Evidence map›Paper›PMID 41408055›Full record

ArticleNature communications2025

AI-powered SPOT imaging for enhanced myocardial scar detection and quantification.

Aurelien Bustin, Matthias Stuber, Victor de Villedon de Naide, Manuel Villegas-Martinez, Kalvin Narceau, Thaïs Génisson, Théo Richard, Pauline Gut, Valery Ozenne, Marion Constantin and 15 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

25 authors.

Aurelien BustinIHU LIRYC, Heart rhythm institute, Université de Bordeaux-INSERM U1045, Pessac, France. aurelien.bustin@ihu-liryc.fr.ORCID http://orcid.org/0000-0002-2845-8617
Matthias StuberIHU LIRYC, Heart rhythm institute, Université de Bordeaux-INSERM U1045, Pessac, France.ORCID http://orcid.org/0000-0001-9843-2028
Victor de Villedon de NaideIHU LIRYC, Heart rhythm institute, Université de Bordeaux-INSERM U1045, Pessac, France.
Manuel Villegas-MartinezIHU LIRYC, Heart rhythm institute, Université de Bordeaux-INSERM U1045, Pessac, France.
Kalvin NarceauIHU LIRYC, Heart rhythm institute, Université de Bordeaux-INSERM U1045, Pessac, France.
Thaïs GénissonIHU LIRYC, Heart rhythm institute, Université de Bordeaux-INSERM U1045, Pessac, France.
Théo RichardIHU LIRYC, Heart rhythm institute, Université de Bordeaux-INSERM U1045, Pessac, France.
Pauline GutIHU LIRYC, Heart rhythm institute, Université de Bordeaux-INSERM U1045, Pessac, France.ORCID http://orcid.org/0000-0003-0554-4974
Valery OzenneIHU LIRYC, Heart rhythm institute, Université de Bordeaux-INSERM U1045, Pessac, France.
Marion ConstantinIHU LIRYC, Heart rhythm institute, Université de Bordeaux-INSERM U1045, Pessac, France.
Guido CaluoriIHU LIRYC, Heart rhythm institute, Université de Bordeaux-INSERM U1045, Pessac, France.
Konstantinos VlachosIHU LIRYC, Heart rhythm institute, Université de Bordeaux-INSERM U1045, Pessac, France.
Géraldine MontierDepartment of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Pessac, France.
Daphné PascheDepartment of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Pessac, France.
Théo BedagueDepartment of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Pessac, France.
Jean-David MaesDepartment of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Pessac, France.
Soumaya SridiDepartment of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Pessac, France.
Claire BazinDepartment of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Pessac, France.
Gaël DournesDepartment of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Pessac, France.
Stéphanie Clément-GuinaudeauDepartment of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Pessac, France.ORCID http://orcid.org/0009-0007-9760-4140
Ilyes Ben LalaDepartment of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Pessac, France.
Mélèze HociniIHU LIRYC, Heart rhythm institute, Université de Bordeaux-INSERM U1045, Pessac, France.
Michel MontaudonDepartment of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Pessac, France.
Pierre JaïsIHU LIRYC, Heart rhythm institute, Université de Bordeaux-INSERM U1045, Pessac, France.
Hubert CochetIHU LIRYC, Heart rhythm institute, Université de Bordeaux-INSERM U1045, Pessac, France.

Funding

EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) 101076351
6 · The paper itself

Abstract

Cardiovascular disease is the leading global cause of death, underscoring the need for accurate assessment of myocardial injury. The current gold standard, bright-blood late gadolinium enhanced MRI, suffers from poor contrast at the blood-scar interface, reducing sensitivity for subendocardial scar detection and limiting reproducibility. Moreover, reliance on expert manual analysis makes interpretation labor-intensive and variable. Here, we present SPOT, a multi-spectral bright- and black-blood imaging sequence that provides unprecedented scar-to-blood contrast and clear anatomical detail. Integrated with an artificial intelligence (AI) framework for automated image analysis, SPOT enables rapid, fully automated, and operator-independent quantification of myocardial injury. Validated in simulations, animal infarct models, and patients with heart disease, this combined imaging-AI platform delivers accurate detection and quantification in a single acquisition. This innovation presents significant opportunities for earlier diagnosis and enhanced therapeutic management of ischemic heart disease, with potential applications in a wide spectrum of other clinical settings.

Indexed as

Artificial IntelligenceCicatrixMagnetic Resonance ImagingMyocardial InfarctionMyocardiumAnimalsDisease Models, AnimalGadoliniumHumansImage Processing, Computer-AssistedMaleMiceReproducibility of ResultsGadolinium

Identifiers

PMID41408055
PMCPMC12711880

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.