Computed Tomography Radiomics Model Predicts Procedure Success of Coronary Chronic Total Occlusions

Author:

Ling Runjianya1ORCID,Chen Xiuyu2,Yu Yarong3,Yu Lihua3,Yang Wenyi4ORCID,Xu Zhihan5ORCID,Li Yuehua1,Zhang Jiayin3ORCID

Affiliation:

1. Institute of Diagnostic and Interventional Radiology, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, China (R.L., Y.L.).

2. Department of Magnetic Resonance Imaging, Fuwai Hospital, State Key Laboratory of Cardiovascular Disease, National Centre for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (X.C.).

3. Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, China (Y.Y., L.Y., J.Z.).

4. Department of Cardiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, China (W.Y.).

5. Siemen Healthineers, CT collaboration, Shanghai, China (Z.X.).

Abstract

Background: Coronary computed tomography (CT) angiography imaging is useful for the preprocedural evaluation of chronic total occlusion (CTO). However, the predictive value of CT radiomics model for successful percutaneous coronary intervention (PCI) has not been studied. We aimed to develop and validate a CT radiomics model for predicting PCI success of CTOs. Methods: In this retrospective study, a radiomics-based model for predicting PCI success was developed on the training and internal validation sets of 202 and 98 patients with CTO, collected from 1 tertiary hospital. The proposed model was validated on an external test set of 75 CTO patients enrolled from another tertiary hospital. CT radiomics features of each CTO lesion were manually labeled and extracted. Other anatomical parameters, including occlusion length, entry morphology, tortuosity, and calcification burden, were also measured. Fifteen radiomics features, 2 quantitative plaque features, and CT-derived Multicenter CTO Registry of Japan score were used to train different models. The predictive values of each model were evaluated for predicting revascularization success. Results: In the external test set, 75 patients (60 men; 65 years [58.5, 71.5]) with 83 CTO lesions were assessed. Occlusion length was shorter (13.00 mm versus 29.30 mm, P =0.007) in PCI success group whereas the presence of tortuous course was more commonly presented in PCI failure group (1.49% versus 25.00%, P =0.004). The radiomics score was significantly smaller in PCI success group (0.10 versus 0.55, P <0.001). The area under the curve of CT radiomics-based model was significantly higher than that of CT-derived Multicenter CTO Registry of Japan score for predicting PCI success (area under the curve=0.920 versus 0.752, P =0.008). The proposed radiomics model accurately identified 89.16% (74/83) CTO lesions with procedure success. Conclusions: CT radiomics-based model outperformed CT-derived Multicenter CTO Registry of Japan score for predicting PCI success. The proposed model is more accurate than the conventional anatomical parameters to identify CTO lesions with PCI success.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Cardiology and Cardiovascular Medicine,Radiology, Nuclear Medicine and imaging

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