Literature DB >> 32634758

Fat quantification of the rotator cuff musculature using dual-energy CT-A pilot study.

Amanda M Baillargeon1, Francis I Baffour2, Lifeng Yu3, Joel G Fletcher4, Cynthia H McCollough5, Katrina N Glazebrook6.   

Abstract

PURPOSE: To assess the ability of dual-energy CT (DECT) as a novel technique to quantify the degree of rotator cuff fat degeneration.
METHOD: Clinically indicated shoulder CT exams for evaluation of osteoarthritis, rotator cuff arthropathy, pain or instability, or preoperative planning were acquired using dual-source CT systems. Rotator cuff DECT fat fraction after material decomposition was calculated off the sagittal image. Fat fractions were also assessed using CT numbers from dual energy virtual monochromatic images (70 keV) and single-energy CT (SECT) images (100 kV). Visual subjective Goutallier scores of the rotator cuff muscles were used as the reference standard.
RESULTS: 12 shoulders from 10 patients were analyzed, with bilateral shoulders evaluated in two patients (mean age 69 years (range 19-97)). Three patients were male and seven were female, with mean BMI of 32 (range 26-41). Mean fat fraction of the teres major and subcutaneous fat were, 2.9 % ± 4.0 % and 99.5 % ± 2.6 %, respectively, rendering these as reliable internal standards for 0% and 100 % fat. Mean DECT fat fractions of the rotator cuff were compared to Goutallier scores, revealing a high strength of rank correlation: ρ = 0.92, p < 0.0001. Mean fat fraction assessed with CT numbers also revealed high strengths of linear associations: ρ = 0.83, p < 0.0001 and ρ = 0.82, p < 0.0001, for DECT 70 keV and SECT 100 kV, respectively.
CONCLUSIONS: DECT direct fat fraction after material decomposition presents a novel approach to quantitative assessment of fatty degeneration, which has excellent correlation with clinically accepted standards.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Dual-energy CT; Fat quantification; Rotator cuff

Mesh:

Year:  2020        PMID: 32634758     DOI: 10.1016/j.ejrad.2020.109145

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  1 in total

1.  Fat Quantification in Dual-Layer Detector Spectral Computed Tomography: Experimental Development and First In-Patient Validation.

Authors:  Isabel Molwitz; Graeme Michael Campbell; Jin Yamamura; Tobias Knopp; Klaus Toedter; Roland Fischer; Zhiyue Jerry Wang; Alina Busch; Ann-Kathrin Ozga; Shuo Zhang; Thomas Lindner; Florian Sevecke; Mirco Grosser; Gerhard Adam; Patryk Szwargulski
Journal:  Invest Radiol       Date:  2022-02-11       Impact factor: 10.065

  1 in total

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