Review
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Radiol. Oct 28, 2024; 16(10): 497-511
Published online Oct 28, 2024. doi: 10.4329/wjr.v16.i10.497
Quantitative magnetic resonance imaging in prostate cancer: A review of current technology
Ankita Dhiman, Virendra Kumar, Chandan Jyoti Das
Ankita Dhiman, Chandan Jyoti Das, Department of Radiodiagnosis and Interventional Radiology, All India Institute of Medical Sciences, New Delhi 110029, Delhi, India
Virendra Kumar, Department of NMR & MRI Facility, All India Institute of Medical Sciences, New Delhi 110029, Delhi, India
Author contributions: Dhiman A, Kumar V, and Das CJ wrote the manuscript; Kumar V and Das CJ supervised and finally approval of the manuscript.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Chandan Jyoti Das, MD, PhD, Professor, Department of Radiodiagnosis and Interventional Radiology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi 110029, Delhi, India. chandan.das@aiims.edu
Received: May 14, 2024
Revised: September 26, 2024
Accepted: October 20, 2024
Published online: October 28, 2024
Processing time: 166 Days and 21.4 Hours
Core Tip

Core Tip: Quantitative imaging has many advantages over conventional qualitative assessment. A few parameters have also been shown to correlate with the Gleason score and can help in deciding disease prognosis and clinical management. A quantitative imaging biomarker could improve prostate cancer (PCa) detection by minimizing inter-observer variability, thereby reducing overdiagnosis of clinically insignificant PCa (Gleason score < 7). This would help avoid unnecessary biopsies and decrease the overtreatment of slow-growing PCa. In addition, with further advancement in the quantitative imaging parameters, they may be used to monitor therapeutic response or to predict response to a particular treatment.