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Combined DCE-MRI- and FDG-PET enable histopathological grading prediction in a rat model of hepatocellular carcinoma.

Authors :
Kaissis GA
Lohöfer FK
Hörl M
Heid I
Steiger K
Munoz-Alvarez KA
Schwaiger M
Rummeny EJ
Weichert W
Paprottka P
Braren R
Source :
European journal of radiology [Eur J Radiol] 2020 Mar; Vol. 124, pp. 108848. Date of Electronic Publication: 2020 Jan 23.
Publication Year :
2020

Abstract

Purpose: To test combined dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and 18F-FDG positron emission tomography (FDG-PET)-derived parameters for prediction of histopathological grading in a rat Diethyl Nitrosamine (DEN)-induced hepatocellular carcinoma (HCC) model.<br />Methods: 15 male Wistar rats, aged 10 weeks were treated with oral DEN 0.01 % in drinking water and monitored until HCCs were detectable. DCE-MRI and PET were performed consecutively on small animal scanners. 38 tumors were identified and manually segmented based on HCC-specific contrast enhancement patterns. Grading (G2/3: 24 tumors, G1:14 tumors) alongside other histopathological parameters, tumor volume, contrast agent and 18F-FDG uptake metrics were noted. Class imbalance was addressed using SMOTE and collinearity was removed using hierarchical clustering and principal component analysis. A logistic regression model was fit separately to the individual parameter groups (DCE-MRI-derived, PET-derived, tumor volume) and the combined parameters.<br />Results: The combined model using all imaging-derived parameters achieved a mean ± STD sensitivity of 0.88 ± 0.16, specificity of 0.70 ± 0.20 and AUC of 0.90 ± 0.03. No correlation was found between tumor grading and tumor volume, morphology, necrosis, extracellular matrix, immune cell infiltration or underlying liver fibrosis.<br />Conclusion: A combination of DCE-MRI- and 18F-FDG-PET-derived parameters provides high accuracy for histopathological grading of hepatocellular carcinoma in a relevant translational model system.<br />Competing Interests: Declaration of Competing Interest The authors state no conflicts of interest.<br /> (Copyright © 2020 Elsevier B.V. All rights reserved.)

Details

Language :
English
ISSN :
1872-7727
Volume :
124
Database :
MEDLINE
Journal :
European journal of radiology
Publication Type :
Academic Journal
Accession number :
32006931
Full Text :
https://doi.org/10.1016/j.ejrad.2020.108848