Radiomics Analysis of CTO Plaques for Predicting Successful Guidewire Crossing Within 30 Minutes of PCI

Abstract

BACKGROUND: Coronary computed tomography angiography provides valuable information for evaluating the difficulty of chronic total occlusion (CTO) percutaneous coronary intervention. This study aimed to investigate the value of CTO plaque characteristics derived from radiomics analysis for predicting the difficulty of percutaneous coronary intervention. METHODS: Patients with CTO were retrospectively enrolled from a hospital as training and internal test sets and from the other 2 territory hospitals as external test sets. Radiomics characteristics were extracted from the CTO segment on coronary computed tomography angiography. Radiomics and combined models were developed to predict successful guidewire crossing within 30 minutes (guidewire success) of CTO percutaneous coronary intervention. Subgroup analysis was conducted to investigate the influence of potential risk factors on the radiomics model performance. RESULTS: A total of 551 patients (median, 60; interquartile range, 52.00–66.00 years, 460 men) with 565 CTO lesions were finally enrolled. In the training, internal test, and external test sets, 203 of 357, 85 of 149, and 38 of 59 CTO lesions achieved guidewire success, respectively. Six radiomics features were selected for constructing the radiomics model. In the external test set, the area under the receiver operating characteristic curve of the radiomics model was significantly higher than prior prediction models ( P <0.05 for all) with the area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity of 0.86, 74.58%, 81.58%, and 61.90%, respectively. The performance of the radiomics model was dependent on calcification, CTO location, adjacent branch(es), and operator caseload. CONCLUSIONS: CTO characteristics revealed by radiomics analysis can be used as effective imaging biomarkers for predicting guidewire success. However, the performance of the radiomics model depends on anatomic and operator factors.