To examine five available software packages for the assessment of abdominal adipose tissue with magnetic resonance imaging, compare their features and assess the reliability of measurement results.
Feature evaluation and test–retest reliability of softwares (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision) used in manual, semi-automated or automated segmentation of abdominal adipose tissue.
A random sample of 15 obese adults with type 2 diabetes.
Axial T1-weighted spin echo images centered at vertebral bodies of L2–L3 were acquired at 1.5 T. Five software packages were evaluated (NIHImage, SliceOmatic, Analyze, HippoFat and EasyVision), comparing manual, semi-automated and automated segmentation approaches. Images were segmented into cross-sectional area (CSA), and the areas of visceral (VAT) and subcutaneous adipose tissue (SAT). Ease of learning and use and the design of the graphical user interface (GUI) were rated. Intra-observer accuracy and agreement between the software packages were calculated using intra-class correlation. Intra-class correlation coefficient was used to obtain test–retest reliability.
Three of the five evaluated programs offered a semi-automated technique to segment the images based on histogram values or a user-defined threshold. One software package allowed manual delineation only. One fully automated program demonstrated the drawbacks of uncritical automated processing. The semi-automated approaches reduced variability and measurement error, and improved reproducibility. There was no significant difference in the intra-observer agreement in SAT and CSA. The VAT measurements showed significantly lower test–retest reliability. There were some differences between the software packages in qualitative aspects, such as user friendliness.
Four out of five packages provided essentially the same results with respect to the inter- and intra-rater reproducibility. Our results using SliceOmatic, Analyze or NIHImage were comparable and could be used interchangeably. Newly developed fully automated approaches should be compared to one of the examined software packages.
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The study was supported in part by NIH/NIDDK Grant RO1-DK060427 and UO1-DK57149. We thank Charlette Diggs, Project Coordinator for the Fatty Liver Ancillary Study, Kathleen Kahl and Terry Brawner, MR technicians, and the participants for their time and commitment.
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Bonekamp, S., Ghosh, P., Crawford, S. et al. Quantitative comparison and evaluation of software packages for assessment of abdominal adipose tissue distribution by magnetic resonance imaging. Int J Obes 32, 100–111 (2008). https://doi.org/10.1038/sj.ijo.0803696
- magnetic resonance imaging
- abdominal adipose tissue
- software evaluation
- image segmentation
- visceral adipose tissue
- subcutaneous adipose tissue
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