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Computed Tomography Radiomics to Differentiate Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma by S. Mahmoudi; S. Bernatz; J. Ackermann; V. Koch; D.P. Dos Santos; L.D. Grünewald; I. Yel; S.S. Martin; J.-E. Scholtz; A. Stehle; D. Walter; S. Zeuzem; P.J. Wild; T.J. Vogl; M.N. Kinzler is a Medicine article available to read on EtoBox.

What is Computed Tomography Radiomics to Differentiate Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma about?

Aims Intrahepatic cholangiocarcinoma (iCCA) and hepatocellular carcinoma (HCC) differ in prognosis and treatment. We aimed to non-invasively differentiate iCCA and HCC by means of radiomics extracted from contrast-enhanced standard-of-care computed tomography (CT). Materials and methods In total, 94 patients (male, n = 68, mean age 63.3 ± 12.4 years) with histologically confirmed iCCA (n = 47) or HCC (n = 47) who underwent contrast-enhanced abdominal CT between August 2014 and November 2021 were retrospectively included. The enhancing tumour border was manually segmented in a clinically feasible way by defining three three-dimensional volumes of interest per tumour. Radiomics features were extracted. Intraclass correlation analysis and Pearson metrics were used to stratify robust and non-redundant features with further feature reduction by LASSO (least absolute shrinkage and selection operator). Independent training and testing datasets were used to build four different machine learning models. Performance metrics and feature importance values were computed to increase the models' interpretability. Results The patient population was split into 65 patients for training (iCCA, n = 32

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Author

S. Mahmoudi; S. Bernatz; J. Ackermann; V. Koch; D.P. Dos Santos; L.D. Grünewald; I. Yel; S.S. Martin; J.-E. Scholtz; A. Stehle; D. Walter; S. Zeuzem; P.J. Wild; T.J. Vogl; M.N. Kinzler

Publisher

Elsevier BV

Published

2023

Language

EN

Field

Medicine (Health Sciences)