Validation of an active shape model-based semi-automated segmentation algorithm for the analysis of thigh muscle and adipose tissue cross-sectional areas

Objective To validate a semi-automated method for thigh muscle and adipose tissue cross-sectional area (CSA) segmentation from MRI. Materials and methods An active shape model (ASM) was trained using 113 MRI CSAs from the Osteoarthritis Initiative (OAI) and combined with an active contour model and...

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Vydáno v:Magma (New York, N.Y.) Ročník 30; číslo 5; s. 489 - 503
Hlavní autoři: Kemnitz, Jana, Eckstein, Felix, Culvenor, Adam G., Ruhdorfer, Anja, Dannhauer, Torben, Ring-Dimitriou, Susanne, Sänger, Alexandra M., Wirth, Wolfgang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2017
Témata:
Biomedical Engineering and Bioengineering
Computer Appl. in Life Sciences
Health Informatics
Imaging
Medicine
Medicine & Public Health
Radiology
Research Article
Solid State Physics
Statistical shape model
Thigh muscle
Segmentation
Magnetic resonance imaging
Training intervention
ISSN:0968-5243, 1352-8661, 1352-8661
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Shrnutí:Objective To validate a semi-automated method for thigh muscle and adipose tissue cross-sectional area (CSA) segmentation from MRI. Materials and methods An active shape model (ASM) was trained using 113 MRI CSAs from the Osteoarthritis Initiative (OAI) and combined with an active contour model and thresholding-based post-processing steps. This method was applied to 20 other MRIs from the OAI and to baseline and follow-up MRIs from a 12-week lower-limb strengthening or endurance training intervention ( n  = 35 females). The agreement of semi-automated vs. previous manual segmentation was assessed using the Dice similarity coefficient and Bland-Altman analyses. Longitudinal changes observed in the training intervention were compared between semi-automated and manual segmentations. Results High agreement was observed between manual and semi-automated segmentations for subcutaneous fat, quadriceps and hamstring CSAs. With strength training, both the semi-automated and manual segmentation method detected a significant reduction in adipose tissue CSA and a significant gain in quadriceps, hamstring and adductor CSAs. With endurance training, a significant reduction in adipose tissue CSAs was observed with both methods. Conclusion The semi-automated approach showed high agreement with manual segmentation of thigh muscle and adipose tissue CSAs and showed longitudinal training effects similar to that observed using manual segmentation.
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ISSN:0968-5243
1352-8661
1352-8661
DOI:10.1007/s10334-017-0622-3