Development and validation of CT-based clinical-radiomics nomogram for predicting abdominal aortic aneurysms progression

Background: The rapid progression associated with abdominal aortic aneurysms (AAA) is the major contributor to morbidity and mortality among the elderly. More comprehensive radiomics-based prediction of AAA progression is both valuable and warranted. Methods: In this multicenter retrospective investigation, 166 AAA patients who received two contrast-enhanced abdominal CT examinations from January 2014 to July 2022 were divided into training (n = 92) and external test cohort (n = 74). A clinical model for predicting AAA progression was built using clinical and CT characteristics that were significant independent predictors. Radiomics features were extracted from CT images, and a radiomics signature was constructed. The nomogram model was constructed by combining clinical model and radiomics signature. The diagnostic performance were evaluated and validated on the training and test sets, and then compared among the three models. Results: Over a median of 0.94 years (range, 0.5-7.05 years), 66 patients (training set: n = 35; external test set: n= 31) experienced AAA progression. The clinical model was built by diabetes and AAA maximal diameter. Seven features were employed to build the radiomics signature. In the external test set, the area under the curve was higher for the nomogram (0.83) than for the clinical model (0.69, p =0.02), and the nomogram model showed a sensitivity, specificity, and accuracy of 74.2%, 81.4%, and 78.4%. Conclusions: The nomogram model combining the clinical factors and radiomics signature showed better diagnostic performance than the clinical model, and may assist clinical decision-making process.