Original Article

International Journal of Obesity (2008) 32, 100–111; doi:10.1038/sj.ijo.0803696; published online 14 August 2007

Quantitative comparison and evaluation of software packages for assessment of abdominal adipose tissue distribution by magnetic resonance imaging

S Bonekamp1, P Ghosh2, S Crawford3, S F Solga4, A Horska5, F L Brancati6, A M Diehl7, S Smith8 and J M Clark3,6

  1. 1Russel H Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
  2. 2The Johns Hopkins University School of Medicine, Baltimore, MD, USA
  3. 3Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
  4. 4Division of Gastroenterology and Hepatology, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
  5. 5Division of Neuroradiology, Russel H Morgan, Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
  6. 6Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
  7. 7Division of Gastroenterology, Duke University Medical Center, Durham, NC, USA
  8. 8Pennington Biomedical Research Center, Baton Rouge, LA, USA

Correspondence: Dr S Bonekamp, Russel H Morgan Department of Radiology and Radiological Science, Division of Medical Imaging Physics, Johns Hopkins Medical Institutions, 601 N Caroline Street, JHOC 4253, Baltimore, MD 21287, USA. E-mail: shemker2@jhmi.edu

Received 23 January 2007; Revised 17 May 2007; Accepted 25 May 2007; Published online 14 August 2007.

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Abstract

Objective:

 

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.

Design:

 

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.

Subjects:

 

A random sample of 15 obese adults with type 2 diabetes.

Measurements:

 

Axial T1-weighted spin echo images centered at vertebral bodies of L2–L3 were acquired at 1.5T. 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.

Results:

 

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.

Conclusion:

 

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.

Keywords:

magnetic resonance imaging, abdominal adipose tissue, software evaluation, image segmentation, visceral adipose tissue, subcutaneous adipose tissue

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