Evidence map›Paper›PMID 42389791›Full record

ArticleCirculation. Cardiovascular imaging2026

Automated AI-Based Aortic Measurements From Attenuation Correction CT as an Adjunctive Cardiovascular Risk Biomarker: An International Multicenter Study.

Anna M Marcinkiewicz, Aakash Shanbhag, Panithaya Chareonthaitawee, Wenhao Zhang, Hasanian Al-Jilaihawi, Ryan Zaid, Sebastien Cadet, Giselle Ramirez, Mark Lemley, Jirong Yi and 22 more

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Circulation. Cardiovascular imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

32 authors.

Anna M Marcinkiewicz *Artificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA (A.M.M., A.S., W.Z., H.A.-J., R.Z., S.C., G.R., M.L., J.Y., W.H., V.B., J.X.L., D.S.B., D.D., R.J.H.M., P.J.S.).ORCID 0000-0001-9769-1757
Aakash Shanbhag *Artificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA (A.M.M., A.S., W.Z., H.A.-J., R.Z., S.C., G.R., M.L., J.Y., W.H., V.B., J.X.L., D.S.B., D.D., R.J.H.M., P.J.S.).ORCID 0000-0001-5199-3071
Panithaya ChareonthaitaweeDepartment of Cardiovascular Medicine, Mayo Clinic, Rochester, MN (P.C., S.B.W.).ORCID 0000-0002-3811-8712
Wenhao ZhangArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA (A.M.M., A.S., W.Z., H.A.-J., R.Z., S.C., G.R., M.L., J.Y., W.H., V.B., J.X.L., D.S.B., D.D., R.J.H.M., P.J.S.).
Hasanian Al-JilaihawiArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA (A.M.M., A.S., W.Z., H.A.-J., R.Z., S.C., G.R., M.L., J.Y., W.H., V.B., J.X.L., D.S.B., D.D., R.J.H.M., P.J.S.).ORCID 0000-0002-8397-9431
Ryan ZaidArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA (A.M.M., A.S., W.Z., H.A.-J., R.Z., S.C., G.R., M.L., J.Y., W.H., V.B., J.X.L., D.S.B., D.D., R.J.H.M., P.J.S.).ORCID 0009-0003-9162-0204
Sebastien CadetArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA (A.M.M., A.S., W.Z., H.A.-J., R.Z., S.C., G.R., M.L., J.Y., W.H., V.B., J.X.L., D.S.B., D.D., R.J.H.M., P.J.S.).ORCID 0000-0002-9567-6438
Giselle RamirezArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA (A.M.M., A.S., W.Z., H.A.-J., R.Z., S.C., G.R., M.L., J.Y., W.H., V.B., J.X.L., D.S.B., D.D., R.J.H.M., P.J.S.).ORCID 0009-0004-3730-5075
Mark LemleyArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA (A.M.M., A.S., W.Z., H.A.-J., R.Z., S.C., G.R., M.L., J.Y., W.H., V.B., J.X.L., D.S.B., D.D., R.J.H.M., P.J.S.).ORCID 0000-0002-1531-880X
Jirong YiArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA (A.M.M., A.S., W.Z., H.A.-J., R.Z., S.C., G.R., M.L., J.Y., W.H., V.B., J.X.L., D.S.B., D.D., R.J.H.M., P.J.S.).ORCID 0000-0002-3106-4715
Waseem HijaziArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA (A.M.M., A.S., W.Z., H.A.-J., R.Z., S.C., G.R., M.L., J.Y., W.H., V.B., J.X.L., D.S.B., D.D., R.J.H.M., P.J.S.).ORCID 0000-0003-1511-9605
Valerie BuiloffArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA (A.M.M., A.S., W.Z., H.A.-J., R.Z., S.C., G.R., M.L., J.Y., W.H., V.B., J.X.L., D.S.B., D.D., R.J.H.M., P.J.S.).ORCID 0009-0006-4838-3700
Joanna X LiangArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA (A.M.M., A.S., W.Z., H.A.-J., R.Z., S.C., G.R., M.L., J.Y., W.H., V.B., J.X.L., D.S.B., D.D., R.J.H.M., P.J.S.).
Vinicius F CalsavaraDepartment of Computational Biomedicine, Biostatistics Shared Resource, Cedars-Sinai Medical Center, Los Angeles, CA (V.F.C.).ORCID 0000-0003-2332-5863
Andrew J EinsteinDivision of Cardiology, Department of Medicine, and Department of Radiology, Columbia University Irving Medical Center and New York-Presbyterian Hospital (A.J.E.).ORCID 0000-0003-2583-9278
Edward J MillerSection of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT (E.J.M., A.F.).ORCID 0000-0002-2156-5962
Attila FeherSection of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT (E.J.M., A.F.).ORCID 0000-0002-2561-4282
Terrence D RuddyDivision of Cardiology, University of Ottawa Heart Institute, Ontario, Canada (T.D.R.).ORCID 0000-0002-0686-5449
Viet T LeIntermountain Medical Center Heart Institute, Intermountain Health, Murray, UT (V.T.L., S.M., S.K.).ORCID 0000-0001-6659-5332
Steve MasonIntermountain Medical Center Heart Institute, Intermountain Health, Murray, UT (V.T.L., S.M., S.K.).
Stacey KnightIntermountain Medical Center Heart Institute, Intermountain Health, Murray, UT (V.T.L., S.M., S.K.).ORCID 0000-0003-0092-7327
Erick AlexandersonDepartment of Nuclear Cardiology, National Institute of Cardiology Ignacio Chavez, Mexico (E.A., I.C.-J.).
Isabel Carvajal-JuarezDepartment of Nuclear Cardiology, National Institute of Cardiology Ignacio Chavez, Mexico (E.A., I.C.-J.).ORCID 0000-0001-8764-6012
Leandro SlipczukDivision of Nuclear Medicine, Department of Radiology and Division of Cardiology, Montefiore Medical Center and the Albert Einstein College of Medicine, Bronx, NY (L.S., M.I.T.).ORCID 0000-0003-3091-3735
Mark I TravinDivision of Nuclear Medicine, Department of Radiology and Division of Cardiology, Montefiore Medical Center and the Albert Einstein College of Medicine, Bronx, NY (L.S., M.I.T.).ORCID 0000-0003-0968-2143
Thomas L RosamondDepartment of Cardiovascular Medicine, The University of Kansas Medical Center, Kansas City (T.L.R.).ORCID 0009-0000-1417-8342
Samuel B WoppererDepartment of Cardiovascular Medicine, Mayo Clinic, Rochester, MN (P.C., S.B.W.).ORCID 0009-0001-4281-629X
Daniel S BermanArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA (A.M.M., A.S., W.Z., H.A.-J., R.Z., S.C., G.R., M.L., J.Y., W.H., V.B., J.X.L., D.S.B., D.D., R.J.H.M., P.J.S.).ORCID 0000-0002-3793-9578
Damini DeyArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA (A.M.M., A.S., W.Z., H.A.-J., R.Z., S.C., G.R., M.L., J.Y., W.H., V.B., J.X.L., D.S.B., D.D., R.J.H.M., P.J.S.).ORCID 0000-0003-2236-6970
Marcelo F Di CarliDivision of Nuclear Medicine and Molecular Imaging, Department of Radiology, Brigham and Women's Hospital, Boston, MA (M.F.D.C.).ORCID 0000-0003-3119-025X
Robert J H MillerArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA (A.M.M., A.S., W.Z., H.A.-J., R.Z., S.C., G.R., M.L., J.Y., W.H., V.B., J.X.L., D.S.B., D.D., R.J.H.M., P.J.S.).ORCID 0000-0003-4676-2433
Piotr J SlomkaArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA (A.M.M., A.S., W.Z., H.A.-J., R.Z., S.C., G.R., M.L., J.Y., W.H., V.B., J.X.L., D.S.B., D.D., R.J.H.M., P.J.S.).ORCID 0000-0002-6110-938X

