# 4D CT Imaging for Improved Diagnosis and Treatment of Wrist Ligament Injuries

> **NIH NIH R01** · MAYO CLINIC ROCHESTER · 2020 · $465,912

## Abstract

PROJECT SUMMARY/ABSTRACT
The wrist joint permits complex motion of the upper extremity that is crucial for both precision and power
movements during daily activities; therefore, wrist injuries which result in osteoarthritis (OA) come at a
significant socioeconomic cost due to time off work, surgical fees and associated morbidity. Injury to the
scapholunate interosseus ligament (SLIL), which connects the scaphoid and lunate bones in the proximal
carpal row, is one of the most important and common upper extremity injuries. Accurate diagnosis of the
location of SLIL injuries is crucial for providing the most effective treatments so that the location of the tear can
be considered in a tailored treatment plan. Further, unsuccessful surgical reconstructions occur up to 20%-
30% of the time, with patients often developing OA. Current diagnostic approaches for SLIL injury include
magnetic resonance imaging, which lacks the specificity to assess injury location, and wrist arthroscopy, which
is invasive and results in an injury grade that is subjective and prone to interobserver variability. Thus, there is
a critical need for an accurate, noninvasive, quantitative method for assessing SLIL injury location and
treatment outcomes; our novel, dynamic computed tomography (CT) imaging technique will fill this gap. Our
high spatial and temporal resolution 4D (3D + time) CT technique (4DCT) enables accurate quantification of
key metrics during wrist motion in patients with SLIL injury. This imaging approach, which has been rigorously
validated and is based on strong scientific premise, will improve clinical practice by replacing invasive and
inaccurate diagnostic tests and providing a means of quantifying outcomes of surgical repairs. In this project,
we propose to: establish the relationship between SLIL injury and 4DCT metrics in vitro (Aim 1); assess
whether the location of SLIL injury in patients can be predicted using 4DCT metrics (Aim 2); and determine
whether targeted treatment of ligament injury improves post-surgical outcomes (Aim 3). The innovation of this
project is the use of rigorously validated, dynamic, noninvasive 4DCT metrics to meet the critical need to
provide evidence-based information for the diagnosis and treatment of SLIL injury. The significance lies in the
accurate diagnosis of SLIL injuries that will lead to optimal treatment approaches, resulting in prevention of OA
due to injury or incorrect repair.

## Key facts

- **NIH application ID:** 9905487
- **Project number:** 5R01AR071338-04
- **Recipient organization:** MAYO CLINIC ROCHESTER
- **Principal Investigator:** Kristin Daigle Zhao
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $465,912
- **Award type:** 5
- **Project period:** 2017-05-01 → 2022-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9905487

## Citation

> US National Institutes of Health, RePORTER application 9905487, 4D CT Imaging for Improved Diagnosis and Treatment of Wrist Ligament Injuries (5R01AR071338-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9905487. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*