prone MRI (73% reduction). Based on DSC scores, improvement in inter‐observer variability was seen for the seroma cavity volume on prone MRI with a reduction in DSC score range from 0.4–0.8 to 0.7–0.9. Breast CTV demonstrated good inter‐observer variability scores (mean DSC 0.9) for both pre‐ and post‐workshop. Post‐workshop observer delineated cervix GTV was smaller than pre‐workshop by 26.9%.ConclusionA radiologist‐led workshop did not significantly reduce inter‐observer variability in volume delineation for the three clinical sites. However, some improvement was noted in delineation of breast CTV, seroma volumes and cervix GTV.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.