A reproducible semi-automatic method to quantify the muscle-lipid distribution in clinical 3D CT images of the thigh

Mühlberg A, Museyko O, Laredo JD, Engelke K (2017)


Publication Type: Journal article

Publication year: 2017

Journal

Book Volume: 12

Journal Issue: 4

DOI: 10.1371/journal.pone.0175174

Abstract

Many studies use threshold-based techniques to assess in vivo the muscle, bone and adipose tissue distribution of the legs using computed tomography (CT) imaging. More advanced techniques divide the legs into subcutaneous adipose tissue (SAT), anatomical muscle (muscle tissue and adipocytes within the muscle border) and intra- and perimuscular adipose tissue. In addition, a so-called muscle density directly derived from the CT-values is often measured. We introduce a new integrated approach to quantify the muscle-lipid system (MLS) using quantitative CT in patients with sarcopenia or osteoporosis. The analysis targets the thigh as many CT studies of the hip do not include entire legs The framework consists of an anatomic coordinate system, allowing delineation of reproducible volumes of interest, a robust semi-automatic 3D segmentation of the fascia and a comprehensive method to quantify of the muscle and lipid distribution within the fascia. CT density-dependent features are calibrated using subject-specific internal CT values of the SAT and external CT values of an in scan calibration phantom. Robustness of the framework with respect to operator interaction, image noise and calibration was evaluated. Specifically, the impact of inter- and intra-operator reanalysis precision and addition of Gaussian noise to simulate lower radiation exposure on muscle and AT volumes, muscle density and 3D texture features quantifying MLS within the fascia, were analyzed. Existing data of 25 subjects (age: 75.6 ± 8.7) with porous and low-contrast muscle structures were included in the analysis. Intra- and inter-operator reanalysis precision errors were below 1% and mostly comparable to 1% of cohort variation of the corresponding features. Doubling the noise changed most 3D texture features by up to 15% of the cohort variation but did not affect density and volume measurements. The application of the novel technique is easy with acceptable processing time. It can thus be employed for a comprehensive quantification of the muscle-lipid system enabling radiomics approaches to musculoskeletal disorders.

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How to cite

APA:

Mühlberg, A., Museyko, O., Laredo, J.-D., & Engelke, K. (2017). A reproducible semi-automatic method to quantify the muscle-lipid distribution in clinical 3D CT images of the thigh. PLoS ONE, 12(4). https://dx.doi.org/10.1371/journal.pone.0175174

MLA:

Mühlberg, Alexander, et al. "A reproducible semi-automatic method to quantify the muscle-lipid distribution in clinical 3D CT images of the thigh." PLoS ONE 12.4 (2017).

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