Abstract
To develop and validate a novel method based on radiomics for the preoperative differentiation of benign and malignant gallbladder polypoid lesions (PLG). A total of 145 patients with pathological proven gallbladder polypoid lesions ≥ 1cm were included in this retrospective study. All the patients underwent abdominal contrast-enhanced computed tomography (CT) examinations 3weeks before cholecystectomy from January 2013 to January 2019. Seventy percent of the cases were randomly selected for the training dataset, and 30% of the cases were independently used for testing. Radiomics features extracted from portal venous-phase CT of the PLG and clinical features were analyzed, and the LASSO regression algorithm was used for data dimension reduction. Multivariable logistic regression was used to generate radiomics signatures, clinical signatures, and combination signatures. The receiver operating characteristic (ROC) curve and decision curve were plotted to assess the differentiating performance of the three signatures. The area under the ROC curve (AUC) of the radiomics signature and clinical signature was 0.924 and 0.861 in the testing dataset, respectively. For the radiomics signature, the accuracy was 88.6%, with 88.0% specificity and 89.5% sensitivity. When combined, the AUC was 0.931, the specificity was 84.0%, and the sensitivity was 89.5%. The differences between the AUC values of the two sole models and the combination model were statistically nonsignificant. Radiomics based on CT images can be helpful to differentiate benign and malignant gallbladder polyps ≥ 1cm in size.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.