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

Jana Kemnitz,Alexandra M Sänger,Anja Ruhdorfer,Felix Eckstein,Torben Dannhauer,Wolfgang Wirth,Adam G Culvenor,Susanne Ring-Dimitriou

doi:10.1007/s10334-017-0622-3

Abstract

ObjectiveTo validate a semi-automated method for thigh muscle and adipose tissue cross-sectional area (CSA) segmentation from MRI.Materials and methodsAn 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.ResultsHigh 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.ConclusionThe 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.

Highlights

Deficits in thigh muscle strength are known to be associated with knee pain and functional limitations [1, 2] and to increase the risk of both incident knee osteoarthritis (OA) [3,4,5] and knee replacement surgery [6]
Magnetic resonance imaging (MRI) permits visualization of thigh muscle cross-sectional areas (CSA) directly, with CSAs being correlated with clinical measures of muscle strength [10, 11]
Notable systematic deviations between the semi-automated and the manual segmentation methods were observed for the sartorius (−0.1 cm2/−4.2%) and IMF CSAs (+4.6 cm2/+38.1%) (Fig. 8)

Summary

Introduction

Deficits in thigh muscle strength are known to be associated with knee pain and functional limitations [1, 2] and to increase the risk of both incident knee osteoarthritis (OA) [3,4,5] and knee replacement surgery [6]. Measurements of muscle strength are clinically useful, but depend on the willingness of the study participants to exert maximal possible effort, and are potentially biased by the presence of pain [9]. Magnetic resonance imaging (MRI) permits visualization of thigh muscle cross-sectional areas (CSA) directly, with CSAs being correlated with clinical measures of muscle strength [10, 11]. A comparative study has shown that thigh muscle CSAs are more sensitive to longitudinal change in knee OA than isometric muscle strength measures [12]. MRI is able to directly depict thigh adipose tissue. It is able to detect subtle variations in both muscle morphometry and thigh tissue composition

Methods

Results

Discussion

Conclusion