eISSN: 1897-4317
ISSN: 1895-5770
Gastroenterology Review/Przegląd Gastroenterologiczny
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without publication fees
2/2023
vol. 18
 
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abstract:
Original paper

Clinical and magnetic resonance imaging features predict microvascular invasion in intrahepatic cholangiocarcinoma

Jin-Jun Sun
1
,
Xian-Ling Qian
2, 3, 4
,
Yi-Bing Shi
1
,
Yu-Fei Fu
1
,
Chun Yang
2, 3, 4
,
Xi-Juan Ma
1

  1. Department of Radiology, Xuzhou Central Hospital, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, China
  2. Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
  3. Shanghai Institute of Medical Imaging, Shanghai, China
  4. Department of Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
Gastroenterology Rev 2023; 18 (2): 161–167
DOI: https://doi.org/10.5114/pg.2022.116668
Online publish date: 2022/09/07
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Introduction
Clinical features and magnetic resonance imaging (MRI)-related data are commonly employed in clinical settings and can be used to predict the microvascular invasion (MVI) status of intrahepatic cholangiocarcinoma (ICC) patients.

Aim
To generate a clinical and MRI-based model capable of predicting the MVI status of ICC patients.

Material and methods
Consecutive ICC patients evaluated from June 2015 to December 2018 were retrospectively enrolled in a training group to establish a predictive clinical MRI model. Consecutive ICC patients evaluated from January 2019 to June 2019 were prospectively enrolled in a validation group to test the reliability of this model.

Results
In total, 143 patients were enrolled in the training group, of whom 46 (32.2%) and 96 (67.8%) were MVI-positive and MVI-negative, respectively. Logistics analyses revealed larger tumour size (p = 0.008) and intrahepatic duct dilatation (p = 0.01) to be predictive of MVI positivity, enabling the establishment of the following predictive model: –2.468 + 0.024 × tumour size + 1.094 × intrahepatic duct dilatation. The area under the receiver operating characteristic (ROC) curve (AUC) for this model was 0.738 (p < 0.001). An optimal cut-off value of –1.0184 was selected to maximize sensitivity (71.7%) and specificity (61.9%). When the data from the validation group were incorporated into the predictive model, the AUC value was 0.716 (p = 0.009).

Conclusions
Both larger tumour size and intrahepatic duct dilatation were predictive of MVI positivity in patients diagnosed with ICC, and the predictive model developed based on these variables can offer quantitative guidance for assessing the risk of MVI.

keywords:

intrahepatic cholangiocarcinoma, microvascular invasion, magnetic resonance imaging
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