Key result
An adaptive processing method using the valley between fat and nonfat distributions in the average histogram curve was judged best for measuring abdominal fat on T1-weighted MR images.
Why the study?
Do adaptive processing methods improve the measurement of abdominal fat cross-sectional area on T1-weighted MR images compared to existing methods?
Population
18 patients for method comparison, and 35 women (18 nonobese, 17 obese) for clinical utility illustration
Comparison
Adaptive processing methods for measuring… vs Existing MR imaging measurement method for…
Design
Cross-sectional
Authors
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May aid abdominal fat quantification on T1-weighted MRI; extends histogram methods but leaves open prospective validation.
Cross-Sectional (n=35)
Do adaptive processing methods improve the measurement of abdominal fat cross-sectional area on T1-weighted MR images compared to existing methods?
Adaptive processing methods using T1-weighted MR images provide effective and improved measurements of abdominal visceral and subcutaneous fat cross-sectional areas for both research and clinical applications.
Lancaster et al. (1991) conducted a cross-sectional in Abdominal fat / Obesity (n=35). Adaptive processing methods for MR imaging vs. Existing MR imaging measurement method was evaluated on Measurement of abdominal fat cross-sectional area. An adaptive processing method using the valley between fat and nonfat distributions in the average histogram curve was judged best for measuring abdominal fat on T1-weighted MR images.
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