Cardiothoracic Imaging in China: Opening Up New Horizons : Journal of Thoracic Imaging

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Cardiothoracic Imaging in China

Opening Up New Horizons

Zhang, Long Jiang MD, PhD*; Yang, Junjie MD; Jin, Zhengyu MD; Lu, Guang Ming MD*

Author Information
doi: 10.1097/RTI.0000000000000681
  • Open

Since the mid-1990s, China has experienced profound economic and social changes, as well as seismic shifts in residents’ living and health conditions. With the acceleration of population aging and urbanization, the impact of chronic disease risk factors on the health of residents has become more and more significant, among which cardiovascular disease has become the leading cause of death in urban and rural residents in China.1,2 Approximately 4 million people die of cardiovascular disease in China every year.2 To fight against these chronic disorders and emerging infectious diseases, scientists and radiologists from China have made many efforts and important contributions in the past 2 decades.1,2

Driven by the rapid development of computing power, algorithm optimization and data storage capabilities, Chinese cardiothoracic radiology is experiencing its second development peak. Chinese cardiothoracic radiologists have developed and validated many advanced imaging techniques and integrated them into routine clinical use, such as dual-energy computed tomography pulmonary angiography, computed tomography–derived fractional flow reserve (CT-FFR), and both cardiac magnetic resonance and computed tomography myocardial perfusion techniques. These advanced imaging techniques have been demonstrated to have impressive discriminative capabilities, receiving sufficient attention in Chinese medical research.3–7 In recent years, a large number of articles on artificial intelligence methods to solve imaging tasks have flooded into medical journals, promoting the interdisciplinary integration of radiology, engineering, computer science, and other fields, culminating in the creation of machine learning based pulmonary nodule detection software and machine learning CT-FFR software in China.4,8 In this special China issue of the Journal, Tang and colleagues’9–11 review articles briefly describe the past, present, and future of cardiovascular imaging, thoracic imaging, and imaging in cardiac intervention in China, reflecting the progression and achievements of Chinese Cardiothoracic Radiology over the past 2 decades.

Thoracic and cardiovascular imaging is involved in many complex imaging and analysis procedures. To facilitate the dissemination of advanced cardiovascular imaging techniques in a standardized manner across China, Chinese cardiothoracic radiologists are actively involved in the development, promotion, and application of clinical guidelines, expert consensus, and recommendations. In this special issue, we publish the Chinese expert consensus document addressing CT-FFR on behalf of the Chinese Society of Radiology.12 Nowadays, Chinese cardiothoracic radiologists are pushing these advanced cardiovascular imaging techniques into clinical routine applications, an additional effort to lay a solid foundation for future research.

When the coronavirus disease 2019 (COVID-19) pandemic swept the world, causing serious losses of life and property, Chinese cardiothoracic radiologists fought in the forefront against this new disease. They rapidly summarized a series of imaging manifestations, dynamic changes of COVID-19 in chest and heart imaging, reported bioimaging markers of COVID-19, used machine learning techniques to automatically, efficiently and accurately detect COVID-19, classified the severity and assessed the prognosis of the disease.13–18 The infection control measures and experiences of radiology departments were published and disseminated in some international journals such as the Journal of Thoracic Imaging and the Korean Journal of Radiology.19,20 These experiences are still playing an important role in combating COVID-19 around the world.

Although still facing many great challenges such as methodological limitations and the lack of a large prospective multicenter study, Chinese Cardiothoracic Radiology has been exploring safer, more cost-effective, and patient-friendly noninvasive modalities to replace invasive methods. Many knowledge gaps still exist and must be bridged. Multidisciplinary cooperation and breakthroughs are imperative to improve the levels of scientific study and clinical transformation, with sustained cooperation being essential to solve future problems. As Chinese Cardiothoracic Radiology matures, we are eager to unite with more clinical physicians and scientists around the world to bring discoveries in cardiothoracic radiology from the laboratory to the larger public arena of clinical daily practice. Chinese Cardiothoracic Radiology is moving forward with an unyielding steadfastness, embracing its most prosperous era. We firmly believe that with our best efforts, the future of Chinese Cardiothoracic Radiology is promising.


