Affiliation:
1. Institute of Clinical Physiology National Research Council Pisa Italy
2. Department of Information Engineering and Computer Science University of Trento Trento Italy
3. Hepatology Unit Pisa University Hospital Pisa Italy
4. Fondazione Toscana Gabriele Monasterio Massa Italy
5. Department of Clinical and Experimental Medicine Pisa University Pisa Italy
6. Institute of Biostructure and Bioimaging National Research Council Naples Italy
7. Emergency Medicine Unit, Department of Clinical and Experimental Medicine University Hospital of Pisa Pisa Italy
Abstract
AbstractBackground & AimsThere is an unmet need for a reliable and reproducible non‐invasive measure of fatty liver content (FLC) for monitoring steatotic liver disease in clinical practice. Sonographic FLC assessment is qualitative and operator‐dependent, and the dynamic quantification range of algorithms based on a single ultrasound (US) parameter is unsatisfactory.This study aims to develop and validate a new multiparametric algorithm based on B‐mode images to quantify FLC using Magnetic Resonance (MR) values as standard reference.MethodsPatients with elevated liver enzymes and/or bright liver at US (N = 195) underwent FLC evaluation by MR and by US. Five US‐derived quantitative features [attenuation rate(AR), hepatic renal‐ratio(HR), diaphragm visualization(DV), hepatic‐portal‐vein‐ratio(HPV), portal‐vein‐wall(PVW)] were combined by mixed linear/exponential regression in a multiparametric model (Steatoscore2.0). One hundred and thirty‐four subjects were used for training and 61 for independent validations; score‐computation underwent an inter‐operator reproducibility analysis.ResultsThe model is based on a mixed linear/exponential combination of 3 US parameters (AR, HR, DV), modelled by 2 equations according to AR values. The computation of FLC by Steatoscore2.0 (mean ± std, 7.91% ± 8.69) and MR (mean ± std, 8.10% ± 10.31) is highly correlated with a low root mean square error in both training/validation cohorts, respectively (R = 0.92/0.86 and RMSE = 5.15/4.62, p < .001). Steatoscore2.0 identified patients with MR‐FLC≥5%/≥10% with sensitivity = 93.2%/89.4%, specificity = 86.1%/95.8%, AUROC = 0.958/0.975, respectively and correlated with MR (R = 0.92) significantly (p < .001) better than CAP (R = 0.73).ConclusionsMultiparametric Steatoscore2.0 measures FLC providing values highly comparable with MR. It is reliable, inexpensive, easy to use with any US equipment and qualifies to be tested in larger, prospective studies as new tool for the non‐invasive screening and monitoring of FLC.