Thursday, April 18, 2024
4/18/2024
Project Summary/Abstract Prostate cancer (PCa) is the most common malignancy and is the 2nd leading cause of cancer-related mortality in males in the United States. Despite high incidence and tremendous human and economic impact of PCa, there is no good screening test for clinically significant PCa. Commonly used blood test for Prostate Specific Antigen (PSA) is inexpensive but lack specificity for clinically significant PCa. Over the last decade, multi- parametric prostate MRI has been shown to have an increasingly important role in the detection and localization of clinically significant PCa. Despite the demonstrated value of prostate MRI, there are two major challenges in clinical implementation of prostate MRI as a first-line screening tool at a population level: (1) high cost of the scanner and the exam, which decreases accessibility, and (2) lack of robustness of the MRI exam. To overcome these limitations we propose establishing a low-field, robust, widely accessible, and thus low- cost high-performance MRI system for PCa screening. Major challenges for imaging at lower field strength is the lower signal to noise (SNR) and thus longer acquisition times compared to 1.5 and 3.0 T. In this proposal we aim to address these efficiency and scan time challenges at low field. Our team of clinical and imaging scientists will bring to bear novel acquisition and reconstruction techniques to restore SNR, specifically random matrix theory (RMT- a technique our center has recently introduced), and deep-learning- based image reconstruction (an area our group has helped to pioneer). We will evaluate these techniques in healthy volunteers and patients with PCa. Subsequently, we will perform head-to-head comparison of low-field bi-parametric exam to routine clinical 1.5 T or 3.0 T MRI exams in 30 patients with known or suspected PCa.
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