Literature DB >> 32447815

Three-Dimensional Surface-Based Analysis of Cartilage MRI Data in Knee Osteoarthritis: Validation and Initial Clinical Application.

James W MacKay1,2, Joshua D Kaggie1, Graham M Treece3, Stephen M McDonnell4, Wasim Khan4, Alexandra R Roberts5,6, Robert L Janiczek5, Martin J Graves1, Tom D Turmezei2,7, Andrew W McCaskie4, Fiona J Gilbert1.   

Abstract

BACKGROUND: Traditional quantitative analysis of cartilage with MRI averages measurements (eg, thickness) across regions-of-interest (ROIs) which may reduce responsiveness.
PURPOSE: To validate and describe clinical application of a semiautomated surface-based method for analyzing cartilage relaxation times ("composition") and morphology on MRI, 3D cartilage surface mapping (3D-CaSM). STUDY TYPE: Validation study in cadaveric knees and prospective observational (cohort) study in human participants. POPULATION: Four cadaveric knees and 14 participants aged 40-60 with mild-moderate knee osteoarthritis (OA) and 6 age-matched healthy volunteers, imaged at baseline, 1, and 6 months. FIELD STRENGTH/SEQUENCE: 3D spoiled gradient echo, T1 rho/T2 magnetization-prepared 3D fast spin echo for mapping of T1 rho/T2 relaxation times and delayed gadolinium enhanced MRI of cartilage (dGEMRIC) using variable flip angle T1 relaxation time mapping at 3T. ASSESSMENT: 3D-CaSM was validated against high-resolution peripheral quantitative computed tomography (HRpQCT) in cadaveric knees, with comparison to expert manual segmentation. The clinical study assessed test-retest repeatability and sensitivity to change over 6 months for cartilage thickness and relaxation times. STATISTICAL TESTS: Bland-Altman analysis was performed for the validation study and evaluation of test-retest repeatability. Six-month changes were assessed via calculation of the percentage of each cartilage surface affected by areas of significant change (%SC), defined using thresholds based on area and smallest detectable difference (SDD).
RESULTS: Bias and precision (0.06 ± 0.25 mm) of 3D-CaSM against reference HRpQCT data were comparable to expert manual segmentation (-0.13 ± 0.26 mm). 3D-CaSM demonstrated significant (>SDD) 6-month changes in cartilage thickness and relaxation times in both OA participants and healthy controls. The parameter demonstrating the greatest 6-month change was T2 relaxation time (OA median %SC [IQR] = 8.8% [5.5 to 12.6]). DATA
CONCLUSION: This study demonstrates the construct validity and potential clinical utility of 3D-CaSM, which may offer advantages to conventional ROI-based methods. LEVEL OF EVIDENCE: 2. TECHNICAL EFFICACY STAGE: 2. J. Magn. Reson. Imaging 2020;52:1139-1151.
© 2020 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  3D; cartilage composition; cartilage mapping; cartilage thickness; knee osteoarthritis; magnetic resonance imaging

Year:  2020        PMID: 32447815     DOI: 10.1002/jmri.27193

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  6 in total

1.  Multiparametric 3-D analysis of bone and joint space width at the knee from weight bearing computed tomography.

Authors:  Tom D Turmezei; Samantha B Low; Simon Rupret; Graham M Treece; Andrew H Gee; James W MacKay; John A Lynch; Kenneth Es Poole; Neil A Segal
Journal:  Osteoarthr Imaging       Date:  2022-06-17

2.  The optimisation of deep neural networks for segmenting multiple knee joint tissues from MRIs.

Authors:  Dimitri A Kessler; James W MacKay; Victoria A Crowe; Frances M D Henson; Martin J Graves; Fiona J Gilbert; Joshua D Kaggie
Journal:  Comput Med Imaging Graph       Date:  2020-09-28       Impact factor: 4.790

3.  Knee joint distraction results in MRI cartilage thickness increase up to 10 years after treatment.

Authors:  Mylène P Jansen; Simon C Mastbergen; James W MacKay; Tom D Turmezei; Floris Lafeber
Journal:  Rheumatology (Oxford)       Date:  2022-03-02       Impact factor: 7.046

4.  An Expert-Supervised Registration Method for Multiparameter Description of the Knee Joint Using Serial Imaging.

Authors:  Hugo Babel; Patrick Omoumi; Killian Cosendey; Julien Stanovici; Hugues Cadas; Brigitte M Jolles; Julien Favre
Journal:  J Clin Med       Date:  2022-01-22       Impact factor: 4.241

5.  CT- and MRI-Based 3D Reconstruction of Knee Joint to Assess Cartilage and Bone.

Authors:  Federica Kiyomi Ciliberti; Lorena Guerrini; Arnar Evgeni Gunnarsson; Marco Recenti; Deborah Jacob; Vincenzo Cangiano; Yonatan Afework Tesfahunegn; Anna Sigríður Islind; Francesco Tortorella; Mariella Tsirilaki; Halldór Jónsson; Paolo Gargiulo; Romain Aubonnet
Journal:  Diagnostics (Basel)       Date:  2022-01-22

6.  Investigating acute changes in osteoarthritic cartilage by integrating biomechanics and statistical shape models of bone: data from the osteoarthritis initiative.

Authors:  Anthony A Gatti; Peter J Keir; Michael D Noseworthy; Monica R Maly
Journal:  MAGMA       Date:  2022-03-14       Impact factor: 2.533

  6 in total

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