Quantitative measurements of muscle degeneration in volumetric shoulder muscle models
- Authors
- Hong, Ki-Taek; Lee, Dokwan; Shin, Choongsoo; Choi, Jung-Ah; Song, Yongnam
- Issue Date
- 10월-2017
- Publisher
- KOREAN SOC PRECISION ENG
- Keywords
- 3D modeling; Biomechanics; Image post-processing; Muscle degeneration; MRI; Shoulder
- Citation
- INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING, v.18, no.10, pp.1449 - 1454
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING
- Volume
- 18
- Number
- 10
- Start Page
- 1449
- End Page
- 1454
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/82045
- DOI
- 10.1007/s12541-017-0172-7
- ISSN
- 2234-7593
- Abstract
- Qualitative image-based Goutallier grading system is popular to examine fatty degeneration of shoulder muscles, but may not provide consistent results to describe the true status of the muscles due to observer-dependent variabilities and limitations of using one cross-sectional image. We calculated occupation ratio (ratio between the supraspinatus muscle and the fossa), single-image and volumetric fat contents to quantitatively describe the degree of muscle atrophy and fatty infiltration in the supraspinatus muscle and compared them with conventional Goutallier grading system. We retrospectively examined the MR images of 33 symptomatic patients. Significant differences were found in the occupation ratio (p < 0.01, Kruskall-Wallis H test) and volumetric fat contents (p < 0.05) among different grading groups while no differences were found in single-image fat contents. Correlations of the occupation ratio with single-image and volumetric fat contents were found to be moderate suggesting that muscle atrophy and fatty infiltration might be independent factors. Quantitative measurements of occupation ratio and threshold-based volumetric fat contents may be useful to provide consistent information describing both atrophy and fatty infiltration of the supraspinatus muscle which are important predictors of degenerative muscles.
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Collections - College of Engineering > Department of Mechanical Engineering > 1. Journal Articles
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