Table 2.

Summary of CT studies for quantitative evaluation of hepatic steatosis

First author [Reference]	Number of patients	Methods	Reference standard	AUROC or positive and negative predictive value	Sensitivity	Specificity
Pickhardt [31]	1,204	Deep learning	MR-PDFF	Steatosis ≥ 5%: 0.669 Steatosis ≥ 10%: 0.854 Steatosis ≥ 15%: 0.962	Steatosis ≥ 5%: 34.0% Steatosis ≥ 15%:75.9%	Steatosis ≥ 5%: 94.2% Steatosis ≥ 10%: 95.7%
Guo [16]	400	QCT	MR-PDFF	Steatosis ≥ 5%: 0.87 Steatosis ≥ 14%: 0.99	Steatosis ≥ 5%:75.9% Steatosis ≥ 14%:84.8%	Steatosis ≥ 5%: 83.3% Steatosis ≥ 14%: 98.4%
Hyodo [32]	33	DECT FVF	Histologic	FVF discrimination between histologic grade 0 and grades 1–3: 0.88	Cut-off 4.6% for FVF: 82%	Cut-off 4.6% for FVF: 100%
Cao [33]	50	DECT MMD	Pathological	FVF correlated well with the pathological grades: 0.92	89.2%	100%
Zhang [34]	128	DECT VNC	MR-PDFF	Steatosis > 6%: 0.834 and 0.872 in the right and left lobe	57%/93.9% (right)	67.9%/90% (left)
Niehoff [35]	140	PCD-CT VNC	Previous reported cut-off values for diagnosing hepatic steatosis (CT (L) ≤ 40 HU, CT (L-S) ≤ -10 HU, CT (L/S) ≤ 0.8	PPV and NPV for the detection of hepatic steatosis: 30% and 99.5% When adjusting cut-off values: 41% and 99.6%	PPV and NPV: 94% When adjusting cut-off values: 94%	PPV and NPV: 87% When adjusting cut-off values: 92%

AUROC Area under the receiver operating characteristic curve, DECT Dual-energy computed tomography, FVF Fat volume fraction, HU Hounsfield units, MMD Multi-material decomposition, MR-PDFF Magnetic resonance imaging-derived proton density fat fraction, NPV Negative predictive value, PPV Positive predictive values, QCT Quantitative CT, VNC Virtual non-contrast