Quantification of hepatocellular carcinoma heterogeneity with multiparametric magnetic resonance imaging

Abstract : Tumour heterogeneity poses a significant challenge for treatment stratification. The goals of this study were to quantify heterogeneity in hepatocellular carcinoma (HCC) using multiparametric magnetic resonance imaging (mpMRI), and to report preliminary data correlating quantitative MRI parameters with advanced histopathology and gene expression in a patient subset. Thirty-two HCC patients with 39 HCC lesions underwent mpMRI including diffusion-weighted imaging (DWI), blood-oxygenation-level-dependent (BOLD), tissue-oxygenation-level-dependent (TOLD) and dynamic contrast-enhanced (DCE)-MRI. Histogram characteristics [central tendency (mean, median) and heterogeneity (standard deviation, kurtosis, skewness) MRI parameters] in HCC and liver parenchyma were compared using Wilcoxon signed-rank tests. Histogram data was correlated between MRI methods in all patients and with histopathology and gene expression in 14 patients. HCCs exhibited significantly higher intra-tissue heterogeneity vs. liver with all MRI methods (P < 0.030). Although central tendency parameters showed significant correlations between MRI methods and with each of histopathology and gene expression, heterogeneity parameters exhibited additional complementary correlations between BOLD and DCE-MRI and with histopathologic hypoxia marker HIF1α and gene expression of Wnt target GLUL, pharmacological target FGFR4, stemness markers EPCAM and KRT19 and immune checkpoint PDCD1. Histogram analysis combining central tendency and heterogeneity mpMRI features is promising for non-invasive HCC characterization on the imaging, histologic and genomics levels.
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http://hal.upmc.fr/hal-01542017
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Soumis le : lundi 19 juin 2017 - 15:02:08
Dernière modification le : mardi 20 juin 2017 - 01:03:34

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Stefanie J. Hectors, Mathilde Wagner, Octavia Bane, Cecilia Besa, Sara Lewis, et al.. Quantification of hepatocellular carcinoma heterogeneity with multiparametric magnetic resonance imaging. Scientific Reports, Nature Publishing Group, 2017, 7, pp.2452. 〈10.1038/s41598-017-02706-z〉. 〈hal-01542017〉

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