ArticleSkeletal radiology2019
Quantification of shoulder muscle intramuscular fatty infiltration on T1-weighted MRI: a viable alternative to the Goutallier classification system.
Article in Skeletal radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
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Who cites it
30 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.
- Automatability and validity of methods for the quantification of intra-/Intermuscular adipose tissue in conventional MRI: a systematic review.BMC medical imaging · 2025Pooled it
- Validation of Three-Dimensional Magnetic Resonance Imaging-Based Volumetric Quantification for Fatty Infiltration in a Rabbit Model of Chronic Rotator Cuff Tears.Diagnostics (Basel, Switzerland) · 2026Article
- Lumbar MRI-Based Deep Learning for Osteoporosis Prediction.Diagnostics (Basel, Switzerland) · 2026Article
- Developing a three-dimensional convolutional neural network for automated full-volume multi-tissue segmentation of the shoulder with comparisons to Goutallier classification and partial volume muscle quality analysis.Journal of shoulder and elbow surgery · 2025Article
- Hypogonadism is associated with worse outcomes in arthroscopic rotator cuff repair.JSES international · 2025Article
- Fat Expansion Not Fat Infiltration of Muscle Post Rotator Cuff Tendon Tears of the Shoulder: Regenerative Engineering Implications.Regenerative engineering and translational medicine · 2025Article
- Single slice MR image estimation of 3D supraspinatus intramuscular fatty infiltration in older adults: relevance for clinical practice and research.Skeletal radiology · 2025Article
- Fully-automated segmentation of muscle and inter-/intra-muscular fat from magnetic resonance images of calves and thighs: an open-source workflow in Python.Skeletal muscle · 2024Article
- Myosteatosis: diagnostic significance and assessment by imaging approaches.Quantitative imaging in medicine and surgery · 2024Review
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- Fat quantification of the rotator cuff muscles using CT histogram analysis in comparison with Dixon MRI sequence.The British journal of radiology · 2023Article
- Estimating 3D supraspinatus intramuscular fatty infiltration in older adults: a pilot study.Acta radiologica (Stockholm, Sweden : 1987) · 2023Article
- Gluteal muscle fatty infiltration, fall risk, and mobility limitation in older women with urinary incontinence: a pilot study.Skeletal radiology · 2023Article
- Shoulder Dysfunction and Mobility Limitation in Aging.Advances in geriatric medicine and research · 2023Article
- Ultrasound and magnetic resonance imaging as diagnostic tools for sarcopenia in immune-mediated rheumatic diseases (IMRDs).La Radiologia medica · 2022Review
- Automatic MRI segmentation of pectoralis major muscle using deep learning.Scientific reports · 2022Article
- Relationship between preoperative size of rotator cuff tears measured using radial-slice magnetic resonance images and postoperative rotator cuff integrity: a prospective case-control study.JSES international · 2022Article
- Supraspinatus fatty infiltration on MRI among older adults receiving physical therapy as initial management for clinically suspected rotator cuff tear: A pilot study.Journal of clinical imaging science · 2022Article
- Changes in Muscle Volume and Composition After Treatment of Hip Dysplasia with Periacetabular Osteotomy.The Iowa orthopaedic journal · 2021Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundQuantification 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
methodsWe 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.
resultsWe 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.
conclusionQuantification 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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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.