Evidence map›Paper›PMID 42592031›Full record

ArticleEuropean heart journal. Imaging methods and practice2026

Peak exercise-to-recovery changes in biventricular volumes and function assessed by exercise cardiovascular magnetic resonance.

Alexander Schulz, Nicole C Y Deng, Marcelline Lopes, Long Ngo, Kathryn Arcand, Warren J Manning, Reza Nezafat

Abstract read
In one paragraph

Article in European heart journal. Imaging methods and practice, 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

7 authors.

Alexander SchulzDepartment of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA 02215, USA.ORCID https://orcid.org/0000-0001-5589-8792
Nicole C Y DengDepartment of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA 02215, USA.ORCID https://orcid.org/0009-0000-2581-7015
Marcelline LopesDepartment of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA 02215, USA.ORCID https://orcid.org/0009-0000-5627-2345
Long NgoDepartment of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA 02215, USA.ORCID https://orcid.org/0000-0002-8903-9352
Kathryn ArcandDepartment of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA 02215, USA.ORCID https://orcid.org/0009-0006-1903-4042
Warren J ManningDepartment of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA 02215, USA.
Reza NezafatDepartment of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA 02215, USA.ORCID https://orcid.org/0000-0002-1963-7138

Funding

Harvard Clinical and Translational Science CenterUM1TR004408 · NCATS · HARVARD MEDICAL SCHOOL · PI Lindsey Robert Baden, Lee Marshall Nadler · 2023 to 2026
$43.3M
Cardiopulmonary Exercise MRI in Heart Failure with Preserved Ejection FractionR01HL158077 · NHLBI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI NEZAFAT, REZA · 2021 to 2025
$3.7M
Unraveling The Mechanism of Heart Failure in Hypertrophic Cardiomyopathy with Exercise CMRR01HL177076 · NHLBI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI Martin S Maron, Reza Nezafat · 2025 to 2026
$1.5M
NCATS NIH HHS UM1 TR004408NHLBI NIH HHS R01 HL158077NHLBI NIH HHS R01 HL177076
6 · The paper itself

Abstract

Aims: Exercise cardiovascular magnetic resonance (Ex-CMR) assesses cardiac function under physiological stress. Imaging during continuous in-bore exercise reflects peak physiology but is challenging, prone to motion artefacts and patient discomfort. Exercise performed outside the scanner followed by rapid post-exercise imaging improves feasibility and image quality, but the time course of ventricular volume recovery after exercise cessation remains poorly defined. We compared biventricular Ex-CMR measurements during steady-state peak exercise with those acquired sequentially after exercise termination. Methods and results: Ten healthy adults [24 (21-31) years; 8 female] underwent Ex-CMR on a 3T system. Biventricular volumes were assessed using a free-breathing, electrocardiogram-triggered, highly accelerated multi-slice cine sequence with compressed sensing and deep learning-based reconstruction. Short-axis stacks were acquired at rest, during two steady-state peak exercise acquisitions, and at three sequential post-exercise timepoints, with the first recovery scan beginning 10-15 s after cessation. Linear mixed-effects models evaluated recovery categorically and as a function of elapsed time. Differences between repeated peak acquisitions were small [left ventricular (LV) end-diastolic volume +1 ± 3 mL; LV end-systolic volume -4 ± 7 mL]. Immediately after cessation (13 ± 2 s), biventricular volumes remained unchanged vs. peak (all Conclusion: Biventricular volumes measured immediately after exercise closely approximate peak physiology, whereas recovery changes occur rapidly and linearly thereafter. Rapid post-exercise acquisition offers a practical surrogate for peak measurements while improving image quality.

Indexed as

biventricular volumesexercise CMRleft ventricular functionpost-exercise recoveryright ventricular function

Identifiers

PMID42592031
PMCPMC13463763

What OpenQuestion holds

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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.