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Classification of cardiomyopathies: bringing order to complexity

Maria Perotto1,2, Carola Pio Loco Detto Gava1,2, Federico Garoia1,2

  • 1Cardiovascular Department, Center for Diagnosis and Treatment of Cardiomyopathies, Azienda Sanitaria Universitaria Giuliano-Isontina (ASUGI), University of Trieste, Trieste, Italy.

European Heart Journal Supplements : Journal of the European Society of Cardiology
|May 8, 2026
PubMed

Insights

Cardiomyopathy classification is complex due to disease diversity. A new 2023 ESC model uses a phenotype-first approach, but overlapping features necessitate dynamic diagnostic strategies for accurate cardiomyopathy diagnosis.

Area of Science:

  • Cardiology
  • Genetics
  • Medical Diagnostics

Background:

  • Cardiomyopathy classification presents challenges due to significant clinical, morphological, and genetic heterogeneity.
  • Previous classification systems include the 2008 ESC morphofunctional classification and the 2013 MOGE(S) system.
  • Advances in diagnostic technologies necessitate updated frameworks for disease conceptualization and communication.

Purpose of the Study:

  • To introduce the revised 2023 European Society of Cardiology (ESC) phenotype-first model for cardiomyopathy classification.
  • To address the limitations and overlaps observed in current cardiomyopathy phenotypes.
  • To highlight the need for advanced diagnostic pathways in managing cardiomyopathies.

Main Methods:

  • Review and analysis of recent advances in cardiovascular imaging and genetic diagnostics.
  • Evaluation of the five major cardiomyopathy phenotypes: dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), restrictive cardiomyopathy (RCM), arrhythmogenic right ventricular cardiomyopathy (ARVC), and non-dilated left ventricular cardiomyopathy (NDLVC).
  • Assessment of the overlap and diagnostic challenges among these phenotypes, particularly DCM, ARVC, and NDLVC.

Main Results:

  • The 2023 ESC model adopts a phenotype-first approach, categorizing cardiomyopathies into five main types.
  • Significant overlap exists between DCM, ARVC, and NDLVC, complicating precise classification.
  • Current phenotypic classification alone is insufficient for definitive diagnosis due to extensive overlap.

Conclusions:

  • The 2023 ESC phenotype-first model provides a framework but highlights the need for dynamic, multiparametric diagnostic approaches.
  • Individualized interpretation of diagnostic data is crucial for accurate cardiomyopathy diagnosis.
  • Further research into integrated diagnostic strategies is warranted to overcome classification challenges.

Keywords:
Arrhythmogenic cardiomyopathyClassificationDilated cardiomyopathyHypertrophic cardiomyopathy

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