Evidence map›Paper›PMID 39932640›Full record

ReviewCurrent cardiology reports2025

Integration and Potential Applications of Cardiovascular Computed Tomography in Cardio-Oncology.

Muhammed Ibrahim Erbay, Venkat Sanjay Manubolu, Ashley F Stein-Merlob, Maros Ferencik, Mamas A Mamas, Juan Lopez-Mattei, Lauren A Baldassarre, Matthew J Budoff, Eric H Yang

Abstract readReview
In one paragraph

Review in Current cardiology reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

9 authors.

Muhammed Ibrahim ErbayLundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA.
Venkat Sanjay ManuboluLundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA.
Ashley F Stein-MerlobUCLA Cardio-Oncology Program, Division of Cardiology, Department of Medicine, University of California at Los Angeles, Los Angeles, USA.
Maros FerencikKnight Cardiovascular Institute, Oregon Health and Science University, Portland, OR, USA.
Mamas A MamasKeele Cardiovascular Research Group, Keele University, Keele, UK.
Juan Lopez-MatteiLee Health Heart Institute, Fort Myers, FL, USA.
Lauren A BaldassarreSection of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT, USA.
Matthew J BudoffLundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, USA.
Eric H YangUCLA Cardio-Oncology Program, Division of Cardiology, Department of Medicine, University of California at Los Angeles, Los Angeles, USA. ehyang@mednet.ucla.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewCardiovascular computed tomography (CCT) is a versatile, readily available, and non-invasive imaging tool with high-resolution capabilities in many cardiovascular diseases (CVD). Our review explains the increased risk of CVD among patients with cancer due to chemoradiotherapies, shared risk factors and cancer itself and explores the expanding role of CCT in the detection, surveillance, and management of numerous CVD among these patients. RECENT

findingsRecent research has highlighted the versatility and enhanced resolution capabilities of CCT in assessing a wide range of cardiovascular diseases. Early detection of cardiac changes and monitoring of disease progression in asymptomatic patients with cancer may lessen the severity of CVD. It offers an essential means to assess for coronary artery disease when patients are either unable to safely undergo stress testing for ischemia evaluation or at risk of complications from invasive coronary angiography. Furthermore, CCT extends its utility to valvular diseases, cardiomyopathies, pericardial diseases, cardiac masses, and radiation-induced cardiovascular diseases, allowing for a comprehensive, noninvasive assessment of the entire spectrum of cancer treatment associated CVD. Looking to the future, the integration of artificial intelligence and machine learning algorithms holds potential for automated image interpretation, improved precision and earlier detection of subclinical cardiac deterioration, allowing opportunities for earlier intervention and disease prevention. CCT is a useful imaging modality for assessing the myriad cardiovascular manifestations of diseases such as coronary artery disease, cardiomyopathies, pericardial disesaes, cardiac masses and radiation-induced cardiovascular diseases. CCT has several advantages. Readily available non-cardiac chest CT scans of patients with cancer may help with improved cardiovascular care, enhanced ASCVD risk stratification and toxicity surveillance.

Indexed as

Cardiovascular DiseasesNeoplasmsTomography, X-Ray ComputedArtificial IntelligenceCardio-OncologyCoronary Artery DiseaseHumansMedical OncologyCardio-oncologyCardiovascular computed tomographyCoronary artery calcium scoreCoronary artery diseaseRisk stratification

Identifiers

PMID39932640
PMCPMC11814013

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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.