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Multicenter Study
. 2025 Aug;35(8):4699-4710.
doi: 10.1007/s00330-025-11404-8. Epub 2025 Feb 8.

Prognostic impact of late gadolinium enhancement granularity in non-ischemic dilated cardiomyopathy

Trecy Gonçalves  1   2   3   4   5 , Jérôme Garot  6 , Solenn Toupin  7 , Valérie Bousson  3 , Francesca Sanguineti  5 , Myriam Akodad  5 , Suzanne Duhamel  5 , Stéphane Champagne  5 , Antoinette Neylon  5 , Thierry Unterseeh  5 , Thomas Hovasse  5 , Lounis Hamzi  3 , Alexandre Unger  1   2   4   5   8 , Jeremy Florence  1   2   4 , Raphael Mirailles  1   2   4 , Antoine Bondue  8 , Jean Guillaume Dillinger  1   2   4 , Patrick Henry  1   2   4 , Philippe Garot  5 , Théo Pezel  1   2   3   4   5
Affiliations
Multicenter Study

Prognostic impact of late gadolinium enhancement granularity in non-ischemic dilated cardiomyopathy

Trecy Gonçalves et al. Eur Radiol. 2025 Aug.

Abstract

Objectives: We aimed to assess the additional prognostic value of the concept of "late gadolinium enhancement (LGE) granularity" in non-ischemic dilated cardiomyopathy (DCM) patients to predict all-cause death.

Methods: Between 2008 and 2021, we conducted a bicentric retrospective study including all consecutive DCM patients referred for Cardiovascular Magnetic Resonance (CMR). The primary outcome was all-cause death. Cox regressions were performed to determine the prognostic value of LGE findings.

Results: Of 1668 DCM patients recruited (age 52 ± 8 years, 54% male), 268 (16%) died after a median (interquartile range) follow-up of 9 (7-12) years. In DCM patients with LGE (N = 472), the LGE extent, the septal location, and its presence in multiple areas were independently associated with death after adjustment for all prognostic variables (adjusted hazard ratio (HR): 4.27, 95% CI: 2.22-8.22; HR: 5.74, 95% CI: 3.35-9.85; and HR: 4.38, 95% CI: 2.08-9.22 respectively; all p < 0.001). The LGE granularity model combining all these LGE features showed the best improvement in model discrimination and reclassification over traditional prognostic variables, including the left ventricular ejection fraction (LVEF) value (C-statistic improvement: 0.14; net reclassification improvement = 64.3%; integrative discrimination index = 29.0%; all p < 0.05).

Conclusion: In a large cohort of DCM patients, a LGE granularity model combining LGE extent, location and multiple areas had additional prognostic value above traditional prognostic variables including the LVEF value to predict all-cause death.

Key points: Question Assessment of late gadolinium enhancement (LGE) is recommended in non-ischemic dilated. cardiomyopathy (DCM) patients to stratify the risk of death, but other LGE characteristics are not currently considered. Findings The concept of "LGE granularity," including the extent, location, and number of areas, provides additional prognostic value, especially in predicting all-cause mortality. Clinical relevance "LGE granularity" could play a crucial role not only in guiding the decision to implant a defibrillator in DCM patients but also in providing more personalized management, such as enhanced cardioprotective treatments, for those with high-risk LGE characteristics.

Keywords: Additional prognostic value; Cardiovascular magnetic resonance; Late gadolinium enhancement; Non-ischemic dilated cardiomyopathy; Prognosis.

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Conflict of interest statement

Compliance with ethical standards. Guarantor: The scientific guarantor of this publication is Jérôme Garot. Conflict of interest: S.T. is an employee of Siemens Healthcare. Other authors declare that they have no competing interests. Statistics and biometry: No complex statistical methods were necessary for this paper. Informed consent: The study was evaluated and approved by the local ethics committee of our institutions and conducted in accordance with the 1964 Declaration of Helsinki. All patients enrolled in this study were required to understand and give their consent for participation. Ethical approval: Institutional Review Board approval was obtained. Study subjects or cohorts overlap: No study subjects or cohorts have been previously reported. Methodology: Retrospective Observational Multicenter study

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