Performance evaluation of deep learning-based post-processing and diagnostic reporting system for coronary CT angiography: a clinical comparative study

Performance evaluation of deep learning-based post-processing and diagnostic reporting system for coronary CT angiography: a clinical comparative study

In the clinical validation of this study, patients were eligible if they underwent CCTA and invasive coronary angiography (ICA) in sequence within 6 months from January 2017 to January 2019 in Beijing Friendship Hospital. Non-ionic contrast media (iopromide 370 or iohexol 350) was continuously injec...

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Veröffentlicht in:Chinese medical journal 2022-10, Vol.135 (19), p.2366-2368
Hauptverfasser: Luo, Nan, He, Yi, Fan, Jitao, Guo, Ning, Yang, Guang, Kong, Yuanyuan, Wei, Jianyong, Bi, Tao, Zhou, Jie, Cao, Jiaxin, Han, Xianjun, Li, Fang, Zhang, Shiyu, Sun, Rujing, Wang, Zhaozhao, Ma, Tian, Xu, Lixue, Chen, Hui, Li, Hongwei, Wang, Zhenchang, Yang, Zhenghan
Format: Artikel
Sprache:eng
Schlagworte:
Algorithms
Artificial intelligence
Cardiovascular disease
Computed Tomography Angiography
Coronary Angiography
Coronary Artery Disease
Coronary Stenosis - diagnosis
Coronary vessels
Deep Learning
Fractional Flow Reserve, Myocardial
Humans
Medical imaging
Patients
Performance evaluation
Predictive Value of Tests
Professionals
Retrospective Studies
Scanners
Tomography
Tomography, X-Ray Computed
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Zusammenfassung:In the clinical validation of this study, patients were eligible if they underwent CCTA and invasive coronary angiography (ICA) in sequence within 6 months from January 2017 to January 2019 in Beijing Friendship Hospital. Non-ionic contrast media (iopromide 370 or iohexol 350) was continuously injected into the antecubital vein at 5 mL/s with a volume of 60 mL when the body weight was
ISSN:0366-6999
2542-5641
DOI:10.1097/CM9.0000000000001913