Steato-Score: Non-Invasive Quantitative Assessment of Liver Fat by Ultrasound Imaging

Lascio, Nicole Di; Avigo, Cinzia; Salvati, A; Mondaini, Nicola; Ragucci, Monica; Monti, Serena; Prinster, Anna; Chiappino, Dante; Mancini, Marcello; Delia, Domenico; Ghiadoni, Lorenzo; Bonino, Ferruccio; Brunetto, M.R.; Faita, Francesco

doi:10.1016/j.ultrasmedbio.2018.03.011

Cited by 20 publications

(24 citation statements)

References 45 publications

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“…Moreover, the presence of steatosis has been reported to be associated with faster fibrosis progression or significant fibrosis burden in patients with CHC or CHB [7][8][9][10]. Therefore, an easy-to-use tool that can diagnose hepatic steatosis via simple, noninvasive evaluation of liver fat content in different clinical settings would be beneficial for the identification of asymptomatic high-risk patients and the evaluation of response to therapy or disease progression [11].…”

Section: Introductionmentioning

confidence: 99%

Reproducibility of ultrasound attenuation imaging for the noninvasive evaluation of hepatic steatosis

et al. 2020

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Purpose: The purpose of this study was to evaluate the intra-observer reproducibility of ultrasound attenuation imaging (ATI) for the noninvasive assessment of hepatic steatosis in patients with suspected hepatic steatosis and the inter-observer reproducibility in asymptomatic volunteers. Methods: This prospective study was approved by our institutional review board and informed consent was obtained from all patients. In group 1, composed of patients with suspected hepatic steatosis (n=143), one abdominal radiologist performed gray-scale ultrasonography and two sessions of ATI. In group 2, composed of healthy volunteers (n=18), three independent sessions of ATI were performed by three abdominal radiologists. The visual degree of hepatic steatosis in all study subjects was graded on a 4-point scale by two independent reviewers using gray-scale ultrasonography. Thereafter, the attenuation coefficient (AC) was correlated with the degree of hepatic steatosis using Spearman rank correlation analysis. Intra-class correlation coefficients (ICCs) were used to assess the intra-observer (group 1) and inter-observer reproducibility (group 2) of ATI measurements. Results: For the intra-observer reproducibility of ATI, the ICC was 0.929 (95% confidence interval [CI], 0.901 to 0.949), and the coefficient of variation was 7.1%. Inter-observer reproducibility of ATI measurements showed an ICC of 0.792 (95% CI, 0.549 to 0.916). The AC showed a significant correlation with the visual grade of hepatic steatosis for both reviewers (rho, 0.780 and 0.695; P<0.001, respectively). Conclusion: ATI showed high intra-and inter-observer reproducibility in the assessment of hepatic steatosis.

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Section: Introductionmentioning

confidence: 99%

Reproducibility of ultrasound attenuation imaging for the noninvasive evaluation of hepatic steatosis

et al. 2020

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“…There is now a trend to adopting multi-parametric strategies to better assess steatosis quantitatively. One such approach is based on the acquisition of common scan projections (both subcostal longitudinal and oblique views) available with commercial US systems[ 65 ]. Two recordings (clips of 5 s) allow the quantification of 5 different parameters associated with intrahepatic fat accumulation (Figure 1 ).…”

Section: Intrahepatic Fat Measured By Ultrasoundmentioning

confidence: 99%

“…In addition, the attenuation rate (AR) takes into account the reduction of US beam penetration[ 61 ], while grades are assigned to diaphragm visualization (DV, assessing the degree of diaphragm line visualization) and portal vein wall visualization (PVW visual , assessing blurring of the portal vein walls). An algorithm (Steato-score) combining these five parameters showed good diagnostic performance discriminating presence (≥ 5%) or absence (< 5%) of steatosis relative to 1 H-MRS with an area under the receiving operator characteristic (ROC) curve of 0.98 and roughly 90% specificity and sensitivity[ 65 ].…”

Section: Intrahepatic Fat Measured By Ultrasoundmentioning

confidence: 99%

“… Quantitative multi-parametric assessment of intrahepatic fat by ultrasound. Workflow of the image acquisition, processing and data elaboration leading to a score provided by an algorithm (Steato-score)[ 65 ]. US: Ultrasound; AR: Attenuation rate; DV: Diaphragm visualization.…”

Section: Intrahepatic Fat Measured By Ultrasoundmentioning

confidence: 99%

“…In a further refinement, the five parameters (HR ratio , HPV ratio , AR, DV, PVW visual ) will be combined with texture analysis of the liver parenchyma in the images to discriminate multiple steatosis classes using machine learning approaches. Taking 1 H-MRS values as ground-truth, the diagnostic performance of advanced algorithms will extend the quantification of higher intrahepatic fat levels by ultrasound[ 65 - 67 ].…”

Section: Intrahepatic Fat Measured By Ultrasoundmentioning

confidence: 99%

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Digital liver biopsy: Bio-imaging of fatty liver for translational and clinical research

Mancini¹,

Summers²,

Faita³

et al. 2018

WJH

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The rapidly growing field of functional, molecular and structural bio-imaging is providing an extraordinary new opportunity to overcome the limits of invasive liver biopsy and introduce a “digital biopsy” for in vivo study of liver pathophysiology. To foster the application of bio-imaging in clinical and translational research, there is a need to standardize the methods of both acquisition and the storage of the bio-images of the liver. It can be hoped that the combination of digital, liquid and histologic liver biopsies will provide an innovative synergistic tri-dimensional approach to identifying new aetiologies, diagnostic and prognostic biomarkers and therapeutic targets for the optimization of personalized therapy of liver diseases and liver cancer. A group of experts of different disciplines (Special Interest Group for Personalized Hepatology of the Italian Association for the Study of the Liver, Institute for Biostructures and Bio-imaging of the National Research Council and Bio-banking and Biomolecular Resources Research Infrastructure) discussed criteria, methods and guidelines for facilitating the requisite application of data collection. This manuscript provides a multi-Author review of the issue with special focus on fatty liver.

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A Deep Learning Approach for Hepatic Steatosis Estimation from Ultrasound Imaging

Colantonio

Salvati²,

Caudai

et al. 2021

Advances in Computational Collective Intelligence

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Steato-Score: Non-Invasive Quantitative Assessment of Liver Fat by Ultrasound Imaging

Cited by 20 publications

References 45 publications

Reproducibility of ultrasound attenuation imaging for the noninvasive evaluation of hepatic steatosis

Reproducibility of ultrasound attenuation imaging for the noninvasive evaluation of hepatic steatosis

Digital liver biopsy: Bio-imaging of fatty liver for translational and clinical research

A Deep Learning Approach for Hepatic Steatosis Estimation from Ultrasound Imaging

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