In AJR. American journal of roentgenology
Background: Hepatic attenuation at unenhanced CT is linearly correlated with MR proton density fat fraction (PDFF). Liver fat quantification at contrast-enhanced CT is more challenging. Objective: To evaluate liver steatosis categorization on contrast-enhanced CT using a fully-automated deep learning volumetric hepatosplenic segmentation algorithm and unenhanced CT as the reference standard. Materials and Methods: A fully-automated volumetric hepatosplenic segmentation algorithm using 3D convolutional neural networks was applied to unenhanced and contrast-enhanced series from a sample of 1204 healthy adults (mean age, 45.2 years; 726 women, 478 men) undergoing CT evaluation for renal donation. The mean volumetric attenuation was computed from all designated liver and spleen voxels. PDFF was estimated from unenhanced CT attenuation and served as the reference standard. Contrast-enhanced attenuations were evaluated for detecting PDFF thresholds of 5% (mild steatosis), 10%, and 15% (moderate); PDFF<5% was considered normal. Results: Using unenhanced CT as reference, estimated PDFF was ≥5% (mild steatosis), ≥10%, and ≥15% (moderate) in 50.1% (n=603), 12.5% (n=151) and 4.8% (n=58) of patients, respectively. ROC-AUC values for predicting PDFF thresholds of 5%, 10%, and 15% using contrast-enhanced liver attenuation were 0.669, 0.854, and 0.962, respectively, and using contrast-enhanced liver-spleen attenuation difference were 0.662, 0.866, and 0.986, respectively. A total of 96.8% (90/93) of patients with contrast-enhanced liver attenuation <90 HU had steatosis (PDFF≥5%); this <90 HU threshold achieved sensitivity 75.9% and specificity 95.7% for moderate steatosis (PDFF≥15%). Liver attenuation <100 HU achieved sensitivity 34.0% and specificity 94.2% for any steatosis (PDFF≥5%). A total of 93.8% (30/32) of patients with contrast-enhanced liver-spleen attenuation difference <-10 HU had moderate steatosis (PDFF≥15%); a liver-spleen difference <5 HU achieved sensitivity 91.4% and specificity 95.0% for moderate steatosis. Liver-spleen difference <10 HU achieved sensitivity 29.5% and specificity 95.5% for any steatosis (PDFF≥5%). Conclusion: Contrast-enhanced volumetric hepatosplenic attenuation derived using a fully-automated deep-learning CT tool may allow objective categorical assessment of hepatic steatosis. Accuracy was better for moderate than mild steatosis. Further confirmation using different scanning protocols and vendors is warranted. Clinical Impact: If these results are confirmed in independent patient samples, this automated approach could prove useful for both individualized and population-based steatosis assessment.
Pickhardt Perry J, Blake Glen M, Graffy Peter M, Sandfort Veit, Elton Daniel C, Perez Alberto A, Summers Ronald M