The incidence of esophageal squamous cell carcinoma (ESCC) in China is high and the prognosis is poor. Aimed toevaluate the ESCC, we investigated computerized quantitative analyses on diagnostic computed tomography (CT) anddigital histopathological slices.A retrospective study with IRB approval was conducted to assess the prognosis of ESCCs in 158 patients who underwentesophagectomy. Every of them has 3D CT image and pathological hematoxylin-eosin staining tissue slide. Weperformed quantitative analysis on digital histology slices and diagnostic CT volumes. A total of 125 computerizedquantitative features were extracted including 20 pathological image clustering (PIC) features and 105 CT features. Thenwe selected 45 CT features by correlation analysis and 5 PIC features by univariate survival analysis for preventingoverfitting.Cox hazard model with L1 penalization was used for prognostic indexing. We compared three different prognosticindices in order to build a robust model: Model A: using CT features alone; Model B: using PIC features alone; Model C:using both CT and PIC features. For testing the model, we performed leave-one-out cross-validation for testing and weused the index of concordance(C-index) to access the accuracy of the prognostic model. The testing C-index values ofModel A, B, C were 0.667, 0.601 and 0.711. The improvement of the final Model C is significant and it’s able to provideeffective stratification.Quantitative prognostic modeling with joint information from clinical, histopathology, and diagnostic CT has the abilityto stratify the patient well. Our prognostic model has potential to impact the perioperative care in the future clinicalpractice and improve the quality of individual life.
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