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Related Concept Videos

Computed Tomography01:10

Computed Tomography

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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
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Related Experiment Video

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Author Spotlight: A Non-Invasive Tool to Assess and Differentiate Fat Patterns in Liver Using 3D Dixon MRI
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Comparison of CT and Dixon MR Abdominal Adipose Tissue Quantification Using a Unified Computer-Assisted Software

Li-Yueh Hsu1, Zara Ali1, Hadi Bagheri1

  • 1Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Building 10, Room 1C370, 10 Center Drive, Bethesda, MA 20892, USA.

Tomography (Ann Arbor, Mich.)
|May 23, 2023
PubMed
Summary

This study demonstrates reliable quantification of abdominal fat distribution using computed tomography (CT) and magnetic resonance (MR) imaging. A unified software framework ensures excellent agreement for subcutaneous (SAT) and visceral (VAT) adipose tissue measurements.

Keywords:
abdominal adipose tissuecomputed tomographyfat quantificationimage segmentationmagnetic resonance imaging

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Area of Science:

  • Medical Imaging
  • Radiology
  • Obesity Research

Background:

  • Accurate abdominal fat quantification is crucial for assessing cardiometabolic disease risk.
  • Objective measures are needed across different imaging modalities.
  • Obesity-related health risks necessitate reliable diagnostic tools.

Purpose of the Study:

  • To compare quantitative measures of subcutaneous (SAT) and visceral (VAT) adipose tissues.
  • To evaluate abdominal fat distribution between computed tomography (CT) and Dixon-based magnetic resonance (MR) imaging.
  • To validate a unified computer-assisted software framework for fat quantification.

Main Methods:

  • 21 subjects underwent same-day abdominal CT and Dixon MR imaging.
  • Matched axial images at L2-L3 and L4-L5 levels were selected for fat quantification.
  • Automated software generated abdominal wall segmentation and SAT/VAT masks, with expert correction.

Main Results:

  • Excellent agreement was observed between CT and MR for abdominal wall segmentation (Pearson r=0.97).
  • High agreement was found for SAT (r=0.99) and VAT (r=0.97) quantification.
  • Bland-Altman analyses revealed minimal bias in all comparisons.

Conclusions:

  • Abdominal adipose tissue (SAT and VAT) can be reliably quantified using both CT and Dixon MR imaging.
  • A unified, user-friendly software framework supports fat measurement across modalities.
  • This framework facilitates diverse clinical research applications in obesity and cardiometabolic health.