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 |
| Sumario: | 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. |
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