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Related Concept Videos

Imaging Studies for Cardiovascular System V: CT01:28

Imaging Studies for Cardiovascular System V: CT

406
Cardiac computed tomography (CT) scanning is an advanced cardiac imaging technique that utilizes CT technology, with or without intravenous (IV) contrast, to produce accurate cross-sectional virtual slices of specific areas of the heart, coronary circulation, and major blood vessels such as the aorta, pulmonary veins, and arteries. The computer processes these slices to generate three-dimensional images. Multidetector CT (MDCT) is a rapid form of CT scanning that captures multiple slices...
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Related Experiment Video

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Multimodal CT for Predicting Microvascular Invasion in Solitary cHCC-CCA: Dual-Center External Validation.

Wu-Yuan Liu1, Yu-Chen Wei2, Qiao-Fang Chen3

  • 1Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China (W.-Y.L.,Y.-C.W., Q.-F.C., Y.-F.T., L.C., J.-Y.L.); Department of Radiology, People's Hospital of Luchuan, Yulin, Guangxi, China (W.-Y.L.).

Academic Radiology
|February 21, 2026
PubMed
Summary

A new multimodal CT model accurately predicts microvascular invasion (MVI) in combined hepatocellular-cholangiocarcinoma (cHCC-CCA) before surgery. The model combines quantitative and semantic CT features, showing promise for improved patient risk stratification.

Keywords:
CHCC-CCADeep learningMicrovascular invasionPeritumoral segmentationRadiomics

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Area of Science:

  • Radiology and Imaging
  • Oncology
  • Hepatobiliary Surgery

Background:

  • Preoperative prediction of microvascular invasion (MVI) in combined hepatocellular-cholangiocarcinoma (cHCC-CCA) is challenging.
  • Externally validated computed tomography (CT)-based tools for MVI prediction in cHCC-CCA are scarce.

Purpose of the Study:

  • To develop and externally validate a multimodal CT model for MVI prediction in solitary cHCC-CCA.
  • To compare intratumoral, peritumoral, and combined segmentation strategies for MVI prediction.

Main Methods:

  • Retrospective dual-center study of 184 patients with solitary cHCC-CCA.
  • Development of a multimodal model using portal venous-phase quantitative CT features and multiphasic CT semantic features.
  • External validation using a separate cohort, with performance assessed by AUC, calibration, and SHAP analysis.

Main Results:

  • The multimodal CT model achieved moderate and consistent discrimination across segmentation strategies in external validation (AUC, 0.761-0.800).
  • The 10-mm peritumoral segmentation strategy showed a numerically highest AUC (0.800) and high sensitivity.
  • SHAP analyses identified rim arterial-phase hyperenhancement and widened perilesional enhancement as key predictors of MVI.

Conclusions:

  • A multimodal CT approach provides externally validated preoperative MVI risk estimation for solitary cHCC-CCA.
  • Peritumoral modeling demonstrated a modest advantage in MVI prediction, though not statistically superior.
  • Prospective multicenter validation is recommended to confirm the model's utility as a decision-support tool.