# Quantitative, Image-Based Osteoarthritis Biomarkers Software Resubmission

> **NIH NIH R44** · KITWARE, INC. · 2021 · $445,896

## Abstract

PROJECT SUMMARY
Musculoskeletal diseases are common in the United States, especially among the elderly and individuals of
low socioeconomic status, and they take a large toll on the Nation's overall health status. Bone disorders are
diagnosed by exploring a patient's medical history and by physical exam, alongside laboratory tests, bone 
biopsies, and imaging tests. Bone imaging tests provide a non-invasive way to examine at bone structure. However,
imaging data is often evaluated qualitatively or with operator dependence as opposed to automated or quantitative
measurements. These quantitative measurements are not sensitive enough to detect subtle variations in bone
quality associated with early disease progression. We propose the development of high performance, multimodal,
and automated 3D bone characterization tools, which are accessible through a web browser. A broad range
of researchers and clinicians can leverage these tools to obtain high-throughput, reproducible biomarkers for
statistically sensitive research studies. The system will automatically segment bone and cartilage and quantify
biomarkers from the regions of interest. The proposed system will have superior high-throughput capabilities
over existing bone image analysis suites, and it will provide access to state-of-the-art algorithms for researchers
without programming abilities. In addition to providing a powerful resource to the research community, we will
commercialize this complete, streamlined analytical solution by offering it as an online fee-per-image processing
service. Our system will be validated by demonstrating that we can detect skeletal deterioration in preclinical
studies, which can potentially lead to new clinical trials for novel therapeutic and diagnostic approaches in
humans. We will test the hypothesis that the system can automatically identify osteoarthritis in knee images
from the Osteoarthritis Initiative database and differentiate hemophilia in micro-computed tomography images.
The ultimate goal of the proposed project is to lead to better preventive strategies and improved progression
monitoring of osteoarthritis and related diseases.

## Key facts

- **NIH application ID:** 10250562
- **Project number:** 5R44AR074375-03
- **Recipient organization:** KITWARE, INC.
- **Principal Investigator:** Matthew McCormick
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $445,896
- **Award type:** 5
- **Project period:** 2019-09-01 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10250562

## Citation

> US National Institutes of Health, RePORTER application 10250562, Quantitative, Image-Based Osteoarthritis Biomarkers Software Resubmission (5R44AR074375-03). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10250562. Licensed CC0.

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