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Zhou Z, Bo K, Gao Y, Zhang W, Zhang H, Chen Y, Chen Y, Wang H, Zhang N, Huang Y, Mao X, Gao Z, Zhang H, Xu L. Deep Learning and Radiomics Discrimination of Coronary Chronic Total Occlusion and Subtotal Occlusion using CTA. Acad Radiol 2025:S1076-6332(25)00206-5. [PMID: 40164533 DOI: 10.1016/j.acra.2025.03.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2025] [Revised: 03/03/2025] [Accepted: 03/08/2025] [Indexed: 04/02/2025]
Abstract
RATIONALE AND OBJECTIVES Coronary chronic total occlusion (CTO) and subtotal occlusion (STO) pose diagnostic challenges, differing in treatment strategies. Artificial intelligence and radiomics are promising tools for accurate discrimination. This study aimed to develop deep learning (DL) and radiomics models using coronary computed tomography angiography (CCTA) to differentiate CTO from STO lesions and compare their performance with that of the conventional method. MATERIALS AND METHODS CTO and STO were identified retrospectively from a tertiary hospital and served as training and validation sets for developing and validating the DL and radiomics models to distinguish CTO from STO. An external test cohort was recruited from two additional tertiary hospitals with identical eligibility criteria. All participants underwent CCTA within 1 month before invasive coronary angiography. RESULTS A total of 581 participants (mean age, 50 years ± 11 [SD]; 474 [81.6%] men) with 600 lesions were enrolled, including 403 CTO and 197 STO lesions. The DL and radiomics models exhibited better discrimination performance than the conventional method, with areas under the curve of 0.908 and 0.860, respectively, vs. 0.794 in the validation set (all p<0.05), and 0.893 and 0.827, respectively, vs. 0.746 in the external test set (all p<0.05). CONCLUSIONS The proposed CCTA-based DL and radiomics models achieved efficient and accurate discrimination of coronary CTO and STO.
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Affiliation(s)
- Zhen Zhou
- Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China (Z.Z., K.B., Y.G., H.Z., Y.C., Y.C., H.W., N.Z., L.X.)
| | - Kairui Bo
- Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China (Z.Z., K.B., Y.G., H.Z., Y.C., Y.C., H.W., N.Z., L.X.)
| | - Yifeng Gao
- Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China (Z.Z., K.B., Y.G., H.Z., Y.C., Y.C., H.W., N.Z., L.X.)
| | - Weiwei Zhang
- School of Biomedical Engineering, Sun Yat-Sen University, Guangzhou, China (W.Z., Z.G., H.Z.)
| | - Hongkai Zhang
- Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China (Z.Z., K.B., Y.G., H.Z., Y.C., Y.C., H.W., N.Z., L.X.)
| | - Yan Chen
- Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China (Z.Z., K.B., Y.G., H.Z., Y.C., Y.C., H.W., N.Z., L.X.)
| | - Yanchun Chen
- Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China (Z.Z., K.B., Y.G., H.Z., Y.C., Y.C., H.W., N.Z., L.X.)
| | - Hui Wang
- Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China (Z.Z., K.B., Y.G., H.Z., Y.C., Y.C., H.W., N.Z., L.X.)
| | - Nan Zhang
- Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China (Z.Z., K.B., Y.G., H.Z., Y.C., Y.C., H.W., N.Z., L.X.)
| | - Yimin Huang
- Shukun Technology Co., Ltd, Beijing, China (Y.H., X.M.)
| | - Xinsheng Mao
- Shukun Technology Co., Ltd, Beijing, China (Y.H., X.M.)
| | - Zhifan Gao
- School of Biomedical Engineering, Sun Yat-Sen University, Guangzhou, China (W.Z., Z.G., H.Z.)
| | - Heye Zhang
- School of Biomedical Engineering, Sun Yat-Sen University, Guangzhou, China (W.Z., Z.G., H.Z.)
| | - Lei Xu
- Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China (Z.Z., K.B., Y.G., H.Z., Y.C., Y.C., H.W., N.Z., L.X.).
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Xu W, Ma J, Chen Y, Zhou F, Zhou C, Zhang LJ. Coronary chronic total occlusion on coronary CT angiography: what radiologists should know? Insights Imaging 2024; 15:55. [PMID: 38411752 PMCID: PMC10899151 DOI: 10.1186/s13244-024-01621-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 01/11/2024] [Indexed: 02/28/2024] Open
Abstract
Coronary chronic total occlusion (CTO) often occurs in patients with obstructive coronary artery disease, which remains one of the greatest challenges for interventional cardiologists. Coronary computed tomography angiography (CCTA) with its emerging post-processing techniques can provide a detailed assessment of CTO lesions before percutaneous coronary intervention (PCI), playing an important role in the clinical management of CTO PCI, from early diagnosis, pre-procedural outcome prediction, the crossing algorithm planning, intraprocedural guidance, and finally post-procedural assessment and follow-up. In addition, the feasibility of CT perfusion (CTP) in patients with CTO has been validated. Combined CCTA and CTP have the great potential to be the one-stop-shop imaging modality for assessing both anatomy and function of CTO lesions. This review aims to make radiologists understand the role of CCTA in the diagnosis and assessment of CTO lesions, thus assisting interventionalists in optimizing CTO PCI crossing strategies with the expertise of radiologists.Critical relevance statement The anatomical features of CTO on CCTA can reveal the complexity of CTO lesions and are associated with CTO PCI outcome, thus helping interventionalists optimize CTO PCI crossing strategies.Key points • CTO is the common lesion in invasive coronary angiography, and CTO PCI is technically difficult and its success rate is relatively low.• Length, collaterals, and attenuation-related signs can help distinguish CTO from subtotal occlusion.• The anatomical features of CTO lesions can help grade the difficulty of CTO PCI and predict procedural outcomes and long-term outcomes of CTO PCI.• The real-time fusion of CCTA with fluoroscopic angiography can be applied in highly complicated CTO lesions.• After CTO PCI, CCTA can help guide a second CTO PCI re-entry or follow up stent patency.
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Affiliation(s)
- Wei Xu
- Department of Radiology, Jinling Hospital, Nanjing Medical University, 305 Zhongshan East Road, Nanjing, China
| | - Junfeng Ma
- Emergency Medical Center, Xi'an Xianyang International Airport Co., Ltd., Xianyang, China
| | - Yiwen Chen
- Department of Radiology, Jinling Hospital, Nanjing Medical University, 305 Zhongshan East Road, Nanjing, China
| | - Fan Zhou
- Department of Radiology, Affiliated Jinling Hospital of Medical School, Nanjing University, 305 Zhongshan East Road, Nanjing, China
| | - Changsheng Zhou
- Department of Radiology, Affiliated Jinling Hospital of Medical School, Nanjing University, 305 Zhongshan East Road, Nanjing, China
| | - Long Jiang Zhang
- Department of Radiology, Jinling Hospital, Nanjing Medical University, 305 Zhongshan East Road, Nanjing, China.
- Department of Radiology, Affiliated Jinling Hospital of Medical School, Nanjing University, 305 Zhongshan East Road, Nanjing, China.
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