Rationale and design of the INVICTUS Registry: (Multicenter Registry of Invasive and Non-Invasive imaging modalities to compare Coronary Computed Tomography Angiography, Intravascular Ultrasound and Optical Coherence Tomography for the determination of Severity, Volume and Type of coronary atherosclerosiS)

Rine Nakanishi, Department of Cardiovascular Medicine, Toho University Graduate School of Medicine, Toho University Omori Medical Center, Tokyo, Japan. Electronic address: rine.n@med.toho-u.ac.jp.
Ryo Okubo, Division of Cardiovascular Medicine, Department of Internal Medicine, Toho University Faculty of Medicine, Toho University Omori Medical Center, Tokyo, Japan.
Yoshihiro Sobue, Department of Cardiovascular Medicine, Gifu Heart Center, Gifu, Japan.
Umihiko Kaneko, Sapporo Cardiovascular Clinic, Hokkaido, Japan.
Hideyuki Sato, Edogawa Hospital Tokyo, Japan; Department of Cardiovascular Biology and Medicine, Juntendo University, Graduate School of Medicine, Tokyo, Japan.
Shinichiro Fujimoto, Department of Cardiovascular Biology and Medicine, Juntendo University, Graduate School of Medicine, Tokyo, Japan.
Yui Nozaki, Department of Cardiovascular Biology and Medicine, Juntendo University, Graduate School of Medicine, Tokyo, Japan.
Takashi Kajiya, Tenyoukai Central Hospital, Kagoshima, Japan.
Toru Miyoshi, Department of Cardiovascular Medicine, Dentistry and Pharmaceutical Sciences, Okayama University Graduate School of Medicine, Okayama, Japan.
Keishi Ichikawa, Department of Cardiovascular Medicine, Dentistry and Pharmaceutical Sciences, Okayama University Graduate School of Medicine, Okayama, Japan.
Mitsunori Abe, Yotsuba Circulation Clinic, Ehime, Japan.
Toshiro Kitagawa, Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, Japan.
Hiroki Ikenaga, Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical and Health Sciences, Hiroshima, Japan.
Kazuhiro Osawa, Department of General Internal Medicine 3, Kawasaki Medical School General Medical Center, Okayama, Japan; Okayama Red-Cross Hospital, Okayama, Japan.
Mike Saji, Division of Cardiovascular Medicine, Department of Internal Medicine, Toho University Faculty of Medicine, Toho University Omori Medical Center, Tokyo, Japan; Department of Cardiology, Sakakibara Heart Institute, Tokyo, Japan.
Nobuo Iguchi, Okayama Red-Cross Hospital, Okayama, Japan.
Gaku Nakazawa, Department of Cardiology, Kindai University Faculty of Medicine, Osaka, Japan.
Kuniaki Takahashi, Department of Cardiology, Tokai University, School of Medicine, Kanagawa, Japan.
Takeshi Ijich, Department of Cardiology, Tokai University, School of Medicine, Kanagawa, Japan.
Hiroshi Mikamo, Department of Cardiology, Toho University Sakura Medical Center, Chiba, Japan.
Akira Kurata, Department of Cardiology, Shikoku Cancer Center, Ehime, Japan; Department of Radiology, Ehime University Graduate School of Medicine, Ehime, Japan.
Masao Moroi, Department of Cardiovascular Medicine, Toho University Ohashi Medical Center, Tokyo, Japan.
Raisuke Iijima, Department of Cardiovascular Medicine, Toho University Ohashi Medical Center, Tokyo, Japan.
Shant Malkasian, Wayne State University School of Medicine, MI, USA.
Tami Crabtree, Cleerly Inc., CO, USA.
Daniel Chamie, Cardiovascular Medicine, Yale School of Medicine, CT, USA.
Lansky J. Alexandra, Cardiovascular Medicine, Yale School of Medicine, CT, USA.
James K. Min, Cleerly Inc., CO, USA.
James P. Earls, Cleerly Inc., CO, USA; George Washington University School of Medicine and Health Sciences, Washington DC, USA.
Hitoshi Matsuo, Department of Cardiovascular Medicine, Toho University Graduate School of Medicine, Toho University Omori Medical Center, Tokyo, Japan.

Document Type

Journal Article

Publication Date

9-5-2023

Journal

Journal of cardiovascular computed tomography

DOI

10.1016/j.jcct.2023.08.011

Keywords

Artificial intelligence; Calcified plaque; Coronary artery disease; Coronary atherosclerosis; Coronary computed tomography angiography; Intravascular ultrasound; Low density non-calcified plaque; Near infrared spectroscopy intravascular ultrasound; Non-calcified plaque; Optical coherence tomography

Abstract

BACKGROUND: Coronary CT angiography (CCTA) is a first-line noninvasive imaging modality for evaluating coronary artery disease (CAD). Recent advances in CCTA technology enabled semi-automated detection of coronary arteries and atherosclerosis. However, there have been to date no large-scale validation studies of automated assessment of coronary atherosclerosis phenotype and coronary artery dimensions by artificial intelligence (AI) compared to current standard invasive imaging. METHODS: INVICTUS registry is a multicenter, retrospective, and prospective study designed to evaluate the dimensions of coronary arteries, as well as the characteristic, volume, and phenotype of coronary atherosclerosis by CCTA, compared with the invasive imaging modalities including intravascular ultrasound (IVUS), near-infrared spectroscopy (NIRS)-IVUS and optical coherence tomography (OCT). All patients clinically underwent both CCTA and invasive imaging modalities within three months. RESULTS: Patients data are sent to the core-laboratories to analyze for stenosis severity, plaque characteristics and volume. The variables for CCTA are measured using an AI-based automated software and assessed independently with the variables measured at the imaging core laboratories for IVUS, NIRS-IVUS, and OCT in a blind fashion. CONCLUSION: The INVICTUS registry will provide new insights into the diagnostic value of CCTA for determining coronary atherosclerosis phenotype and coronary artery dimensions compared to IVUS, NIRS-IVUS, and OCT. Our findings will potentially shed new light on precision medicine informed by an AI-based coronary CTA assessment of coronary atherosclerosis burden, composition, and severity. (ClinicalTrials.gov: NCT04066062).

Department

Radiology

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