# MR Virtual Pathology of the Prostate > **NIH NIH R41** · QMIS, LLC · 2020 · $225,000 ## Abstract QMIS, LLC (Quantitative MRI Solutions) is developing a new MRI-based tool that reliably screens for prostate cancer (PCa). PCa is a leading cause of death (29,500 U.S. deaths in 2018). Current methods (PSA and digital rectal exam) are unreliable; they result in unnecessary biopsies while missing clinically significant PCa. MRI has potential to detect PCa at an early stage when it is highly curable, because of its excellent soft tissue contrast. However, conventional MRI methods produce highly variable and unreliable results. QMIS is developing an innovative, proprietorial MRI technology, ‘MVP2’ (MR Virtual Pathology of the Prostate), for analysis of prostate tissue at the microscopic level to provide data comparable to histology (patent pending). Preliminary studies show that MVP2 improves cancer detection relative to conventional MRI. However, our work has been hindered by lack of co-registration of MRI with gold standard whole mount histology. We propose to accurately register MRI data with histology and develop new algorithms that maximize correspondence between MRI and histology. Since histology is the gold standard for diagnosis, this will demonstrate the diagnostic utility of MVP2, and will be a major advance relative to current MRI methods. This revised STTR will produce user-friendly MVP2 software operating on workstations and MRI scanners to produce maps of tissue composition that reliably identify clinically significant PCa for routine screening. MVP2 is based on compartmental analysis of HM-MRI (hybrid-multidimensional MRI) data to measure volume fractions of lumen, stroma, and epithelium. High epithelial fraction and low stromal and luminal fractions indicate PCa. We will develop MVP2 software for ‘virtual histology’ based on precise correlation with co- registered quantitative histology. MVP2 will maximize Radiologists’ accuracy and efficiency, and avoid unnecessary biopsies and treatment, while ensuring that clinically significant cancers are found and treated at an early stage. This will reduce physical, emotional, and financial costs of PCa. The Specific Aims are: Specific Aim 1 –Based on precise co-registration of MRI and histology (data from 40 men), develop a compartmental model and fitting parameters to maximize agreement between MVP2 and quantitative histology. Specific Aim 2 –Evaluate diagnostic effectiveness of MVP2 by retrospectively analyzing 90 HM-MRI datasets from men who received prostatectomies. We will measure sensitivity, positive predictive value, and false negative fraction of MVP2 compared to Radiologists’ interpretation of multi-parametric MR images. We expect to demonstrate with high statistical confidence that MVP2 is more accurate than Radiologists’ diagnosis based on PIRADS v2 guidelines. MVP2 software will be designed to meet FDA standards. Commercial Application: We have discussed validation of MVP2 with the FDA and expect 510K clearance in 12 months. We expect to place MVP2 on 30% of the 12,500 MRI scanne... ## Key facts - **NIH application ID:** 10008041 - **Project number:** 1R41CA244056-01A1 - **Recipient organization:** QMIS, LLC - **Principal Investigator:** Gregory S. Karczmar - **Activity code:** R41 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $225,000 - **Award type:** 1 - **Project period:** 2020-04-01 → 2021-09-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10008041 ## Citation > US National Institutes of Health, RePORTER application 10008041, MR Virtual Pathology of the Prostate (1R41CA244056-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10008041. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*