Funding

Quantitative Prediction of Disease and Outcomes from Next Generation SPECT and CTR01HL089765 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI SLOMKA, PIOTR J · 2007 to 2021
$6.1M
Patient-specific Outcome Prediction from Cardiovascular Multimodality Imaging by Artificial IntelligenceR35HL161195 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI Piotr J Slomka · 2022 to 2026
$5.0M
NHLBI NIH HHS R01 HL089765NHLBI NIH HHS R35 HL161195
6 · The paper itself

Abstract

backgroundAortic enlargement is a powerful predictor of dissection and rupture, yet it is rarely evaluated during routine myocardial perfusion imaging, despite the widespread availability of computed tomography (CT) attenuation correction scans. The aim of this study was to determine whether fully automated, opportunistically derived, artificial intelligence-based aortic measurements from myocardial perfusion imaging CT attenuation correction scans are associated with adverse outcomes in a large multicenter cohort.

methodsCT attenuation correction scans from patients undergoing positron emission tomography/CT and single-photon emission CT/CT myocardial perfusion imaging across 10 centers were included. A deep learning model automatically segmented the thoracic aorta, and a postprocessing algorithm extracted maximum ascending and descending diameters. The aortic size index was calculated by indexing the diameter to body surface area.

resultsA total of 29 339 patients (56% men; median age, 66 years [interquartile range, 58-75 years]) were included. Over a median follow-up of 3.5 years (interquartile range, 1.9-5.0 years), 5083 (17.3%) patients died. Median ascending and descending aortic size index values were 1.8 cm/m

conclusionsArtificial intelligence can unlock previously unused information within routine myocardial perfusion imaging CT attenuation correction scans by rapidly and automatically quantifying aortic size at scale. Opportunistic aortic measurements derived from CT attenuation correction may serve as an adjunctive risk biomarker and could add prognostic value to standard myocardial perfusion imaging without additional imaging or radiation.

Indexed as

Aorta, ThoracicAortographyArtificial IntelligenceComputed Tomography AngiographyMyocardial Perfusion ImagingRadiographic Image Interpretation, Computer-AssistedAgedAutomationFemaleHumansMaleMiddle AgedPredictive Value of TestsPrognosisRetrospective StudiesRisk Assessmentaortaartificial intelligencebiomarkersperfusiontomography

Identifiers

PMID42389791
PMCPMC13489667

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.