Evidence map›Paper›PMID 42238410›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Opportunistic CT Attenuation Biomarkers of Anemia Are Associated With Impaired Myocardial Flow Reserve and Cardiovascular Outcomes.

Robert J H Miller, Aakash Shanbhag, Jirong Yi, Jacek Kwiecinski, Paul Kavanagh, Giselle Ramirez, Mark Lemley, Assiata Kamagate, Leandro Slipczuk, Mark I Travin and 18 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 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

28 authors.

Robert J H MillerArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, United States.ORCID 0000-0003-4676-2433
Aakash ShanbhagArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Jirong YiArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Jacek KwiecinskiArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Paul KavanaghArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Giselle RamirezArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Mark LemleyArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Assiata KamagateArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Leandro SlipczukCardiology Division, Montefiore Health System/Albert Einstein College of Medicine, NY, USA.ORCID 0000-0003-3091-3735
Mark I TravinDepartment of Radiology (Nuclear Medicine), Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, NY, USA.
Erick AlexandersonFaculty of Medicine, National Institute of Cardiology Ignacio Chavez, Mexico City, Mexico.
Isabel Carvajal-JuarezFaculty of Medicine, National Institute of Cardiology Ignacio Chavez, Mexico City, Mexico.
René R S PackardDivision of Cardiology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.ORCID 0000-0002-8520-5843
Mouaz Al-MallahHouston Methodist DeBakey Heart & Vascular Center, Houston Methodist Academic Institute, Houston, TX, USA.ORCID 0000-0003-2348-0484
Andrew J EinsteinDivision of Cardiology, Department of Medicine, and Department of Radiology, Columbia University Irving Medical Center and New York-Presbyterian Hospital, New York, USA.
Wanda AcampaDepartment of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy.
Stacey KnightIntermountain Medical Center Heart Institute, Intermountain Healthcare, Murray, UT, USA.
Viet T LeIntermountain Medical Center Heart Institute, Intermountain Healthcare, Murray, UT, USA.
Steve MasonIntermountain Medical Center Heart Institute, Intermountain Healthcare, Murray, UT, USA.
Samuel WoppererDepartment of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
Panithaya ChareonthaitaweeDepartment of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
Thomas L RosamondDepartment of Cardiovascular Medicine, The University of Kansas Medical Center, Kansas City, KS, USA.
Robert A DeKempDivision of Cardiology, Department of Medicine, University of Ottawa Heart Institute, ON, Canada.
Ronny R BuechelCardiovascular Imaging Program, Departments of Radiology and Medicine; Division of Nuclear Medicine and Molecular Imaging, Department of Radiology; and Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.ORCID 0000-0001-8064-8904
Daniel S BermanArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Damini DeyArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Marcelo F Di CarliArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, United States.
Piotr J SlomkaArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, United States.ORCID 0000-0002-6110-938X

Funding

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
Integrating Artificial Intelligence for Optimal Analysis of CardiacPET/CTR01EB034586 · NIBIB · CEDARS-SINAI MEDICAL CENTER · PI DI CARLI, MARCELO F, SLOMKA, PIOTR J · 2022 to 2025
$2.9M
NHLBI NIH HHS R35 HL161195NIBIB NIH HHS R01 EB034586
6 · The paper itself

Abstract

Background: Anemia is an established marker of cardiovascular disease severity and risk which leads to elevations in resting myocardial blood flow (MBF) and impaired myocardial flow reserve (MFR) in patients without obstructive coronary artery disease (CAD). Anemia can potentially be detected opportunistically from blood pool density changes on computed tomography (CT) imaging. Objectives: We evaluated relationships between chamber density measurements with hemoglobin, positron emission tomography (PET) findings, and cardiovascular events. Methods: We included 33460 patients from 13 sites in the REFINE-PET who underwent PET and 24368 patients undergoing lung cancer screening chest CT. A deep learning model segmented cardiac chambers from CT images, then quantified chamber density. We evaluated the relationship between chamber density measures with resting MBF and MFR, as well as associations with death or myocardial infarction (MI). Results: We included a total of 57,828 patients. A higher density in myocardium compared to left ventricle blood pool was associated with reduced MFR (adjusted odds ratio 3.02 per SD increase, 95% confidence interval[CI] 2.72 - 3.38) and an increased risk of death or MI in (adjusted hazard ratio[HR] 1.38 per SD increase, 95% CI 1.26-1.51). Having myocardial density higher than blood pool density was also associated with cardiovascular death in patients undergoing low-dose chest CT (adjusted HR 1.73, 95% CI 1.20-2.52). Conclusions: In a large multimodality dataset, lower cardiac chamber density is associated with impaired MFR and independently associated with cardiovascular events. These biomarkers can be automatically extracted from CT to provide physiologic insights and potentially guide patient care.

Indexed as

Anemiaartificial intelligenceCTdeep learningnuclear cardiology

Identifiers

PMID42238410
PMCPMC13228781

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.