Prediction of serosal invasion in gastric cancer: development and validation of multivariate models integrating preoperative clinicopathological features and radiographic findings based on late arterial phase CT images

BMC Cancer. 2021 Sep 16;21(1):1038. doi: 10.1186/s12885-021-08672-0.

Abstract

Background: To develop and validate multivariate models integrating endoscopic biopsy, tumor markers, and CT findings based on late arterial phase (LAP) to predict serosal invasion in gastric cancer (GC).

Methods: The preoperative differentiation degree, tumor markers, CT morphological characteristics, and CT value-related and texture parameters of 154 patients with GC were analyzed retrospectively. Multivariate models based on regression analysis and machine learning algorithms were performed to improve the diagnostic efficacy.

Results: The differentiation degree, carbohydrate antigen (CA) 199, CA724, CA242, and multiple CT findings based on LAP differed significantly between T1-3 and T4 GCs in the primary cohort (all P < 0.05). Multivariate models based on regression analysis and random forest achieved AUCs of 0.849 and 0.865 in the primary cohort, respectively.

Conclusion: We developed and validated multivariate models integrating endoscopic biopsy, tumor markers, CT morphological characteristics, and CT value-related and texture parameters to predict serosal invasion in GCs and achieved favorable performance.

Keywords: Biomarkers, tumor; Endoscopy; Neoplasm staging; Stomach neoplasms; Tomography, X-ray computed.

Publication types

  • Validation Study

MeSH terms

  • Adult
  • Aged
  • Antigens, Tumor-Associated, Carbohydrate / blood
  • Biomarkers, Tumor
  • Biopsy / methods
  • Decision Trees
  • Female
  • Gastroscopy
  • Humans
  • Machine Learning
  • Male
  • Middle Aged
  • Models, Statistical*
  • Neoplasm Invasiveness*
  • Preoperative Period
  • Regression Analysis
  • Retrospective Studies
  • Serous Membrane / pathology*
  • Stomach Neoplasms / blood supply
  • Stomach Neoplasms / diagnostic imaging
  • Stomach Neoplasms / pathology*
  • Tomography, X-Ray Computed / methods

Substances

  • Antigens, Tumor-Associated, Carbohydrate
  • Biomarkers, Tumor
  • CA 242 antigen
  • CA-72-4 antigen
  • carbohydrate antigen 199, human