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MR Imaging-Based Biomarkers for Strength Prediction: A Statistical Shape and Architecture Modeling of Quadriceps
Salim Bin Ghouth1, Ozkan Cigdem1, Valentina Mazzoli1
1Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University, New York, New York, USA.
Background:
Muscle mass decline, associated with strength decline, is a hallmark of aging. Yet, strength decline greatly exceeds mass decline. This indicates that aspects of muscle quality and architecture-not reflected by mass-also influence force generating capacity. Additionally, shape modeling enables analysis of the shape variations of muscles beyond size.
Purpose:
To predict muscle strength using muscle features beyond muscle quantity.
Study Type:
Retrospective cross-sectional study.
Population:
Twenty-four healthy subjects normally distributed over an age range between 30 and 79 years old with a balanced sex distribution (12 female).
Field Strength/Sequence:
3 T MRI using multi-echo Dixon and Stejskal-Tanner DTI.
Assessment:
Shape-only and shape + architecture models were generated using water-only and DTI images of the quadriceps. Multiple linear mixed-effects models were produced using (1) volume, (2) shape-only, and (3) shape + architecture. Volume was not added to the shape-only and shape + architecture models. Features reaching statistical significance within the models were retained for further analysis. Models' performance was evaluated using leave-one-subject-out (LOSO) cross-validation (CV).
Statistical Tests:
Pairwise, subject-level bootstrapping comparison was conducted and ∆R 2 and ∆RMSE with 95% confidence interval (CI) were calculated. The improvement was considered statistically significant when both ∆R 2 and ∆RMSE are positive and the 95% CI did not contain zero. Positive ∆R 2 and ∆RMSE indicate an increase in R 2 and a decrease in RMSE values.
Results:
Shape-only features demonstrated an improvement in the model performance compared to muscle volume. Models were significantly improved for the vastus lateralis to predict eccentric torque-∆R 2 = 0.16 (0.01-0.29), ∆RMSE = 5.0 (0.4-9.7); and for the vastus intermedius predicting isometric torque-∆R 2 = 0.19 (0.02-0.36), ∆RMSE = 6.5 (0.7-12.0). Shape + architecture features did not significantly improve the performance (all p ≥ 0.131).
Data Conclusion:
Shape-only models are promising to quantify variations of muscle shape related to force production, and have the potential to develop imaging-based biomarkers for muscle strength in diseases.
Evidence Level:
3.
Technical Efficacy:
Stage 2.
