Radiomic of enhanced CT for identification of benign and borderline serous tumors of ovary / 中国介入影像与治疗学

ABSTRACT

Objective: To establish radiomic model based on enhanced CT, and to observe the value of the model for distinguishing benign and borderline serous tumors of ovary. Methods: Data of CT imaging of 49 patients with ovary serous cystadenoma (SC) and 31 patients with serous borderline tumors (SBT) confirmed by pathology were retrospectively analyzed. AK software was used by 2 radiologists to delineate ROI of the tumors, and radiomic parameters were extracted. Then multiple Logistic regression was applied to identify optimal radiomic features and construct the prediction model. ROC curve was used to analyze the diagnostic efficacy of radiomic parameters and model on ovarian SC and SBT. Results: A total of 396 image radiomics parameters were extracted, and 5 feature parameters were obtained after dimensionality reduction, namely Percentile10, Percentile15, SA, LRHGLEa90, o1 and LRHGLEa90, o7, respectively. The results of reproducibility analysis of 2 radiologists had good consistency (all intraclass correlation coefficient> 0.75). Radscore prediction model was constructed with the above 5 characteristic parameters, and the AUC, sensitivity and specificity of Radscore model for differentiating ovarian SC and SBT in the training set was 0.90, 0.91 and 0.79, while in the testing set was 0.86, 0.90 and 0.73, respectively. Conclusion: Radiomic model based on enhanced CT can be used for identifying SC and SBT of ovary.