{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T04:57:27Z","timestamp":1787893047012,"version":"build-2784847793"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T00:00:00Z","timestamp":1772668800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T00:00:00Z","timestamp":1772668800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Cleerly Inc."},{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["22K08216"],"award-info":[{"award-number":["22K08216"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"name":"NIH T32 Clinician-Scientist Training Program","award":["EB005970"],"award-info":[{"award-number":["EB005970"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eur Radiol"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Automated artificial intelligence (AI)-based assessment of atherosclerosis burden applied to coronary computed tomography angiography (CCTA) can optimize image processing times, standardize interpretation, and minimize inter-observer variability. We investigated the diagnostic utility of AI-based CCTA quantification (AI-QCT) of coronary atherosclerosis in coronary segments co-registered with intravascular ultrasound (IVUS) of diseased and non-diseased segments.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and methods<\/jats:title>\n                    <jats:p>Patients who underwent CCTA and IVUS in the INVICTUS registry (ClinicalTrials.gov: NCT04066062) were enrolled. Images were analyzed by independent core laboratories blinded to each modality\u2019s findings. Vessel external elastic membrane (EEM), lumen, plaque volumes, plaque burden, and percent atheroma volume (PAV) were quantified in whole co-registered segments and subsegments containing non-calcified and low-attenuation plaques. A calcium index was calculated for the whole co-registered segment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 108 vessels from 85 patients were included. Pearson\u2019s correlation demonstrated strong associations between AI-QCT and IVUS in quantifying the EEM volume (r\u2009=\u20090.899), lumen volume (r\u2009=\u20090.943), and plaque volume (r\u2009=\u20090.833), length-normalized PAV (r\u2009=\u20090.851), and calcium index (r\u2009=\u20090.960) in the whole-segment analysis. Strong correlations were seen for vessel, lumen, and plaque volumes in non-calcified (Pearson\u2019s coefficient: 0.95, 0.97, and 0.83, respectively) and low-attenuation (Pearson\u2019s coefficient: 0.90, 0.86, and 0.86, respectively) plaque segments. The minimum lumen area was 0.61\u2009\u00b1\u20091.18 mm\n                      <jats:sup>2<\/jats:sup>\n                      (95% CI, \u22120.83 to \u22120.38) smaller by AI-QCT than IVUS, with a similar lumen area stenosis (mean difference, 1.26\u2009\u00b1\u200924.17; 95% CI, \u22123.37 to 5.90).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>AI-QCT quantification of atherosclerosis burden showed high correlations and close agreement with IVUS in whole-segment and segments with non-calcified and low-attenuation plaques.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Key Points<\/jats:title>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Question<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>Coronary atheroma burden is a powerful predictor of cardiovascular events. Can AI-based coronary CT angiography (CCTA) accurately quantify atherosclerotic burden across the full disease spectrum\u00a0when compared with\u00a0intravascular ultrasound (IVUS)?<\/jats:italic>\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Findings<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>AI-based CCTA quantification (AI-QCT) showed strong correlations with IVUS for plaque volume, burden, and calcium across whole coronary segments, including non-calcified and low-attenuation plaques.<\/jats:italic>\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Clinical relevance<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>AI-QCT provides rapid, automatic, and accurate atherosclerosis quantification without reader-dependent variability, enabling standardized cardiovascular risk assessment, treatment monitoring, and therapeutic decision-making across all disease severity spectrum in routine clinical practice.<\/jats:italic>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00330-026-12412-y","type":"journal-article","created":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T23:02:06Z","timestamp":1772665326000},"page":"5364-5377","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Artificial intelligence-based coronary computed tomography angiography quantification of atherosclerosis burden: comparison with intravascular ultrasound in the INVICTUS 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Ryo Okubo: None. Hitoshi Matsuo: Speakers\u2019 bureau of Abbott Vascular, Philips, HeartFlow, Amgen, and Zeon Medical. Yoshihiro Sobue: None. Umihiko Kaneko: None. Hideyuki Sato: None. Shinichiro Fujimoto: None. Yui Nozaki: None. Takashi Kajiya: None. Toru Miyoshi: None. Keishi Ichikawa: None. Mitsunori Abe: None. Toshiro Kitagawa: None. Hiroki Ikenaga: None. Kazuhiro Osawa: None. Mike Saji: None. Nobuo Iguchi: None. Gaku Nakazawa: Speaker fees from Boston Scientific, Abbott Medical, Terumo Corp, and HeartFlow Japan. Kuniaki Takahashi: None. Takeshi Ijichi: Speakers\u2019 bureau\u2014Novartis Pharma, AstraZeneca, and Bayer Pharma. Hiroshi Mikamo: None. Akira Kurata: Member of the Scientific Editorial Board of\n                      European Radiology\n                      and, as such, did not participate in the selection or review processes for this article. Masao Moroi: None. Raisuke Iijima: None. Daniel Bandeira: None. Abigail Demuyakor: None. Helen Parise: None. Shant Malkasian: Consultant for and equity interest in Cleerly Inc. Gary S. Mintz: Honoraria\u2014Boston Scientific. Alexandra J. Lansky: None. James P. Earls: Consultant for and equity interest in Cleerly Inc. Daniel Chami\u00e9: Consulting and speaker fees from Boston Scientific.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Statistical analysis of the current work was performed at Yale University, under the leadership of Helen Parise, ScD, who is a co-author of this manuscript.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Statistics and biometry"}},{"value":"All prospective patients provided written informed consent. For retrospective cases, opt-out forms were posted on each facility\u2019s website and\/or local sites to inform patients who did not wish their information included in the study.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki and was approved by the Ethics Committee of Toho University Omori Medical Center (M24009_22063_21054_19012). It was prospectively registered at ClinicalTrials.gov (NCT04066062).","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"None of the study subjects or cohorts has been previously reported.","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Study subjects or cohorts overlap"}},{"order":8,"name":"Ethics","group":{"name":"EthicsHeading","label":"Methodology"}}]}}