IMR Press / RCM / Special Issues / 1623214939202

New insight in Cardiovascular Imaging

Submission deadline: 31 December 2022
Special Issue Editors
  • Zhonghua Sun
    John Curtin Distinguished Professor and Head of Discipline, Medical Radiation Science, Curtin Medical School; Program Lead in Chronic Disease (including in Advanced Imaging), Curtin Health Innovation Research Institute (CHIRI), Faculty of Health Sciences, Curtin University, Australia
    Interests: Cardiovascular CT imaging; 3D printing of heart and cardiovascular disease; Diagostic radiation; Radiation dose optimisation; Virtual reality; Augmented reality
  • Yung-Liang Wan
    Honorable Professor of Radiology, College of Medicine, Chang Gung University Consultant Radiologist; Department of Medical Imaging and Intervention Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan
    Interests: Cardiothoracic imaging mainly in coronary CTA; Virtual intravascular endoscopy
Special Issue Information

Dear Colleagues,


We are pleased to announce the special issue “New Insight in Cardiovascular Imaging”. Cardiac imaging modalities play an increasingly important role in the diagnosis and prediction of cardiovascular disease. Advancements in these imaging modalities including echocardiography, CT, MRI and nuclear medicine including hybrid imaging have significantly improved their diagnostic accuracy which is represented in not only the morphology and structure assessment, but also the function assessment of cardiovascular disease. Further, novel imaging tools allow for early detection and quantificaiton of cardiovascular disease, thus improving the patient’s prognostic outcomes. This special issue aims to create a platform for researchers from different disciplines to share their recent research outputs on the use of latest imaging modalities in cardiovascular disease. 

Potential topics include, but not limited to:
● Quantitative assessment of cardiovascular disease using cardiac CT, MRI, echocardiography, SPECT/PET
● New diagnostic modalities including dual-energy CT for detection of extracellular volume (ECV) and shear wave imaging by ultrasound in myocardial stiffness
● Diagnostic efficacy and strategy for coronary artery disease with use of FFRCT including the use of machine learning or deep learning tools
● Tissue characterization by Cardiac MR T1 mapping in cardiovascular disease
● 3D printing in cardiovascular disease
● Virtual reality and augmented reality in cardiovascular disease

Authors are encouraged to discuss with the guest editors to determine the suitability of their intended manuscripts. Before submission authors should carefully read over the journal’s Author guidelines, which are available at Author Instructions via: 
We look forward to receiving your excellent work. 

Thank you very much!

Prof. Dr. Zhonghua Sun and Prof. Dr. Yung-Liang Wan

Guest Editors

Cardiovascular disease
Imaging modalities
Artificial intelligence
Manuscript Submission Information

Manuscripts should be submitted via our online editorial system at by registering and logging in to this website. Once you are registered, click here to start your submission. Manuscripts can be submitted now or up until the deadline. All papers will go through peer-review process. Accepted papers will be published in the journal (as soon as accepted) and meanwhile listed together on the special issue website. Research articles, reviews as well as short communications are preferred. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office to announce on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts will be thoroughly refereed through a double-blind peer-review process. Please visit the Instruction for Authors page before submitting a manuscript. The Article Processing Charge (APC) in this open access journal is 2200 USD. Submitted manuscripts should be well formatted in good English.

Published Paper (14 Papers)
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