The authors thank Professor U. Joseph Schoepf and Callum E. Gill from the Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina (25 Courtenay Drive, Charleston, SC 29425), for their editorial help for this manuscript.


1. Li X, Wu C, Lu J, et al. Cardiovascular risk factors in China: a nationwide population-based cohort study [published correction appears in Lancet Public Health 2021;6:e271]. Lancet Public Health. 2020;5:e672–e681.
2. Du X, Patel A, Anderson CS, et al. Epidemiology of cardiovascular disease in China and opportunities for improvement: JACC international. Am Coll Cardiol. 2019;73:3135–3147.
3. Zhang LJ, Zhao YE, Wu SY, et al. Pulmonary embolism detection with dual-energy CT: experimental study of dual-source CT in rabbits. Radiology. 2009;252:61–70.
4. Tang CX, Liu CY, Lu MJ, et al. CT FFR for ischemia-specific CAD with a new computational fluid dynamics algorithm: a Chinese multicenter study. JACC Cardiovasc Imaging. 2020;13:980–990.
5. Zhang N, Yang G, Gao Z, et al. Deep learning for diagnosis of chronic myocardial infarction on nonenhanced cardiac cine MRI. Radiology. 2019;291:606–617.
6. Li Y, Yu M, Dai X, et al. Detection of hemodynamically significant coronary stenosis: CT myocardial perfusion versus machine learning CT fractional flow reserve. Radiology. 2019;293:305–314.
7. Leiner T, Bogaert J, Friedrich MG, et al. SCMR position paper (2020) on clinical indications for cardiovascular magnetic resonance. J Cardiovasc Magn Reson. 2020;22:76.
8. Lv W, Wang Y, Zhou C, et al. Development and validation of a clinically applicable deep learning strategy (HONORS) for pulmonary nodule classification at CT: a retrospective multicentre study. Lung Cancer. 2021;155:78–86.
9. Tang CX, Zhang LJ, Xu L, et al. Cardiovascular imaging in China: yesterday, today and tomorrow. J Thorac Imaging. 2022;37:xxx–xxx.
10. Fan L, Yang WJ, Liu SY. Thoracic imaging in China: yesterday, today and tomorrow. J Thorac Imaging. 2022;37:xxx–xxx.
11. Liu ZN, Yang JJ, Chen YD. Imaging in cardiac intervention—the Chinese approach. J Thorac Imaging. 2022;37:xxx–xxx.
12. Zhang LJ, Tang CX, Xu PP, et al. Fractional flow reserve derived from coronary CT angiography: an expert consensus document of the Chinese Society of Radiology. J Thorac Imaging. 2022;37:xxx–xxx.
13. Shi H, Han X, Jiang N, et al. Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: a descriptive study. Lancet Infect Dis. 2020;20:425–434.
14. Xu Q, Zhan X, Zhou Z, et al. AI-based analysis of CT images for rapid triage of COVID-19 patients. NPJ Digit Med. 2021;4:75.
15. Zu ZY, Jiang MD, Xu PP, et al. Coronavirus disease 2019 (COVID-19): a perspective from China. Radiology. 2020;296:E15–E25.
16. Xu PP, Tian RH, Luo S, et al. Risk factors for adverse clinical outcomes with COVID-19 in China: a multicenter, retrospective, observational study. Theranostics. 2020;10:6372–6383.
17. Song F, Shi N, Shan F, et al. Emerging 2019 novel coronavirus (2019-nCoV) pneumonia. Radiology. 2020;297:E346.
18. Ni Q, Sun ZY, Qi L, et al. A deep learning approach to characterize 2019 coronavirus disease (COVID-19) pneumonia in chest CT images. Eur Radiol. 2020;30:6517–6527.
19. Xiang KY, Zu ZY, Lu GM, et al. Coronavirus disease 2019 (COVID-19): Chinese radiologists are acting. J Thorac Imaging. 2020;35:234–238.
20. Chen Q, Zu ZY, Jiang MD, et al. Infection control and management strategy for COVID-19 in the radiology department: focusing on experiences from China. Korean J Radiol. 2020;21:851–858.
Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc.