Abdominal fat-water separation with SSFP at 3 Tesla

Area of Science:

• Magnetic Resonance Imaging
• Medical Physics
• Radiology

Background:

• Distinguishing between subcutaneous and visceral adipose tissue is crucial for metabolic health assessment.
• Accurate body fat quantification is important, especially in pediatric populations.
• Existing MRI techniques may have limitations in speed or ease of use for routine body composition analysis.

Purpose of the Study:

• To evaluate the efficacy of phase-sensitive steady-state free precession (SSFP) MRI at 3 Tesla for differentiating abdominal subcutaneous and visceral adipose tissue.
• To present a computationally efficient and robust postprocessing algorithm for automated fat and water separation.
• To assess the feasibility of this technique for in vivo body fat distribution quantification.

Main Methods:

• Utilized a 3 Tesla MRI scanner with a phased array receiver coil.
• Employed a commercially available SSFP pulse sequence for abdominal imaging.
• Developed and applied an automated postprocessing algorithm to generate separate fat-only and water-only images from raw SSFP data.

Main Results:

• The phase-sensitive SSFP technique successfully distinguished between subcutaneous and visceral adipose tissue.
• The presented postprocessing algorithm automatically separated fat and water pixels without user intervention.
• In vivo imaging demonstrated the feasibility of the technique with short breath-hold scans.

Conclusions:

• Phase-sensitive SSFP MRI at 3T is a viable method for abdominal adipose tissue characterization.
• The automated postprocessing offers an efficient and user-independent approach to fat-water separation.
• The technique's speed and simplicity make it suitable for pediatric body fat distribution quantification.