Evidence map›Paper›PMID 42388419›Full record

ArticleEuropean heart journal. Digital health2026

Fully automated artificial intelligence-based echocardiographic analysis for global longitudinal strain monitoring and cancer therapy-related cardiac dysfunction detection in breast cancer patients.

Yoshihito Saijo, Robert Zheng, Yuichiro Okushi, Yuka Nomura, Yukina Hirata, Hiroaki Inoue, Hirotsugu Yamada, Kenya Kusunose, Masataka Sata

Abstract read
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Article in European heart journal. Digital health, 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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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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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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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

9 authors.

Yoshihito SaijoDepartment of Cardiovascular Medicine, Tokushima University Hospital, 2-50-1, Kuramoto-cho, Tokushima 7708503, Japan.ORCID https://orcid.org/0000-0002-1621-0200
Robert ZhengDepartment of Cardiovascular Medicine, Tokushima University Hospital, 2-50-1, Kuramoto-cho, Tokushima 7708503, Japan.
Yuichiro OkushiDepartment of Cardiovascular Medicine, Tokushima University Hospital, 2-50-1, Kuramoto-cho, Tokushima 7708503, Japan.ORCID https://orcid.org/0009-0004-8534-6760
Yuka NomuraUltrasound Center, Tokushima University Hospital, 2-50-1, Kuramoto-cho, Tokushima, Japan.
Yukina HirataUltrasound Center, Tokushima University Hospital, 2-50-1, Kuramoto-cho, Tokushima, Japan.ORCID https://orcid.org/0000-0002-3379-9387
Hiroaki InoueDepartment of Thoracic, Endocrine, Surgery and Oncology, Tokushima University Hospital, 2-50-1, Kuramoto-cho, Tokushima, Japan.
Hirotsugu YamadaDepartment of Cardiovascular Medicine, Tokushima University Hospital, 2-50-1, Kuramoto-cho, Tokushima 7708503, Japan.
Kenya KusunoseDepartment of Cardiovascular Medicine, Nephrology and Neurology, University of the Ryukyus, Okinawa, Japan.
Masataka SataUltrasound Center, Tokushima University Hospital, 2-50-1, Kuramoto-cho, Tokushima, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: Global longitudinal strain (GLS) is essential for the early detection of cancer therapy-related cardiac dysfunction (CTRCD). A fully automated echocardiographic analysis system using artificial intelligence (AI) may improve workflow efficiency in cardio-oncology. We sought to evaluate the feasibility and diagnostic performance of a fully automated AI-based echocardiographic system in breast cancer patients receiving cardiotoxic chemotherapy. Methods and Results: In this prospective observational study, patients with breast cancer undergoing anthracyclines and/or HER2-targeted therapy between January 2022 and June 2025 were enrolled. Transthoracic echocardiography was performed at baseline and every 12 weeks. GLS was measured manually by two experts and automatically by a fully automated AI-based analysis system. A total of 92 patients (456 echocardiographic studies) were analysed. AI-derived GLS values were significantly lower than expert measurements (17.7 ± 2.9% vs. 18.4 ± 2.8%, Conclusion: The fully automated AI-based echocardiographic system demonstrated acceptable agreement and diagnostic performance for GLS assessment and showed a similar ability to track temporal relative GLS changes and identify CTRCD. However, systemic underestimation of absolute GLS values may contribute to threshold-based classification discordance in borderline cases.

Indexed as

Artificial intelligenceBreast cancerCardiac dysfunctionChemotherapyCTRCDGLS

Identifiers

PMID42388419
PMCPMC13322393

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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.