SBIR/STTR Research Award

MR Virtual Pathology of the Prostate

Award identifier a2d67aa37f988fb112ad276bc949f676959d183e014766eac0b2df6536b271d1Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$225,000

Program and phase

STTR · Phase I

Award year

2020

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
QMIS
Proposal award date
2020-04-01
Contract end date
2021-03-31
UEI
N4RDVK4GLL14
Solicitation number
PA19-270
Topic code
102

Research 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 scanners in the U.S., with revenues of $250M. This market will expand significantly when MVP2 is accepted for routine prostate screening.Project Narrative Prostate Cancer is the most frequently diagnosed and second most fatal type of cancer for U.S. men, impacting 1 in 9 men, and causing 29,500 deaths each year. There are no effective screening methods for prostate cancer and as a result millions of men receive unnecessary biopsies and invasive treatments that cause serious side effects, while many clinically significant cancers are missed. QMIS, LLC (Quantitative Magnetic Resonance Imaging Solutions) requests STTR funding to develop a proprietorial new MRI-screening method, based on ‘virtual MRI pathology’, that can avoid unnecessary biopsies and treatments (e.g. radical prostatectomy), while ensuring that clinically significant cancers are found early when they can be treated very effectively.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

2 SBIR/STTR records share this UEI (2020–2022). Reported award amounts total $2,274,960. Reported amounts are not federal obligations.

Phases: Phase II, Phase I

Agencies: Department of Health and Human Services

Agency intelligence

Department of Health and Human Services

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