An accurate and robust method for unsupervised assessment of abdominal fat by MRI

Purpose To describe and evaluate an automatic and unsupervised method for assessing the quantity and distribution of abdominal adipose tissue by MRI. Material and Methods A total of 20 patients underwent whole‐abdomen MRI. A total of 32 transverse T1‐weighted images were acquired from each subject....

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Published in:Journal of magnetic resonance imaging Vol. 20; no. 4; pp. 684 - 689
Main Authors: Positano, Vincenzo, Gastaldelli, Amalia, Sironi, Anna maria, Santarelli, Maria Filomena, Lombardi, Massimo, Landini, Luigi
Format: Journal Article
Language:English
Published: Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.10.2004
Subjects:
abdomen
abdomen, MR studies
Abdominal Cavity - pathology
abdominal fat
Adipose Tissue - pathology
Anthropometry
fuzzy clustering
Fuzzy Logic
Humans
image processing
Image Processing, Computer-Assisted
Magnetic Resonance Imaging - methods
MR studies
Obesity - diagnosis
Reproducibility of Results
visceral fat
ISSN:1053-1807, 1522-2586
Online Access:Get full text
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Summary:Purpose To describe and evaluate an automatic and unsupervised method for assessing the quantity and distribution of abdominal adipose tissue by MRI. Material and Methods A total of 20 patients underwent whole‐abdomen MRI. A total of 32 transverse T1‐weighted images were acquired from each subject. The data collected were transferred to a dedicated workstation and analyzed by both our unsupervised method and a manual procedure. The proposed methodology allows the automatic processing of MRI axial images, segmenting the adipose tissue by fuzzy clustering approach. The use of an active contour algorithm on image masks provided by the fuzzy clustering algorithm allows the separation of subcutaneous fat from visceral fat. Finally, an automated procedure based on automatic image histogram analysis identifies the visceral fat. Results The accuracy, reproducibility, and speed of our automatic method were compared with the state‐of‐the‐art manual approach. The unsupervised analysis correlated well with the manual analysis, and was significantly faster than manual tracing. Moreover, the unsupervised method was not affected by intraobserver and interobserver variability. Conclusion The results obtained demonstrate that the proposed method can provide the volume of subcutaneous adipose tissue, visceral adipose tissue, global adipose tissue, and the ratio between subcutaneous and visceral fat in an unsupervised and effective manner. J. Magn. Reson. Imaging 2004;20:684–689. © 2004 Wiley‐Liss, Inc.
Bibliography:ArticleID:JMRI20167
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ISSN:1053-1807
1522-2586
DOI:10.1002/jmri.20167