Intersession Repeatability of Diffusion-Tensor Imaging in the Supraspinatus and the Infraspinatus Muscles of Volunteers.

diffusion-tensor imaging elasticity imaging techniques magnetic resonance imaging rotator cuff shoulder

Journal

Journal of magnetic resonance imaging : JMRI
ISSN: 1522-2586
Titre abrégé: J Magn Reson Imaging
Pays: United States
ID NLM: 9105850

Informations de publication

Date de publication:
05 2023
Historique:
revised: 19 08 2022
received: 10 05 2022
accepted: 22 08 2022
medline: 7 4 2023
pubmed: 29 10 2022
entrez: 28 10 2022
Statut: ppublish

Résumé

Quantifying the rotator cuff (RC) muscles' viscoelasticity could provide outcome relevant information in patients with RC tears. MR-elastography requires robust diffusion-tensor imaging (DTI) to account for tissue anisotropy in muscles stiffness computation. To assess the repeatability of DTI parameters in the supraspinatus and infraspinatus muscles and to explore DTI tractography conformity with the muscles' anatomy. Prospective. Six healthy volunteers underwent three consecutive shoulder MRI sessions about 10 minutes apart. 3T/T1-vibe Dixon and Spin echo EPI DTI (12 gradient encoding directions, b-values 500 and 800 sec/mm Supraspinatus and infraspinatus muscles were segmented on the T1-vibe Dixon sequence. DTI image quality was assessed using a quantitative threshold based on the signal-to-noise ratio (SNR). The eigenvalues ( DTI parameters within-subject intersession repeatability was assessed with Bland-Altman analysis and the coefficient of variation (CV). Repeatability was considered good for CV < 10%. The SNR between diffusion-weighted and non-diffusion-weighted images was greater than 3, which aligns with standards for estimating DTI parameters. The FA showed the lowest mean bias (-0.007; 95% confidence interval [CI] -0.031 to 0.018) whereas the λ DTI of the supraspinatus and infraspinatus muscles achieved an adequate SNR, allowing the measurement of the DTI metrics with good repeatability, and thus can be used for optimizing stiffness estimation in these anisotropic tissues. 2 TECHNICAL EFFICACY: Stage 2.

Sections du résumé

BACKGROUND
Quantifying the rotator cuff (RC) muscles' viscoelasticity could provide outcome relevant information in patients with RC tears. MR-elastography requires robust diffusion-tensor imaging (DTI) to account for tissue anisotropy in muscles stiffness computation.
PURPOSE
To assess the repeatability of DTI parameters in the supraspinatus and infraspinatus muscles and to explore DTI tractography conformity with the muscles' anatomy.
STUDY TYPE
Prospective.
SUBJECTS
Six healthy volunteers underwent three consecutive shoulder MRI sessions about 10 minutes apart.
FIELD STRENGTH/SEQUENCE
3T/T1-vibe Dixon and Spin echo EPI DTI (12 gradient encoding directions, b-values 500 and 800 sec/mm
ASSESSMENT
Supraspinatus and infraspinatus muscles were segmented on the T1-vibe Dixon sequence. DTI image quality was assessed using a quantitative threshold based on the signal-to-noise ratio (SNR). The eigenvalues (
STATISTICAL TESTS
DTI parameters within-subject intersession repeatability was assessed with Bland-Altman analysis and the coefficient of variation (CV). Repeatability was considered good for CV < 10%.
RESULTS
The SNR between diffusion-weighted and non-diffusion-weighted images was greater than 3, which aligns with standards for estimating DTI parameters. The FA showed the lowest mean bias (-0.007; 95% confidence interval [CI] -0.031 to 0.018) whereas the λ
DATA CONCLUSION
DTI of the supraspinatus and infraspinatus muscles achieved an adequate SNR, allowing the measurement of the DTI metrics with good repeatability, and thus can be used for optimizing stiffness estimation in these anisotropic tissues.
EVIDENCE LEVEL
2 TECHNICAL EFFICACY: Stage 2.

Identifiants

pubmed: 36305562
doi: 10.1002/jmri.28424
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1414-1422

Informations de copyright

© 2022 International Society for Magnetic Resonance in Medicine.

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Auteurs

Cyril Tous (C)

Research Center, Centre hospitalier de l'Université de Montréal (CRCHUM), Montreal, Quebec, Canada.

Alexandre Jodoin (A)

Department of Radiology, Centre hospitalier de l'Université de Montréal (CHUM), Montreal, Quebec, Canada.

Detlev Grabs (D)

Department of Anatomy, Université du Québec à Trois-Rivières, Trois-Rivières, Quebec, Canada.

Elijah Van Houten (E)

Department of Mechanical Engineering, Université de Sherbrooke, Sherbrooke, Quebec, Canada.

Nathalie J Bureau (NJ)

Research Center, Centre hospitalier de l'Université de Montréal (CRCHUM), Montreal, Quebec, Canada.
Department of Radiology, Centre hospitalier de l'Université de Montréal (CHUM), Montreal, Quebec, Canada.

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