Hepatic fat quantification in dual-layer computed tomography using a three-material decomposition algorithm.

Area of Science:

• Radiology
• Medical Imaging
• Hepatology

Background:

• Hepatic steatosis, or fatty liver disease, is a growing health concern.
• Accurate quantification of liver fat is crucial for diagnosis and management.
• Magnetic Resonance Imaging (MRI) is a reference standard but can be costly and time-consuming.

Purpose of the Study:

• To evaluate a novel three-material decomposition algorithm for hepatic fat quantification using dual-layer computed tomography (DL-CT).
• To compare DL-CT derived fat fraction with MRI reference standard in a large patient cohort.
• To assess the diagnostic performance of DL-CT for detecting hepatic steatosis.

Main Methods:

• Retrospective analysis of 104 patients with both MRI and DL-CT exams.
• Blind positioning of regions of interest (ROIs) in the liver by two independent readers.
• Analysis of fat fraction agreement using intraclass correlation coefficients (ICC), R², and Bland-Altman plots.
• Calculation of sensitivity, specificity, and predictive values for steatosis detection (≥5% fat).

Main Results:

• Excellent correlation between DL-CT and MRI for hepatic fat fraction (ICC=0.99, R²≈0.95) across all perfusion phases.
• Good diagnostic performance for hepatic steatosis detection: sensitivity 89-91%, specificity 75-80%.
• Positive predictive values ranged from 78-93%, and negative predictive values from 82-86%.

Conclusions:

• The three-material decomposition algorithm in DL-CT provides reliable hepatic fat quantification, correlating well with MRI.
• DL-CT is accurate for detecting hepatic steatosis (≥5% fat).
• DL-CT facilitates opportunistic detection of hepatic steatosis during scans for other indications, enabling early intervention for metabolic liver disease.