Purpose or Learning Objective To investigate whether a radiomic analysis performed on hepatocellular carcinoma can reveal the presence of microvascular invasion (MVI). Methods or Background The dataset includes seventy-one early-stage HCC nodules (Milan criteria, nodule≤3 cm, without macrovascular invasion and extrahepatic spread), where forty-two are MVI positive (MVI+) and twenty-nine are MVI negative (MVI-), at histopathological report obtained after surgery. Radiomic analysis is performed on contrast-enhanced CT imaging during the arterial phase. HCC nodules were manually segmented and eighty-four local first-order radiomic features (RFs) are computed from HCC Region of Interest (ROIs). To avoid overfitting, only one couple of RFs is selected for discriminating MVI+ and MVI- into three steps: (i) a subset of RFs is first selected through LASSO; (ii) linearly correlated couples are discarded; (iii) after computing the ROC curve, the most discriminating couple is selected as that one yielding the highest AUC. The discrimination between MVI+ and MVI- is assessed through specificity and sensitivity computed at the Youden Index (YI). Results or Findings The selected couple combines a measure of local heterogeneity to mean CT image values in HCC ROIs and allows achieving an AUC=0.86, with specificity=81% and sensitivity=83% at the YI=0.64. Conclusion The radiomic analysis allows unravelling different inner properties of HCC MVI+ nodules, which show a more heterogeneous tumour pattern with respect to MVI-. Limitations This radiomic analysis was performed exclusively on arterial-phase contrast enhanced images, although it is reasonable arguing that the next inclusion of venous phase images must only improve the outcomes.

Radiomic features disclose the presence of microvascular invasion in hepatocellular carcinoma

Alessandro Bevilacqua;Margherita Mottola;Arianna Rustici;L. V. Pastore;Rita Golfieri
2021

Abstract

Purpose or Learning Objective To investigate whether a radiomic analysis performed on hepatocellular carcinoma can reveal the presence of microvascular invasion (MVI). Methods or Background The dataset includes seventy-one early-stage HCC nodules (Milan criteria, nodule≤3 cm, without macrovascular invasion and extrahepatic spread), where forty-two are MVI positive (MVI+) and twenty-nine are MVI negative (MVI-), at histopathological report obtained after surgery. Radiomic analysis is performed on contrast-enhanced CT imaging during the arterial phase. HCC nodules were manually segmented and eighty-four local first-order radiomic features (RFs) are computed from HCC Region of Interest (ROIs). To avoid overfitting, only one couple of RFs is selected for discriminating MVI+ and MVI- into three steps: (i) a subset of RFs is first selected through LASSO; (ii) linearly correlated couples are discarded; (iii) after computing the ROC curve, the most discriminating couple is selected as that one yielding the highest AUC. The discrimination between MVI+ and MVI- is assessed through specificity and sensitivity computed at the Youden Index (YI). Results or Findings The selected couple combines a measure of local heterogeneity to mean CT image values in HCC ROIs and allows achieving an AUC=0.86, with specificity=81% and sensitivity=83% at the YI=0.64. Conclusion The radiomic analysis allows unravelling different inner properties of HCC MVI+ nodules, which show a more heterogeneous tumour pattern with respect to MVI-. Limitations This radiomic analysis was performed exclusively on arterial-phase contrast enhanced images, although it is reasonable arguing that the next inclusion of venous phase images must only improve the outcomes.
ECR 2021 – BOOK OF ABSTRACTS
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Alessandro Bevilacqua, Francesca Coppola, Margherita Mottola, Matteo Renzulli, Giulio Vara, Arianna Rustici, L. V. Pastore, Lidia Strigari, Rita Golfieri;
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/785465
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