Evaluation of histopathological differentiation in pancreatic ductal adenocarcinoma by texture analysis of CT
CSTR:
Author:
Affiliation:

Clc Number:

R735.9

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Objective:To investigate the value of the texture analysis based on preoperative enhanced CT in predicting the histopathological differentiation of pancreatic ductal adenocarcinoma(PDAC). Methods:Pathological data of 66 patients with PDAC from January 2017 to October 2020 were retrospectively collected,other 34 PDAC patients from other hospital were used for external validation cohort,and they were divided into two groups according to postoperative pathological results:high differentiation and moderately - poorly differentiation. The clinical and conventional imaging characteristics such as gender,age,tumor site,maximum tumor diameter,tumor enhancement and vascular invasion were recorded for univariate regression analysis. ROI based on both arterial phase and venous phase of the preoperative enhanced CT was automatically drawn by ITK -SNAP software and texture features were extracted. Univariate analysis was used to compare the texture features between the two groups,and the texture features with statistical difference were included in binary logistic regression model,and the prediction model of arterial phase and venous phase were established respectively. The prediction model established by the training group is directly applied to the external validation group. The AUC values of ROC were used to evaluate the diagnostic value of prediction model. Results:One and two texture features were selected to construct prediction model respectively based on the CT arterial and venous phase,including run entropy,zone percentage and size-zone non-uniformity. The AUC,sensitivity and specificity were 0.716,0.581,0.824,0.722,0.600,and 0.765 in the training group and the validation group based on the CT arterial texture feature model respectively. The AUC,sensitivity and specificity of the CT venous texture feature model in the training group and the validation group were 0.895,0.781,0.882,0.873,0.722,0.929, respectively. Conclusion:There are differences in the characteristic parameters of texture analysis of CT enhanced images between highly and moderately-poorly differentiated pancreatic ductal adenocarcinoma,providing a new method for preoperative evaluation of the malignant degree of pancreatic ductal adenocarcinoma carcinoma.

    Reference
    Related
    Cited by
Get Citation

吴锦,徐珊珊,张怡帆,汤盛楠,何健. CT纹理特征评估胰腺导管腺癌的分化程度[J].南京医科大学学报(自然科学版英文版),2022,42(10):1464-1470.

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:
  • Revised:
  • Adopted:
  • Online: October 25,2022
  • Published:
Article QR Code