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Erschienen in:
05.02.2018 | Hepatobiliary-Pancreas
Imaging prediction of nonalcoholic steatohepatitis using computed tomography texture analysis
Erschienen in: European Radiology | Ausgabe 7/2018
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Objectives
To determine if texture analysis of non-contrast-enhanced CT (NECT) images is able to predict nonalcoholic steatohepatitis (NASH).
Methods
NECT images from 88 patients who underwent a liver biopsy for the diagnosis of suspected NASH were assessed and texture feature parameters were obtained without and with filtration. The patient population was divided into a predictive learning dataset and a validation dataset, and further divided into groups according to the prediction of liver fibrosis as assessed by hyaluronic acid levels. The reference standard was the histological result of a liver biopsy. A predictive model for NASH was developed using parameters derived from the learning dataset that demonstrated areas under the receiver operating characteristic curve (AUC) of >0.65. The resulting model was then applied to the validation dataset.
Results
In patients without suspected fibrosis, the texture parameter mean without filter and skewness with a 2-mm filter were selected for the NASH prediction model. The AUC of the predictive model for the validation dataset was 0.94 and the accuracy was 94%. In patients with suspicion of fibrosis, the mean without filtration and kurtosis with a 4-mm filter were selected for the NASH prediction model. The AUC for the validation dataset was 0.60 and the accuracy was 42%.
Conclusions
In patients without suspicion of fibrosis, NECT texture analysis effectively predicted NASH.
Key Points
• In patients without suspicion of fibrosis, NECT texture analysis effectively predicted NASH.
• The mean without filtration and skewness with a 2-mm filter were modest predictors of NASH in patients without suspicion of liver fibrosis.
• Hepatic fibrosis masks the characteristic texture features of NASH.