Evidence map›Paper›PMID 41656475›Full record

ArticleThe international journal of cardiovascular imaging2026

Sex differences in hemodynamics and remodeling patterns uncovered by automated Machine-Learning 3D echocardiography in aortic stenosis with preserved ejection fraction.

Andrea Barbieri, Vera Laus, Francesca Mantovani, Francesca Bursi, Niccolò Bonini, Silvia Bonatti, Benedetta Cherubini, Mattia Malaguti, Matteo Paolini, Marie-Annick Clavel and 1 more

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in The international journal of cardiovascular imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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.

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3 · Its place in the literature

Who cites it

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Andrea BarbieriCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, Policlinico di Modena, University of Modena and Reggio Emilia, Modena, 41124, Italy.
Vera LausCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, Policlinico di Modena, University of Modena and Reggio Emilia, Modena, 41124, Italy.
Francesca MantovaniCardiology Division, Azienda USL, IRCCS di Reggio, Emilia, Italy. Francy_manto@hotmail.com.
Francesca BursiDepartment of Health Sciences, Division of Cardiology, San Paolo Hospital, ASST Santi Paolo e Carlo, University of Milan, Milan, Italy.
Niccolò BoniniCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, Policlinico di Modena, University of Modena and Reggio Emilia, Modena, 41124, Italy.
Silvia BonattiCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, Policlinico di Modena, University of Modena and Reggio Emilia, Modena, 41124, Italy.
Benedetta CherubiniCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, Policlinico di Modena, University of Modena and Reggio Emilia, Modena, 41124, Italy.
Mattia MalagutiCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, Policlinico di Modena, University of Modena and Reggio Emilia, Modena, 41124, Italy.
Matteo PaoliniCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, Policlinico di Modena, University of Modena and Reggio Emilia, Modena, 41124, Italy.
Marie-Annick ClavelInstitut Universitaire de Cardiologie et Pneumologie de Québec (Quebec Heart & Lung Institute), Université Laval, Québec, Canada.
Giuseppe BorianiCardiology Division, Department of Biomedical, Metabolic and Neural Sciences, Policlinico di Modena, University of Modena and Reggio Emilia, Modena, 41124, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Women with aortic stenosis (AS) are underdiagnosed and undertreated compared to men and face a higher mortality risk despite similar symptoms and fewer comorbidities. Sex-specific differences in left ventricular (LV) remodeling may contribute to this disparity. We investigated whether a fully automated, machine-learning-based three-dimensional echocardiography (3DE) approach, the Dynamic Heart Model (DHM), improves the detection of these differences compared to conventional two-dimensional echocardiography (2DE). This study investigates sex-related differences in cardiac remodeling and hemodynamics in AS patients with a preserved ejection fraction (EF ≥ 50%), comparing results from 2D echocardiography (2DE) and 3D echocardiography (3DE) via the DHM. The study included 101 consecutive patients with AS (42% women) who were assessed with 2DE and DHM. Parameters such as LV volumes, mass (LVM), stroke volume (SV), and aortic valve area (AVA) were measured and indexed to body surface area (BSA). Sex-specific differences were analyzed, with a focus on identifying significant remodeling patterns. Women exhibited smaller LV end-diastolic volume (EDV) and end-systolic volume (ESV) by DHM compared to men (115 mL vs. 155 mL, p < 0.001; 51 mL vs. 66 mL, p < 0.001). Indexed EDV (EDVi) and ESV (ESVi) were also significantly lower in women (69 mL/m² vs. 84 mL/m², p < 0.001; 30 mL/m² vs. 34 mL/m², p = 0.002). LVM and indexed LV mass (LVMi) were significantly lower in women when measured by DHM (131 g vs. 163 g, p < 0.001; 75 g/m² vs. 89 g/m², p = 0.005), whereas 2DE did not reveal statistically significant differences. Women exhibited a more concentric LV geometry, as reflected by higher relative wall thickness than men (0.42 vs. 0.36; p = 0.04). Despite similar hemodynamic parameters, women had significantly smaller DHM-derived AVA (0.90 cm² vs. 1.20 cm², p < 0.001), correlating with reduced SV (64 mL vs. 90 mL, p < 0.001). This study highlights that significant sex-related differences in LV remodeling and AS severity are better captured by DHM than 2DE, emphasizing the importance of sex-specific considerations and accurate measurements in evaluating and managing AS.

Indexed as

Aortic ValveAortic Valve StenosisEchocardiography, Three-DimensionalHealth Status DisparitiesHemodynamicsImage Interpretation, Computer-AssistedMachine LearningStroke VolumeVentricular Function, LeftVentricular RemodelingAgedAged, 80 and overAutomationFemaleHumansMale3D echocardiographyAortic stenosisArtificial intelligenceDynamic heart modelMachine learning

Identifiers

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Read underepoch 390

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.