Evidence map›Paper›PMID 36581216›Full record

ArticleMagnetic resonance imaging2023

Can global longitudinal strain (GLS) with magnetic resonance prognosticate early cancer therapy-related cardiac dysfunction (CTRCD) in breast cancer patients, a prospective study?

Julia Kar, Michael V Cohen, Samuel A McQuiston, Christopher M Malozzi

Open access · greenAbstract read
In one paragraph

Article in Magnetic resonance imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 9% of its field
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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Julia KarDepartments of Mechanical Engineering and Pharmacology, University of South Alabama, 150 Jaguar Drive, Mobile, AL 36688, USA. Electronic address: jkar@southalabama.edu.
Michael V CohenDivision of Cardiology, Department of Medicine, University Hospital, 2451 USA Medical Center Drive, Mobile, AL 36617, USA; Department of Physiology and Cell Biology, College of Medicine, University of South Alabama, 5851 USA Dr N, Mobile, AL 36688, USA.
Samuel A McQuistonDepartment of Radiology, University Hospital, 2451 USA Medical Center Drive, Mobile, AL 36617, USA.
Christopher M MalozziDivision of Cardiology, Department of Medicine, University Hospital, 2451 USA Medical Center Drive, Mobile, AL 36617, USA.
University of South Alabama · USUniversity of South Alabama Medical Center · US

Funding

Automated MRI-based 3D Contractility (Strain) Analysis for Detecting Subclinical Cardiotoxicity in Breast Cancer Patients Undergoing ChemotherapyR21EB028063 · NIBIB · UNIVERSITY OF SOUTH ALABAMA · PI KAR, JULIA · 2019 to 2021
$554k
NIBIB NIH HHS R21 EB028063
6 · The paper itself

Abstract

purposeTo determine if Artificial Intelligence-based computation of global longitudinal strain (GLS) from left ventricular (LV) MRI is an early prognostic factor of cancer therapy-related cardiac dysfunction (CTRCD) in breast cancer patients. The main hypothesis based on the patients receiving antineoplastic chemotherapy treatment was CTRCD risk analysis with GLS that was independent of LV ejection fraction (LVEF).

methodsDisplacement Encoding with Stimulated Echoes (DENSE) MRI was acquired on 32 breast cancer patients at baseline and 3- and 6-month follow-ups after chemotherapy. Two DeepLabV3+ Fully Convolutional Networks (FCNs) were deployed to automate image segmentation for LV chamber quantification and phase-unwrapping for 3D strains, computed with the Radial Point Interpolation Method. CTRCD risk (cardiotoxicity and adverse cardiac events) was analyzed with Cox Proportional Hazards (PH) models with clinical and contractile prognostic factors.

resultsGLS worsened from baseline to the 3- and 6-month follow-ups (-19.1 ± 2.1%, -16.0 ± 3.1%, -16.1 ± 3.0%; P < 0.001). Univariable Cox regression showed the 3-month GLS significantly associated as an agonist (hazard ratio [HR]-per-SD: 2.1; 95% CI: 1.4-3.1; P < 0.001) and LVEF as a protector (HR-per-SD: 0.8; 95% CI: 0.7-0.9; P = 0.001) for CTRCD occurrence. Bivariable regression showed the 3-month GLS (HR-per-SD: 2.0; 95% CI: 1.2-3.4; P = 0.01) as a CTRCD prognostic factor independent of other covariates, including LVEF (HR-per-SD: 1.0; 95% CI: 0.9-1.2; P = 0.9).

conclusionsThe end-point analyses proved the hypothesis that GLS is an early, independent prognosticator of incident CTRCD risk. This novel GLS-guided approach to CTRCD risk analysis could improve antineoplastic treatment with further validation in a larger clinical trial.

Indexed as

Antineoplastic AgentsBreast NeoplasmsHeart DiseasesVentricular Dysfunction, LeftArtificial IntelligenceFemaleGlobal Longitudinal StrainHumansMagnetic Resonance ImagingMagnetic Resonance SpectroscopyProspective StudiesVentricular Function, LeftAntineoplastic AgentsArtificial intelligenceCancer therapy-related cardiac dysfunctionCox proportional hazardsFully convolutional networkGlobal longitudinal strainLeft ventricular ejection fraction

Identifiers

PMID36581216
PMCPMC10292191
OpenAlexW4312143545

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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.