A 3D Neurovascular Bundles Segmentation Method based on MR-TRUS Deformable Registration

• Type of Material: Article
• Authors: Xiaofeng Yang, Emory University; Peter Rossi, Emory University; Ashesh B Jani, Emory University; Hui Mao, Emory University; Tomi Ogunleye, Emory University; Walter J Curran, Emory University; Tian Liu, Emory University
• Language: English
• Date: 2015-03-20
• Publisher: Society of Photo-optical Instrumentation Engineers (SPIE)
• Publication Version: Final Published Version
• Copyright Statement: © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
• Final Published Version (URL): http://dx.doi.org/10.1117/12.2077828
• Title of Journal or Parent Work: Proceedings of SPIE
• ISSN: 0277-786X
• Volume: 9413
• Grant/Funding Information: This research is supported by the Department of Defense (DoD) Prostate Cancer Research Program (PCRP) Award W81XWH-13–1-0269.
• Keywords: neurovascular bundles; erectile dysfunction; segmentation; NVB; MRI-US registration
• Research Categories: Physics, Radiation; Health Sciences, Radiology

Abstract

In this paper, we propose a 3D neurovascular bundles (NVB) segmentation method for ultrasound (US) image by integrating MR and transrectal ultrasound (TRUS) images through MR-TRUS deformable registration. First, 3D NVB was contoured by a physician in MR images, and the 3D MRdefined NVB was then transformed into US images using a MR-TRUS registration method, which models the prostate tissue as an elastic material, and jointly estimates the boundary deformation and the volumetric deformations under the elastic constraint. This technique was validated with a clinical study of 6 patients undergoing radiation therapy (RT) treatment for prostate cancer. The accuracy of our approach was assessed through the locations of landmarks, as well as previous ultrasound Doppler images of patients. MR-TRUS registration was successfully performed for all patients. The mean displacement of the landmarks between the post-registration MR and TRUS images was less than 2 mm, and the average NVB volume Dice Overlap Coefficient was over 89%. This NVB segmentation technique could be a useful tool as we try to spare the NVB in prostate RT, monitor NVB response to RT, and potentially improve post-RT potency outcomes.