Quantitative ultrasound, elastography, and machine learning for assessment of steatosis, inflammation, and fibrosis in chronic liver disease

To develop a quantitative ultrasound (QUS)- and elastography-based model to improve classification of steatosis grade, inflammation grade, and fibrosis stage in patients with chronic liver disease in comparison with shear wave elastography alone, using histopathology as the reference standard. This...

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Vydáno v:	PloS one Ročník 17; číslo 1; s. e0262291
Hlavní autoři:	Destrempes, François, Gesnik, Marc, Chayer, Boris, Roy-Cardinal, Marie-Hélène, Olivié, Damien, Giard, Jeanne-Marie, Sebastiani, Giada, Nguyen, Bich N., Cloutier, Guy, Tang, An
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States Public Library of Science 27.01.2022 Public Library of Science (PLoS)
Témata:	Accuracy Adult Aged Area Under Curve Attenuation coefficients Biology and Life Sciences Biopsy Chronic Disease Classification Computer and Information Sciences Development and progression Diagnosis Diagnosis, Ultrasonic Elasticity Elasticity Imaging Techniques - methods Engineering and Technology Evaluation Studies as Topic Fatty liver Female Fibrosis Health aspects Hepatitis Hepatitis B Hepatitis B, Chronic - pathology Hepatology Histopathology Hospitals Humans Inflammation Inflammation - pathology K-distribution Laboratories Learning algorithms Liver Liver - pathology Liver cirrhosis Liver Cirrhosis - pathology Liver diseases Machine Learning Male Medicine and Health Sciences Middle Aged Modelling Non-alcoholic Fatty Liver Disease - pathology Nuclear medicine Oncology Parameter identification Pathology Prospective Studies Quality Radiation Research and Analysis Methods Risk factors ROC Curve Shear Steatosis Ultrasonic imaging Ultrasonography - methods Ultrasound Viruses Young Adult Canada
ISSN:	1932-6203, 1932-6203
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Shrnutí:	To develop a quantitative ultrasound (QUS)- and elastography-based model to improve classification of steatosis grade, inflammation grade, and fibrosis stage in patients with chronic liver disease in comparison with shear wave elastography alone, using histopathology as the reference standard. This ancillary study to a prospective institutional review-board approved study included 82 patients with non-alcoholic fatty liver disease, chronic hepatitis B or C virus, or autoimmune hepatitis. Elastography measurements, homodyned K-distribution parametric maps, and total attenuation coefficient slope were recorded. Random forests classification and bootstrapping were used to identify combinations of parameters that provided the highest diagnostic accuracy. Receiver operating characteristic (ROC) curves were computed. For classification of steatosis grade S0 vs. S1-3, S0-1 vs. S2-3, S0-2 vs. S3, area under the receiver operating characteristic curve (AUC) were respectively 0.60, 0.63, and 0.62 with elasticity alone, and 0.90, 0.81, and 0.78 with the best tested model combining QUS and elastography features. For classification of inflammation grade A0 vs. A1-3, A0-1 vs. A2-3, A0-2 vs. A3, AUCs were respectively 0.56, 0.62, and 0.64 with elasticity alone, and 0.75, 0.68, and 0.69 with the best model. For classification of liver fibrosis stage F0 vs. F1-4, F0-1 vs. F2-4, F0-2 vs. F3-4, F0-3 vs. F4, AUCs were respectively 0.66, 0.77, 0.72, and 0.74 with elasticity alone, and 0.72, 0.77, 0.77, and 0.75 with the best model. Random forest models incorporating QUS and shear wave elastography increased the classification accuracy of liver steatosis, inflammation, and fibrosis when compared to shear wave elastography alone.
Bibliografie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Competing Interests: The authors have declared that no competing interests exist.
ISSN:	1932-6203 1932-6203
DOI:	10.1371/journal.pone.0262291