# Classification of Ankle Osteoarthritis Severity from Weightbearing Computed Tomography Using Statistical Shape Modeling and Machine Learning

> **NIH NIH K01** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2024 · $134,716

## Abstract

PROJECT SUMMARY
Candidate: Dr. Amy Lenz is a research track faculty in Orthopaedics at the University of Utah. She has an
outstanding biomechanics background with a focus on merging experimental and modeling methods utilizing
her PhD in Engineering Mechanics. Her primary research interests involve using advanced medical imaging
techniques and computational modeling to study foot and ankle (F&A) orthopaedic biomechanics.
Career Development: This award will ensure Dr. Lenz finalizes training in advanced statistical shape
modeling (SSM) techniques to characterize morphometric variability in patients with tibiotalar and subtalar
osteoarthritis (OA) and is poised to grow a prolific independent research laboratory as an early career faculty
focused on developing new quantitative clinical tools for patients suffering from end-stage ankle OA.
Research Strategy: Dr. Lenz studies F&A morphology and kinematic function in patients with end-stage OA
and outcomes following surgical intervention. Clinical evaluation of end-stage ankle OA is primarily derived
from 2D conventional radiographs. She proposes a computational study to characterize ankle joint complex
disease by quantifying 3D anatomical variation through SSM of OA tibiotalar and subtalar joints. Dr. Lenz’s
preliminary data show that patients with ankle OA present with significant changes in morphology of the ankle
joint complex compared with healthy individuals. Her overall goal is to develop a mathematical model powered
by machine learning to characterize severity of OA identified on weightbearing computed tomography (CT)
scans. Based on the model classification, this research will ultimately guide clinicians with a consistent tool for
interpreting CTs and provide an increased morphometric understanding beyond conventional radiographs.
Mentor Committee: Dr. Lenz has identified a diverse, strong mentoring team. Her primary mentor is Dr.
Anderson in Orthopaedics at Utah, who has a 4+ year mentoring relationship with Dr. Lenz and is a well-
funded established professor in the field. Her computational mentor is Dr. Elhabian from the Scientific
Computing and Imaging Institute at Utah, and a current PI on two SSM NIH grants, will advise the application
of SSM software. Dr. Whitaker, imaging scientist mentor, is the director of the School of Computing and has a
strong history of NIH funding and mentorship of scientists. Dr. Saltzman is her clinical surgical mentor in
Orthopaedics at Utah and has collaborated with her for the last 4+ years, supporting her career advancement.
Dr. Mills at Utah is her musculoskeletal radiologist mentor and has a focus in F&A imaging. Dr. Ledoux, from
the VA Puget Sound, is an external mentor to provide expert insights as a leader in F&A biomechanics.
Environment: The University of Utah boasts an exceptional research environment with leaders in
computational modeling and orthopaedics to successfully execute this multidisciplinary research. In addition,
the Department of Orthop...

## Key facts

- **NIH application ID:** 10893330
- **Project number:** 5K01AR080221-03
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** Amy L. Lenz
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $134,716
- **Award type:** 5
- **Project period:** 2022-08-01 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10893330

## Citation

> US National Institutes of Health, RePORTER application 10893330, Classification of Ankle Osteoarthritis Severity from Weightbearing Computed Tomography Using Statistical Shape Modeling and Machine Learning (5K01AR080221-03). Retrieved via AI Analytics 2026-06-11 from https://api.ai-analytics.org/grant/nih/10893330. Licensed CC0.

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