van Hamersvelt, Robbert W. http://orcid.org/0000-0002-6084-0656
Zreik, Majd
Voskuil, Michiel
Viergever, Max A.
Išgum, Ivana
Leiner, Tim
Funding for this research was provided by:
ZonMw (This work was financially supported by the project FSCAD, funded by the Netherlands Organization for Health Research and Development (ZonMw) with participation of Pie Medical imaging BV in the framework of the research program IMDI (Innovative Medical Devices Initiative); project 104003009)
Philips Healthcare (The University Medical Center Utrecht department of Radiology receives research support from Philips Healthcare.)
Article History
Received: 29 May 2018
Revised: 23 August 2018
Accepted: 2 October 2018
First Online: 12 November 2018
Compliance with ethical standards
:
: The scientific guarantor of this publication is Prof. Dr. Tim Leiner.
: Robbert W. van Hamersvelt, Majd Zreik, and Michiel Voskuil have nothing to disclose. Max A. Viergever and Ivana Išgum received Research grants from the Netherlands Organization for Scientific Research (NWO)/ Foundation for Technological Sciences (number 12726) with industrial participation (Pie Medical Imaging, 3Mensio Medical Imaging). Max A. Viergever, Ivana Išgum, and Tim Leiner received research grants from the Netherlands Organization for Health Research and Development (FSCAD, number 104003009); Research grants from Netherlands Organization for Scientific Research (NWO)/ Foundation for Technological Sciences (number P15–26) with industrial participation (Pie Medical Imaging, Philips Healthcare); and Research grants Pie Medical Imaging. Tim Leiner received research grants from Philips Healthcare and Research grants Bayer.
: No complex statistical methods were necessary for this paper.
: Written informed consent was waived by the Institutional Review Board.
: Institutional Review Board approval was obtained by our local institutional review board at the University Medical Center Utrecht in the Netherlands (protocol number 15/608).
: Some study subjects or cohorts have been previously reported in “Zreik M, Lessmann N, van Hamersvelt RW, et al (2018) Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis. Med Image Anal,” which was focused on the development of the DL algorithm. The current clinical study expands and validates on the previous study by applying a combined method of visual stenosis grading on CCTA and only applying the deep learning–based analysis to the intermediate-degree stenosis.
: • Retrospective• Diagnostic study• Performed at one institution
: The sponsors had no role in the design and conduct of the study, in the collection, analysis, interpretation of the data, and in the preparation.