Software for automated MRI‐based quantification of abdominal fat and preliminary evaluation in morbidly obese patients

To present software for supervised automatic quantification of visceral and subcutaneous adipose tissue (VAT, SAT) and evaluates its performance in terms of reliability, interobserver variation, and processing time, since fully automatic segmentation of fat‐fraction magnetic resonance imaging (MRI) is fast but susceptible to anatomical variations and artifacts, particularly for advanced stages of obesity.

[1]  Y. Miyazaki,et al.  Visceral fat dominant distribution in male type 2 diabetic patients is closely related to hepatic insulin resistance, irrespective of body type , 2009, Cardiovascular diabetology.

[2]  Peter Börnert,et al.  Automated assessment of whole‐body adipose tissue depots from continuously moving bed MRI: A feasibility study , 2009, Journal of magnetic resonance imaging : JMRI.

[3]  Hans Frimmel,et al.  Whole‐body T1 mapping improves the definition of adipose tissue: Consequences for automated image analysis , 2006, Journal of magnetic resonance imaging : JMRI.

[4]  W E Reddick,et al.  Fast adipose tissue (FAT) assessment by MRI. , 2000, Magnetic resonance imaging.

[5]  J. Kullberg,et al.  Automated and reproducible segmentation of visceral and subcutaneous adipose tissue from abdominal MRI , 2007, International Journal of Obesity.

[6]  R. Sturm,et al.  Increases in morbid obesity in the USA: 2000-2005. , 2007, Public health.

[7]  Bostjan Likar,et al.  A Review of Methods for Correction of Intensity Inhomogeneity in MRI , 2007, IEEE Transactions on Medical Imaging.

[8]  Jayaram K. Udupa,et al.  Iterative relative fuzzy connectedness for multiple objects with multiple seeds , 2007, Comput. Vis. Image Underst..

[9]  Luigi Landini,et al.  An accurate and robust method for unsupervised assessment of abdominal fat by MRI , 2004, Journal of magnetic resonance imaging : JMRI.

[10]  Fritz Schick,et al.  Follow-up whole-body assessment of adipose tissue compartments during a lifestyle intervention in a large cohort at increased risk for type 2 diabetes. , 2010, Radiology.

[11]  B. Wajchenberg.  Subcutaneous and visceral adipose tissue: their relation to the metabolic syndrome. , 2000, Endocrine reviews.

[12]  J. Seidell,et al.  Reproducibility of fat area measurements in young, non-obese subjects by computerized analysis of magnetic resonance images , 1997, International Journal of Obesity.

[13]  Luigi Landini,et al.  Automatic correction of intensity inhomogeneities improves unsupervised assessment of abdominal fat by MRI , 2008, Journal of magnetic resonance imaging : JMRI.

[14]  S. Sauerland,et al.  Evidence-based German guidelines for surgery for obesity , 2011, International Journal of Colorectal Disease.

[15]  P. Weatherall,et al.  Water‐saturated three‐dimensional balanced steady‐state free precession for fast abdominal fat quantification , 2005, Journal of magnetic resonance imaging : JMRI.

[16]  L O Hall,et al.  Review of MR image segmentation techniques using pattern recognition. , 1993, Medical physics.

[17]  A. Prentice,et al.  Beyond body mass index , 2001, Obesity reviews : an official journal of the International Association for the Study of Obesity.

[18]  L. Lönn,et al.  Whole-body adipose tissue analysis: comparison of MRI, CT and dual energy X-ray absorptiometry. , 2009, The British journal of radiology.

[19]  Scott K Holland,et al.  Using a phantom to compare MR techniques for determining the ratio of intraabdominal to subcutaneous adipose tissue. , 2003, AJR. American journal of roentgenology.

[20]  Enzo Bonora,et al.  Measurement of abdominal fat with T1‐weighted MR images , 1991, Journal of magnetic resonance imaging : JMRI.

[21]  A. Horská,et al.  Quantitative comparison and evaluation of software packages for assessment of abdominal adipose tissue distribution by magnetic resonance imaging , 2008, International Journal of Obesity.

[22]  F. Schick,et al.  Standardized assessment of whole body adipose tissue topography by MRI , 2005, Journal of magnetic resonance imaging : JMRI.