Value of CT Radiomics Combined with Clinical Features in the Diagnosis of Allergic Bronchopulmonary Aspergillosis

Abstract

Objective. Early diagnosis of allergic bronchopulmonary aspergillosis (ABPA) and targeted treatment can block the process of the disease. This study explores the diagnostic value of CT radiomics combined with clinical features in allergic ABPA. Methods. A total of 40 patients with ABPA were studied retrospectively, divided into training set ( $n=28$ ) and test set ( $n=12$ ). Based on CT imaging, the radiomics features are extracted and combined with clinical features to build a diagnostic model. The diagnosis model was based on support vector machine algorithm. The receiver operating characteristic curve (ROC) and area under the curve (AUC) were used to evaluate the diagnostic efficiency of the model. Results. There was no significant difference in general information and clinical data between the training and test sets ( $P>0.05$ ). The AUC of the training set and the test set is 0.896 (95% CI: 0.836-0.963) and 0.886 (95% CI: 0.821-0.952), respectively. Conclusion. Based on the CT radiomics model combined with clinical data, it has high efficiency in the diagnosis of ABPA.