Kikuchi, Yoshitomo
Togao, Osamu
Kikuchi, Kazufumi
Momosaka, Daichi
Obara, Makoto
Van Cauteren, Marc
Fischer, Alexander
Ishigami, Kousei
Hiwatashi, Akio http://orcid.org/0000-0001-5400-5083
Funding for this research was provided by:
japan society for the promotion of science (21K07645)
Article History
Received: 26 June 2021
Revised: 12 October 2021
Accepted: 18 October 2021
First Online: 7 January 2022
Declarations
:
: The scientific guarantor of this publication is Associate Professor Akio Hiwatashi, MD, PhD, from the Department of Clinical Radiology, Graduate School of Medical Sciences, Kyushu University (hiwatashi.akio.428@m.kyushu-u.ac.jp).
: The authors of this manuscript declare relationships with the following companies: Philips Japan and Philips Healthcare. The authors of this manuscript declare that MO is an employee of Philips Japan and MVC and AF are employee of Philips Healthcare. They were not involved in data analysis in this study.
: 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.
: There is an overlap with previous publication (Kikuchi K, Hiwatashi A, Togao O, et al 3D MR Sequence Capable of Simultaneous Image Acquisitions with and without Blood Vessel Suppression: Utility in Diagnosing Brain Metastases. Eur Radiol 2015;25:901–910.) We compared the diagnostic ability of the newly developed brain metastasis diagnosing system with deep learning and that of the previous observer test in this publication.
: • retrospective• diagnostic or prognostic study• performed at one institution