TY - JOUR
T1 - Association of Thigh Muscle Strength with Texture Features Based on Proton Density Fat Fraction Maps Derived from Chemical Shift Encoding-Based Water-Fat MRI
AU - Dieckmeyer, Michael
AU - Inhuber, Stephanie
AU - Schläger, Sarah
AU - Weidlich, Dominik
AU - Mookiah, Muthu R. K.
AU - Subburaj, Karupppasamy
AU - Burian, Egon
AU - Sollmann, Nico
AU - Kirschke, Jan S.
AU - Karampinos, Dimitrios C.
AU - Baum, Thomas
N1 - Funding Information:
Funding: The present work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Project 432290010 (awarded to J.S.K. and T.B.). In addition, it was funded by the German Society of Musculoskeletal Radiology (Deutsche Gesellschaft für Muskuloskelettale Radiologie, DGMSR; awarded to N.S. and M.D.).
Funding Information:
The present work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Project 432290010 (awarded to J.S.K. and T.B.). In addition, it was funded by the German Society of Musculoskeletal Radiology (Deutsche Gesellschaft f?r Muskuloskelettale Radiologie, DGMSR; awarded to N.S. and M.D.).
Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/2/13
Y1 - 2021/2/13
N2 - Purpose: Based on conventional and quantitative magnetic resonance imaging (MRI), texture analysis (TA) has shown encouraging results as a biomarker for tissue structure. Chemical shift encoding-based water-fat MRI (CSE-MRI)-derived proton density fat fraction (PDFF) of thigh muscles has been associated with musculoskeletal, metabolic, and neuromuscular disorders and was demonstrated to predict muscle strength. The purpose of this study was to investigate PDFF-based TA of thigh muscles as a predictor of thigh muscle strength in comparison to mean PDFF.Methods: 30 healthy subjects (age = 30 ± 6 years; 15 females) underwent CSE-MRI of the lumbar spine at 3T, using a six-echo 3D spoiled gradient echo sequence. Quadriceps (EXT) and ischiocrural (FLEX) muscles were segmented to extract mean PDFF and texture features. Muscle flexion and extension strength were measured with an isokinetic dynamometer.Results: Of the eleven extracted texture features, Variance(global) showed the highest significant correlation with extension strength (p < 0.001, R2adj = 0.712), and Correlation showed the highest significant correlation with flexion strength (p = 0.016, R2adj = 0.658). Multivariate linear regression models identified Variance(global) and sex, but not PDFF, as significant predictors of extension strength (R2adj = 0.709; p < 0.001), while mean PDFF, sex, and BMI, but none of the texture features, were identified as significant predictors of flexion strength (R2adj = 0.674; p < 0.001).Conclusions: Prediction of quadriceps muscle strength can be improved beyond mean PDFF by means of TA, indicating the capability to quantify muscular fat infiltration patterns.
AB - Purpose: Based on conventional and quantitative magnetic resonance imaging (MRI), texture analysis (TA) has shown encouraging results as a biomarker for tissue structure. Chemical shift encoding-based water-fat MRI (CSE-MRI)-derived proton density fat fraction (PDFF) of thigh muscles has been associated with musculoskeletal, metabolic, and neuromuscular disorders and was demonstrated to predict muscle strength. The purpose of this study was to investigate PDFF-based TA of thigh muscles as a predictor of thigh muscle strength in comparison to mean PDFF.Methods: 30 healthy subjects (age = 30 ± 6 years; 15 females) underwent CSE-MRI of the lumbar spine at 3T, using a six-echo 3D spoiled gradient echo sequence. Quadriceps (EXT) and ischiocrural (FLEX) muscles were segmented to extract mean PDFF and texture features. Muscle flexion and extension strength were measured with an isokinetic dynamometer.Results: Of the eleven extracted texture features, Variance(global) showed the highest significant correlation with extension strength (p < 0.001, R2adj = 0.712), and Correlation showed the highest significant correlation with flexion strength (p = 0.016, R2adj = 0.658). Multivariate linear regression models identified Variance(global) and sex, but not PDFF, as significant predictors of extension strength (R2adj = 0.709; p < 0.001), while mean PDFF, sex, and BMI, but none of the texture features, were identified as significant predictors of flexion strength (R2adj = 0.674; p < 0.001).Conclusions: Prediction of quadriceps muscle strength can be improved beyond mean PDFF by means of TA, indicating the capability to quantify muscular fat infiltration patterns.
KW - Magnetic resonance imaging
KW - Muscle strength
KW - Proton density fat fraction
KW - Texture analysis
KW - Thigh muscles
UR - http://www.scopus.com/inward/record.url?scp=85108876948&partnerID=8YFLogxK
U2 - 10.3390/diagnostics11020302
DO - 10.3390/diagnostics11020302
M3 - Article
C2 - 33668624
SN - 2075-4418
VL - 11
JO - Diagnostics
JF - Diagnostics
IS - 2
M1 - 302
ER -