Table 1.
Characteristics in 82 patients.
Fig 1.
Examples of histopathology-proven steatosis grades.
From left to right with histopathology-proven steatosis grades: 1) 62-year-old man with hepatitis B virus with steatosis grade 0; 2) 62-year-old man with NASH and hepatitis B virus with steatosis grade S1; 3) 38-year-old man with NASH with steatosis grade S2; and 4) 69-year-old woman with NASH with steatosis grade S3. Displayed images: (A) Representative B-mode acquired in the right liver lobe and corresponding QUS parametric maps (zoomed in on ROIs) illustrating (B) reciprocal of scatterer clustering parameter (log scale), (C) coherent-to-diffuse signal ratio, and (D) diffuse-to-total signal power ratio. Yellow indicates higher values, whilst dark blue values indicate lower values. In the table are reported the inflammation grade and the fibrosis stage, as well as the corresponding point shear wave elasticity (pSWE), and local and total attenuation coefficient slopes (ACS).
Fig 2.
Examples of point shear wave elastography (pSWE) measurements.
pSWE measurements in 4 different patients: (A) steatosis grade S0, (B) steatosis grade S1, (C) steatosis grade S2, and (D) steatosis grade S3. Green rectangles indicate regions of interest where measurements are performed.
Fig 3.
Flow chart of the post-processing pipeline.
(A) Clinical examination, recruitment with signed informed consent, research data acquisitions, biopsy and histology. (B) Calculation of the echo envelope of radiofrequency (RF) cineloops, manual delineation of a region-of-interest (ROI) contours in one frame, and propagation of contours along all frames of the cineloop. (C) Calculation of quantitative ultrasound (QUS) features. (D) Machine learning with random forests based on 11 features and gold standards: selection of 10 combinations of 4 features or less with highest G-mean (features selection), calculation of AUC-ROC on these combinations (0.632+ bootstrap), and estimation of the 95% CI for the features combination with highest AUC-ROC.
Fig 4.
Examples of histopathology slides.
Hematoxylin and eosin-stained images (10x magnification) in 4 different patients corresponding to those shown in Fig 1 above: (A) steatosis grade S0, (B) steatosis grade S1, (C) steatosis grade S2, and (D) steatosis grade S3. Representative vacuoles of macrovesicular steatosis are indicated by arrows.
Table 2.
Accuracy of shear wave elasticity alone and in combination with quantitative ultrasound (QUS) features for classification of steatosis, inflammation, and fibrosis.
Fig 5.
Receiver operating characteristic (ROC) curves.
ROC curves obtained with elastography (dashed lines) and the combinations of QUS and elasticity features (solid lines) with highest AUC-ROC for the classification of (A) steatosis grade S0 vs. S1-3, S0-1 vs. S2-3, S0-2 vs. S3, (B) inflammation grade A0 vs. A1-3, A0-1 vs. A2-3, A0-2 vs. A3, and (C) fibrosis stage F0 vs. F1-4, F0-1 vs. F2-4, F0-2 vs. F3-4, F0-3 vs. F4. Sensitivity and specificity at optimal Youden index are displayed for each ROC curve.
Table 3.
Coefficients (with 95% confidence intervals in parentheses) of ordinal logistic regressions with the steatosis grade, or the inflammation grade, or the fibrosis stage as responses, and with features appearing in Table 1, as single predictors.