Computer-aided Detection of Prostate Cancer with MRI: Technology and Applications

• Type of Material: Article
• Authors: Lizhi Liu, Emory University; Zhiquang Tian, Emory University; Zhenfeng Zhang, Sun Yat Sen University; Baowei Fei, Emory University
• Language: English
• Date: 2016-04-25
• Publisher: Elsevier
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2016 The Association of University Radiologists.
• Final Published Version (URL): http://dx.doi.org/10.1016/j.acra.2016.03.010
• Title of Journal or Parent Work: Academic Radiology
• ISSN: 1076-6332
• Volume: 23
• Issue: 8
• Start Page: 1024
• End Page: 1046
• Grant/Funding Information: Z. Zhang was supported by the National Natural Science Foundation of China (81372274).; The work was also partially supported by a Georgia Research Alliance Distinguished Scientists Award.; This work was partially supported by NIH grants R01CA156775, R21CA176684, and P50CA128301.
• Keywords: DIFFUSION-WEIGHTED MRI; Life Sciences & Biomedicine; WHOLE-MOUNT HISTOLOGY; GLEASON SCORE; MULTI-PARAMETRIC MRI; Radiology, Nuclear Medicine & Medical Imaging; CONTRAST-ENHANCED MRI; computer-aided detection; image quantification; MAGNETIC-RESONANCE IMAGES; HIGH-B-VALUE; Science & Technology; PERIPHERAL ZONE; MR imaging; ULTRASOUND-GUIDED BIOPSY; Prostate cancer; SUPPORT VECTOR MACHINES
• Research Categories: Engineering, Biomedical; Health Sciences, Radiology

Abstract

One in six men will develop prostate cancer in his lifetime. Early detection and accurate diagnosis of the disease can improve cancer survival and reduce treatment costs. Recently, imaging of prostate cancer has greatly advanced since the introduction of multiparametric magnetic resonance imaging (mp-MRI). Mp-MRI consists of T2-weighted sequences combined with functional sequences including dynamic contrast-enhanced MRI, diffusion-weighted MRI, and magnetic resonance spectroscopy imaging. Because of the big data and variations in imaging sequences, detection can be affected by multiple factors such as observer variability and visibility and complexity of the lesions. To improve quantitative assessment of the disease, various computer-aided detection systems have been designed to help radiologists in their clinical practice. This review paper presents an overview of literatures on computer-aided detection of prostate cancer with mp-MRI, which include the technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application.