Zathar Zafraan, Shah Nihit, Desai Nimai, Patel Peysh A
Department of Cardiology, Worcestershire Acute Hospitals NHS Trust, WR5 1DD Worcester, UK.
Department of Cardiology, Royal Wolverhampton NHS Trust, WV10 0QP Wolverhampton, UK.
Rev Cardiovasc Med. 2024 Jun 4;25(6):208. doi: 10.31083/j.rcm2506208. eCollection 2024 Jun.
Arrhythmogenic cardiomyopathy (ACM) epitomises a genetic anomaly hallmarked by a relentless fibro-fatty transmogrification of cardiac myocytes. Initially typified as a right ventricular-centric disease, contemporary observations elucidate a frequent occurrence of biventricular and left-dominant presentations. The diagnostic labyrinth of ACM emerges from its clinical and imaging properties, often indistinguishable from other cardiomyopathies. Precision in diagnosis, however, is paramount and unlocks the potential for early therapeutic interventions and vital cascade screening for at-risk individuals. Adherence to the criteria established by the 2010 task force remains the cornerstone of ACM diagnosis, demanding a multifaceted assessment incorporating electrophysiological, imaging, genetic, and histological data. Reflecting the evolution of our understanding, these criteria have undergone several revisions to encapsulate the expanding spectrum of ACM phenotypes. This review seeks to crystallise the genetic foundation of ACM, delineate its clinical and radiographic manifestations, and offer an analytical perspective on the current diagnostic criteria. By synthesising these elements, we aim to furnish practitioners with a strategic, evidence-based algorithm to accurately diagnose ACM, thereby optimising patient management and mitigating the intricate challenges of this multifaceted disorder.
致心律失常性心肌病(ACM)是一种遗传异常,其特征是心肌细胞持续发生纤维脂肪变性。最初被典型地视为以右心室为主的疾病,但当代观察结果表明,双心室和以左心室为主的表现也很常见。ACM的诊断难题源于其临床和影像学特征,常常与其他心肌病难以区分。然而,精确诊断至关重要,它为早期治疗干预以及对高危个体进行重要的级联筛查提供了可能。遵循2010年工作组制定的标准仍然是ACM诊断的基石,这需要进行多方面评估,包括电生理、影像学、遗传学和组织学数据。随着我们认识的发展,这些标准已经历了几次修订,以涵盖ACM表型不断扩大的范围。本综述旨在明确ACM的遗传基础,描述其临床和影像学表现,并对当前的诊断标准提供分析视角。通过综合这些要素,我们旨在为从业者提供一种基于证据的策略性算法,以准确诊断ACM,从而优化患者管理并应对这种多方面疾病的复杂挑战。