Evidence map›Paper›PMID 38767657›Full record

ArticleSkeletal radiology2025

Development and stability analysis of carpal kinematic metrics from 4D magnetic resonance imaging.

Azadeh Sharafi, Volkan E Arpinar, Andrew S Nencka, Kevin M Koch

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Article in Skeletal radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Azadeh SharafiRadiology, Medical College of Wisconsin, Madison, WI, USA. asharafi@mcw.edu.ORCID http://orcid.org/0000-0001-9572-4922
Volkan E ArpinarRadiology, Medical College of Wisconsin, Madison, WI, USA.
Andrew S NenckaRadiology, Medical College of Wisconsin, Madison, WI, USA.
Kevin M KochRadiology, Medical College of Wisconsin, Madison, WI, USA.

Funding

Enabling Kinematic Joint Profiling Using MRIR21AR075327 · NIAMS · MEDICAL COLLEGE OF WISCONSIN · PI KOCH, KEVIN M · 2020 to 2021
$379k
NIAMS NIH HHS R21 AR075327NIH HHS R21AR075327
6 · The paper itself

Abstract

objectiveTo develop MRI-derived carpal kinematic metrics and investigating their stability.

methodsThe study used a 4D MRI method to track scaphoid, lunate, and capitate movements in the wrist. A panel of 120 metrics for radial-ulnar deviation and flexion-extension was created using polynomial models of scaphoid and lunate movements relative to the capitate. Intraclass correlation coefficients (ICCs) analyzed intra- and inter-subject stability in 49 subjects, 20 with and 29 without wrist injury history.

resultsComparable degrees of stability were observed across the two different wrist movements. Among the total 120 derived metrics, distinct subsets demonstrated high stability within each type of movement. For asymptomatic subjects, 16 out of 17 metrics with high intra-subject stability also showed high inter-subject stability. The differential analysis of ICC values for each metric between asymptomatic and symptomatic cohorts revealed specific metrics (although relatively unstable) exhibiting greater variability in the symptomatic cohort, thereby highlighting the impact of wrist conditions on the variability of kinematic metrics.

conclusionThe findings demonstrate the developing potential of dynamic MRI for assessing and characterizing complex carpal bone dynamics. Stability analyses of the derived kinematic metrics revealed encouraging differences between cohorts with and without wrist injury histories. Although these broad metric stability variations highlight the potential utility of this approach for analyzing carpal instability, further studies are necessary to better characterize these observations.

Indexed as

Carpal BonesMagnetic Resonance ImagingAdultBiomechanical PhenomenaFemaleHumansImaging, Three-DimensionalMaleMiddle AgedRange of Motion, ArticularWrist InjuriesWrist Joint4D dynamic MRIKinematicsWrist instability

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.