# Computer Aided Diagnostic System for Prostate Cancer Detection Using Quantitative Multiparametric MRI

> **NIH NIH R01** · UNIVERSITY OF MINNESOTA · 2021 · $598,014

## Abstract

Despite the prevalence of prostate cancer, the current tools available to manage the disease continues to
leave physicians and their patients in a position to overdiagnose and overtreat. The confidence to pursue more
conservative approaches like active surveillance are limited, as biopsy is known to underestimate the grade
and extent of disease, both of which are important for risk stratification. Targeted biopsies, by means of MRI-
guidance, are becoming the preferred way to ensure the most aggressive appearing lesions are sampled in the
hopes of avoiding some of the issues with standard biopsy approaches. These targeted biopsies make use of
multi-parametric MRI (mpMRI) which includes both anatomical and functional information that are
complimentary and together increase the sensitivity and specificity for cancer detection. However, the ability to
effectively use mpMRI requires specialized training while the standards for properly using the multiple MRI
datasets are still being developed. To address this issue, we have developed an alternative method that would
provide a quantitative, user-independent, summary of the mpMRI data (qMRI) to visually “map” disease and
assess its aggressiveness. Using quantitative MRI, a Composite Biomarker Score (CBS) map is generated,
with a demonstrated increase in sensitivity and specificity for tumor detection compared to any single qMRI
parameter. Our primary goal is to integrate this predictive qMRI model into a computer-aided diagnostic (CAD)
system (referred to as CBS-CAD) to improve the use of mpMRI in PCa management. Employing quantitative
MRI (qMRI) can address the issues of a qualitative image analysis if the major roadblocks to its adoption can
be overcome. To address the roadblocks and implement the CBS-CAD system we will pursue the following
specific aims: 1) develop an analysis pipeline to evaluate qMRI performance and translate CBS-CAD methods,
2) perform a multi-vendor, multi-site quantitative imaging technical performance evaluation and 3) perform a
multi-center clinical validation study assessing CBS-CAD performance. Our expected outcome of this
academic-industry partnership will be the integration of several novel technologies into a comprehensive CAD
system consisting of a phantom and automated software for 1) qMRI system validation and 2) clinical
translation of novel models for detecting cancer and assessing aggressiveness.

## Key facts

- **NIH application ID:** 10122060
- **Project number:** 1R01CA241159-01A1
- **Recipient organization:** UNIVERSITY OF MINNESOTA
- **Principal Investigator:** Gregory John Metzger
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $598,014
- **Award type:** 1
- **Project period:** 2021-09-23 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10122060

## Citation

> US National Institutes of Health, RePORTER application 10122060, Computer Aided Diagnostic System for Prostate Cancer Detection Using Quantitative Multiparametric MRI (1R01CA241159-01A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10122060. Licensed CC0.

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