# Designing Novel MR Imaging Tools to Quantify Lower-Limb Exercise Adaptations in Knee Osteoarthritis

> **NIH NIH R01** · STANFORD UNIVERSITY · 2024 · $587,432

## Abstract

PROJECT SUMMARY
 Knee osteoarthritis (OA) is a major cause of disability without a cure that affects 20+ million US adults
and leads to large financial burdens. While the etiology of OA is unknown, it is thought to be related to altered
biochemical or biomechanical function of the joint. OA is slow to develop; the current treatment strategies for OA
are pain control using lifestyle or therapeutic interventions, until the patient requires a total knee replacement.
 The progressive loss of periarticular muscle mass and function reduces joint stability and health. Loss of
muscle mass and function is associated with aging, as is OA development and progression. While many OA
studies examine the bone, cartilage, synovium, and meniscus in the knee, the interplay between muscle function
and structure, and the initiation and progression of OA is unclear, despite recommendations of exercise as a
conservative treatment.
 In this study, we seek to build new imaging tools to sensitively measure the effects of muscle strength,
quality, and function on OA initiation and progression. This is an appealing area to study because disease-
modifying treatments such as exercise, physical therapy, and muscle-building drugs could both manage pain
and change disease progression. Toward this goal, we will build imaging tools to provide unparalleled insights
into exercise-induced microstructural changes in the muscle, subtle compositional changes in OA, and
biomechanically inspired biomarkers of how joint loads affect cartilage pressure.
 In Aim 1, we will build and validate a multi-vendor, highly accelerated, multi-parametric whole-bilateral-
limb magnetic resonance imaging (MRI) protocol that will enable acquiring high-resolution quantitative imaging
of both knees, thighs, and calves in under 20 minutes of scan time. In Aim 2, we will compute fully automated
and novel biomechanics-inspired imaging biomarkers for the cartilage, bone, and muscle. These will include
cartilage pressure maps to assess spatial joint loading profile, as well as neural shape models to model the
complex shapes of bones and muscles. In Aim 3, we will assess the responsiveness of these imaging measures
in a two-year longitudinal study in patients with early OA undergoing a walking-based muscle strengthening
intervention. We will quantify the impact of exercise on muscle structure, tissues in the knee, pain relief and OA
progression. We hypothesize that our novel imaging biomarkers have stronger association than current
functional tests on pain relief and OA progression, and that our baseline imaging can predict subject-specific
pain relief.
 Overall, our novel tools will elucidate the mechanistic interplay between exercise and OA physiology,
towards developing precision muscle strengthening programs. These insights will help accelerate the elusive
quest towards developing disease-modifying strategies for OA.

## Key facts

- **NIH application ID:** 10979947
- **Project number:** 2R01EB002524-18
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Akshay Chaudhari
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $587,432
- **Award type:** 2
- **Project period:** 2003-09-20 → 2028-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10979947

## Citation

> US National Institutes of Health, RePORTER application 10979947, Designing Novel MR Imaging Tools to Quantify Lower-Limb Exercise Adaptations in Knee Osteoarthritis (2R01EB002524-18). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10979947. Licensed CC0.

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