Evidence map›Paper›PMID 41902398›Full record

ArticleEuropean heart journal. Cardiovascular Imaging2026

Mechanical dyssynchrony and septal-lateral perfusion heterogeneity predict adverse left ventricular remodelling beyond ECG-defined LBBB.

Simone Cristina Soares Brandão, Lee Joseph, Jenifer M Brown, Diana Lopez, Mark Lemley, Giselle Ramirez, Paul Kavanagh, Serge D Van Kriekinge, Joanna Liang, Valerie Builoff and 17 more

Abstract read
In one paragraph

Article in European heart journal. Cardiovascular Imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

27 authors.

Simone Cristina Soares BrandãoDivision of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.ORCID 0000-0001-9899-1612
Lee JosephDivision of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Jenifer M BrownDivision of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Diana LopezDivision of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Mark LemleyArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Giselle RamirezArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Paul KavanaghArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, USA.ORCID 0000-0002-2242-1936
Serge D Van KriekingeArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Joanna LiangArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Valerie BuiloffArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Sanjay DivakaranDivision of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.ORCID 0000-0003-0598-6502
Brittany WeberDivision of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.ORCID 0000-0002-0177-2091
Jon HainerDivision of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.ORCID 0000-0002-0572-912X
Sylvain CarreDivision of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Ron BlanksteinDivision of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.ORCID 0000-0002-8393-6562
Sharmila DorbalaDivision of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Viet T LeIntermountain Medical Center Heart Institute, Intermountain Healthcare, Murray, UT, USA.
Steve MasonIntermountain Medical Center Heart Institute, Intermountain Healthcare, Murray, UT, USA.
Stacey KnightIntermountain Medical Center Heart Institute, Intermountain Healthcare, Murray, UT, USA.
Panithaya ChareonthaitaweeDepartment of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
Samuel WoppererDepartment of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
Thomas L RosamondDepartment of Cardiovascular Medicine, The University of Kansas Medical Center, Kansas City, KS, USA.
Daniel S BermanArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Damini DeyArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, USA.ORCID 0000-0003-2236-6970
Marcelo F Di CarliDivision of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.ORCID 0000-0003-3119-025X
Piotr J SlomkaArtificial Intelligence in Medicine Research Center, Departments of Biomedical Sciences, Medicine, and Cardiology, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Daniel M HuckDivision of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.ORCID 0000-0003-4221-8078

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
Cardiac Perfusion, Structure, and Function across the Primary Aldosteronism SpectrumK23HL159279 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI Jenifer Michelle Brown · 2022 to 2026
$1.0M
Interplay of Inflammation, Angiogenesis, and Coronary Microvascular Perfusion in Advanced Kidney DiseaseK23HL171893 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI Daniel Michael Huck · 2025 to 2026
$388k
American Heart Association Career Development 21CDA851511American Heart Association Career Development 21CDA852429American Heart Association Career Development Award 23CDA1037589ASNC IANC Research AwardMaster Clinician Scholar AwardNHLBI NIH HHS K23 HL171893NHLBI NIH HHS R35 HL161195NIBIB NIH HHS R01 EB034586NIH/National Heart Lung and Blood Institute R35HL161195NIH/National Heart Lung and Blood Institute K23 HL159276-01NIH/National Heart Lung and Blood Institute K23 K23HL159279NIH/National Institute of Biomedical Imaging and Bioengineering R01EB034586NIH/NHLBI K23 K23HL171893
6 · The paper itself

Abstract

aimsLeft bundle branch block (LBBB) is associated with mechanical dyssynchrony, heterogeneous perfusion, and adverse left ventricular (LV) remodelling. However, not all patients with LBBB develop cardiomyopathy, and dyssynchrony can occur without conduction defects. The role of microvascular dysfunction remains uncertain. We aimed to assess how mechanical dyssynchrony and perfusion heterogeneity relate to LV remodelling and function in patients with and without LBBB. METHODS AND

resultsWe analysed 233 patients with LBBB and 932 matched controls who underwent PET myocardial perfusion imaging, assessing mechanical dyssynchrony (phase entropy), LV volumes, and ejection fraction (EF); coronary vascular resistance (CVR), myocardial blood flow (MBF), myocardial flow reserve (MFR) as markers of microvascular function; and septal-to-lateral MBF ratio (SLR) as a measure of regional perfusion heterogeneity. Compared with controls, LBBB patients had greater dyssynchrony (56% vs. 40%), larger LV volumes, and lower EF (54% vs. 67%) (all P < 0.001), as well as higher stress CVR (37 vs. 34 mmHg/mL·min-1·g-1), and lower MBF (2.4 vs. 2.6 mL/min/g), MFR (2.4 vs. 2.6), and SLR (0.95 vs. 1.00) (all P < 0.05). Among patients with dyssynchrony, SLR <1.0 identified greater remodelling. In multivariable regression, phase entropy and SLR independently predicted LV volumes and EF, with adverse effects of SLR reduction amplified in LBBB (interaction P < 0.01). In Cox analysis, phase entropy (HR:1.02, P = 0.01), MFR (HR:0.62, P < 0.001), and LVEF (HR:0.97, P < 0.001) were independently associated with death or heart failure hospitalization, whereas LBBB was not.

conclusionMechanical dyssynchrony and perfusion heterogeneity independently predict adverse LV remodelling, irrespective of LBBB. Integrated imaging improves cardiomyopathy stratification.

Indexed as

Bundle-Branch BlockElectrocardiographyMyocardial Perfusion ImagingVentricular Dysfunction, LeftVentricular RemodelingAgedCase-Control StudiesCoronary CirculationFemaleGlobal Longitudinal StrainHumansMaleMiddle AgedPositron-Emission TomographyPredictive Value of TestsPrognosisleft bundle branch blockmechanical dyssynchronymicrovascular dysfunctionPETphase entropy

Identifiers

PMID41902398
PMCPMC13082457

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