Fusing MRI and Mechanical Imaging for Improved Prostate Cancer Diagnosis
Abstract
Objectives and Rationales: In the United States in 2012, of the 1.3 million transrectal ultrasound (TRUS) biopsies, around 400,000 cases were negative. A large number of these men with initial negative biopsies return for a repeat biopsy on account of rising PSA (prostate specific antigen). The majority of the resulting biopsy specimens (~90%) are negative while ~70% of patients that undergo biopsies do not have prostate cancer (PCa). While there has been some recent promising data on the role of magnetic resonance imaging (MRI) in active surveillance and in vivo grading of disease, in particular the role of diffusion weighted imaging for in vivo assessment of cancer grade, specificity of multi-parametric MRI in distinguishing between low versus intermediate/high-grade prostate cancer, and benign cancer confounders (e.g., benign prostatic hyperplasia (BPH), high-grade prostatic intra-epithelial neoplasia (HGPIN), inflammation) and prostatic adenocarcinoma is still an open issue. MR-Elastography (MRE) has shown promising clinical results and could facilitate PCa detection. However, MRE is still not routinely employed in clinical practice due to the high cost and technical challenges, even after 20 years since it has been introduced. The proposed technology will merge two complementary imaging modalities, MP-MRI and a novel Food and Drug Administration (FDA)-approved prostate mechanical imaging (PMI) technology to address the urgent need for marked improvement in prostate cancer detection, especially in the context of repeat biopsies. While the cost of MRI makes it difficult to justify as a screening modality, the proposed fused PMI-MRI technology could have significant clinical impact and adoption in reducing the extremely poor detection sensitivity of repeat TRUS biopsies, which is around 16% following an initial negative biopsy. Applicability and Research Impact: Direct MR-Elastography imaging currently requires significant changes to existing MRI machines. In contrast, as PMI has already received FDA approval, the path to market is relatively short. PMI/MRI fusion is hence a cheaper, more viable alternative offering the advantages of MR-Elastography and no issues to prevent its immediate use. MRI is not cost-effective to be used in screening mode. Current MRI has a negative predictive value of 89% for clinically significant disease but a lower specificity for lower grade disease, which is often confounded by presence of other similar appearing pathology (e.g., BPH, inflammation, HGPIN). However, MRI could be used in patients identified as high-risk/suspicious via a low-cost PMI exam (PMI thus serving as a triage). The higher cost of MRI would be offset by savings due to a reduction in unnecessary biopsies, surgeries, and treatment complications. Immediate outcomes of the project will include significant descriptors for quantifying the effectiveness of MRI data, as well as the first attempt of its kind in not only quantifying elastography imaging, but also constructing a fused mechanical-radiological signature for prostate cancer detection. Innovation: This study will be the first of its kind to fuse mechanical imaging and multi-parametric MRI, making available for the first time functional, structural, and mechanical imaging parameters for characterization of prostate cancer. Quantitative tools will be developed to analyze mechanical imaging parameters and better understand their effectiveness for prostate cancer detection in vivo. Computerized decision support and fusion tools for prostate cancer that will be developed as part of this study will include: (1) automated registration and modeling techniques to fuse mechanical, histological, and radiological data into an in vivo imaging-based descriptor for prostate cancer, (2) methods for the automated integrated analysis of multi-functional MRI and mechanical imaging channels, (3) unique visualizations of radiological and elastography information from
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Apr 04, 2016
- Source ID
- W81XWH1510613
Entities
People
- Mahdi Orooji
Organizations
- Case Western Reserve University
- United States Army