Classification of cardiomyopathies: bringing order to complexity

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.