# Core C:  Imaging Core

> **NIH NIH U19** · BOSTON UNIVERSITY MEDICAL CAMPUS · 2024 · $1,270,103

## Abstract

ABSTRACT Imaging Core
Large scale knee imaging in MOST, including from MRI, radiographs and dual energy CT (DECT), has catalyzed
insights into the evolution of structural disease and the relation of structural pathology to joint pain in OA. In the
MOST4 program, expanded use of new imaging modalities including low-dose weight bearing CT of the lower
limb and DECT will add to the richness of these assessments. Deriving valid insights from these imaging
modalities requires attention to the quality of the images acquired and similar focus on the analysis and
processing of the imaging data. The Imaging Core will provide for all of these imaging modalities rigorous
oversight of the quality of the images and of the information gleaned from them. In doing so, the Imaging Core
will enrich immeasurably insights provided by MOST4. The overall goals of the Imaging Core for MOST4 are to:
1) ensure the high quality and completeness of images acquired by the clinical centers, including 1.5T MRI of
the knee (at MOST4 V1 and V2), and a group of images at MOST4 V1, including hand X-rays and weight-bearing
CT of the knees and other lower limb joints, and ultrasound and DECT of the knee; 2) oversee the reading
centers to ensure the high quality of data derived from the images; 3) and provide analysis ready reading center
data and images needed for all four MOST4 Projects and other approved MOST projects. The Imaging Core will
achieve these goals by adapting and updating methods honed and successfully applied during the past 19 years
over three funding cycles of MOST. By achieving these goals, the Imaging Core will ensure that MOST4 has the
high-quality joint imaging data that is essential to achieving a deeper understanding of the role of specific joint
structures in OA pathogenesis, of the inter-relationship between changes in different structures and how they
are in turn related to joint symptoms. The Imaging Core will also use deep learning methods to combine data
from MOST3 DECT and MRI images for exploratory analyses of the role of intra-articular crystals in co-localized
cartilage loss.

## Key facts

- **NIH application ID:** 10843724
- **Project number:** 5U19AG076471-02
- **Recipient organization:** BOSTON UNIVERSITY MEDICAL CAMPUS
- **Principal Investigator:** MICHAEL C NEVITT
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,270,103
- **Award type:** 5
- **Project period:** 2023-06-01 → 2028-02-29

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10843724

## Citation

> US National Institutes of Health, RePORTER application 10843724, Core C:  Imaging Core (5U19AG076471-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10843724. Licensed CC0.

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