Quantification of shoulder muscle intramuscular fatty infiltration on T1-weighted MRI: a viable alternative to the Goutallier classification system.
Background: Quantification of rotator cuff intramuscular fatty infiltration is important for clinical decision-making in patients with rotator cuff tear. The semi-quantitative Goutallier classification system is the most commonly used method, but has limited reliability. Therefore, we sought to test...
| Publicado en: | Skeletal Radiology Vol. 48; no. 4; pp. 535 - 542 |
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| Autores principales: | , , , , , , |
| Formato: | diagnostic images research tables/charts Journal Article |
| Publicado: |
Springer Nature
Apr2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=134766285&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 134766285 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 03642348 O14 jtl: Skeletal Radiology issn: 03642348 maglogo: N pubinfo: dt: Apr2019 vid: 48 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 134766285 134766285 NLM30203182 134766285 10.1007/s00256-018-3057-7 NLM30203182 134766285 ppf: 535 ppct: 7 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Quantification of shoulder muscle intramuscular fatty infiltration on T1-weighted MRI: a viable alternative to the Goutallier classification system. aug: au: Davis, Derik L. Kesler, Thomas Gilotra, Mohit N. Almardawi, Ranyah Hasan, Syed A. Gullapalli, Rao P. Zhuo, Jiachen affil: Department of Diagnostic Radiology & Nuclear Medicine, University of Maryland School of Medicine, 22 S. Greene Street, 21201, Baltimore, MD, USA sug: subj: Rotator Cuff Adipose Tissue Magnetic Resonance Imaging Methods Rotator Cuff Pathology Prospective Studies Middle Age Male Adipose Tissue Pathology Cross Sectional Studies Adult Female Reproducibility of Results Aged Software Human Middle Aged: 45-64 years Adult: 19-44 years Aged: 65+ years Male Female ab: Background: Quantification of rotator cuff intramuscular fatty infiltration is important for clinical decision-making in patients with rotator cuff tear. The semi-quantitative Goutallier classification system is the most commonly used method, but has limited reliability. Therefore, we sought to test a freely available fuzzy C-means segmentation software program for reliability of the quantification of shoulder intramuscular fatty infiltration on T1-weighted MR images and for correlation with fat fraction by six-point Dixon MRI.Materials and Methods: We performed a prospective cross-sectional study to measure visible intramuscular fat area percentage on oblique sagittal T1 MR images by fuzzy C-means segmentation and fat fraction maps by six-point Dixon MRI for 42 shoulder muscles. Intra- and inter-observer reliability were determined. Correlative analysis for fuzzy C-means and six-point Dixon intramuscular fatty infiltration measures was also performed.Results: We found that inter-observer reliability for the quantification of visible intramuscular fat area percentage by fuzzy C-means segmentation and fat fraction by six-point Dixon MRI was 0.947 and 0.951 respectively. The intra-observer reliability for the quantification of visible intramuscular fat area percentage by fuzzy C-means segmentation and fat fraction by six-point Dixon MRI was 0.871 and 0.979 respectively. We found a strong correlation between fuzzy C-means segmentation and six-point Dixon techniques; r = 0.850, p < 0.001 by individual muscle; and r = 0.977, p < 0.002 by study subject.Conclusion: Quantification of intramuscular fatty infiltration by fuzzy C-means segmentation on T1-weighted sequences demonstrates excellent reliability and strong correlation with fat fraction by six-point Dixon MRI. Quantitative fuzzy C-means segmentation is a viable alternative to the semi-quantitative Goutallier classification system. pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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