Background and Aims There remains a need to develop a non-invasive, accurate and easy-to-use tool to identify patients with non-alcoholic steatohepatitis (NASH). Successful clinical and preclinical applications demonstrate the ability of quantitative ultrasound (QUS) techniques to improve medical diagnostics. We aimed to develop and validate a diagnostic tool, based on QUS analysis, for identifying NASH. Methods A total of 259 Chinese individuals with biopsy-proven non-alcoholic fatty liver disease (NAFLD) were enrolled in the study. The histological spectrum of NAFLD was classified according to the NASH clinical research network scoring system. Radiofrequency (RF) data, raw data of iLivTouch, was acquired for further QUS analysis. The least absolute shrinkage and selection operator (LASSO) method was used to select the most useful predictive features. Results Eighteen candidate RF parameters were reduced to two significant parameters by shrinking the regression coefficients with the LASSO method. We built a novel QUS score based on these two parameters, and this QUS score showed good discriminatory capacity and calibration for identifying NASH both in the training set (area under the ROC curve [AUROC]: 0.798, 95% confidence interval [CI] 0.731-0.865; Hosmer-Lemeshow test, P = .755) and in the validation set (AUROC: 0.816, 95% CI 0.725-0.906; Hosmer-Lemeshow test, P = .397). Subgroup analysis showed that the QUS score performed well in different subgroups. Conclusions The QUS score, which was developed from QUS, provides a novel, non-invasive and practical way for identifying NASH.

A novel quantitative ultrasound technique for identifying non-alcoholic steatohepatitis

Targher, Giovanni
Writing – Review & Editing
;
2022

Abstract

Background and Aims There remains a need to develop a non-invasive, accurate and easy-to-use tool to identify patients with non-alcoholic steatohepatitis (NASH). Successful clinical and preclinical applications demonstrate the ability of quantitative ultrasound (QUS) techniques to improve medical diagnostics. We aimed to develop and validate a diagnostic tool, based on QUS analysis, for identifying NASH. Methods A total of 259 Chinese individuals with biopsy-proven non-alcoholic fatty liver disease (NAFLD) were enrolled in the study. The histological spectrum of NAFLD was classified according to the NASH clinical research network scoring system. Radiofrequency (RF) data, raw data of iLivTouch, was acquired for further QUS analysis. The least absolute shrinkage and selection operator (LASSO) method was used to select the most useful predictive features. Results Eighteen candidate RF parameters were reduced to two significant parameters by shrinking the regression coefficients with the LASSO method. We built a novel QUS score based on these two parameters, and this QUS score showed good discriminatory capacity and calibration for identifying NASH both in the training set (area under the ROC curve [AUROC]: 0.798, 95% confidence interval [CI] 0.731-0.865; Hosmer-Lemeshow test, P = .755) and in the validation set (AUROC: 0.816, 95% CI 0.725-0.906; Hosmer-Lemeshow test, P = .397). Subgroup analysis showed that the QUS score performed well in different subgroups. Conclusions The QUS score, which was developed from QUS, provides a novel, non-invasive and practical way for identifying NASH.
MAFLD
NAFLD
NASH
quantitative ultrasound
radiofrequency
transient elastography
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11562/1057489
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