International Consortium for Multimodality Phenotyping in Adults with Non-compaction

摘要 非致密性心肌病(NCCM)是一种异质性的、鲜为人知的疾病，其特征是 内层明显疏松的心肌组织。NCCM患者心力衰竭、中风、 严重的节律不齐和死亡。目前的成像技术不能区分病变和良性 过度小梁形成。此外，目前基于ECHO/MRI的NCCM标准导致对NCCM的过度诊断， 没有提供预后价值，并导致植入除颤器(ICD)和使用抗凝，但没有 对于许多患有非致密心肌的健康个体来说，这是一个积极的好处。对于不断增长的 被诊断为NCCM的人群迫切需要更好的风险分层来适当分配(或 安全地扣留)这些有效的预防措施。我们的国际财团结合了在 来自5个致力于护理的中心的心肌疾病、心脏成像和先进的计算机分析 患有心肌病的患者，并以改善致密化不全患者的护理为最终目标 心肌病。我们假设对临床、遗传、结构和功能的综合分析 信息将改善风险分层。此外，我们假设详细的结构分析将允许 用于区分致密性不全的病理和良性模式。在一大群成年患者中 疑似NCCM我们将进行深入的表型鉴定，包括临床信息，家系数据，遗传学， 超声心动图和核磁共振检查，并对患者进行长达3年的随访。我们将应用基于机器学习的分析 开发预测模型，并将其性能与当前使用的模型和治疗标准进行比较。 其次，在一组患者中，我们将对详细的结构进行高分辨率心脏CT检查 心肌壁的特征。将开发新的分析方法来表征3D 基于病理生理学假设的架构复杂性，但也使用RAW的无假设分析 使用深度学习技术的图像。此外，我们还将研究心肌梗死与 结构和局部收缩功能，如回声和核磁共振评估。这项提案的目的是确定 与病理性压实不紧密相关的结构特征和改进的已开发风险预测 模特们。这个致力于NCCM的国际联盟将是第一个收集遗传和多模式的 成像数据。通过创新的成像技术发现病理结构特征，与 对心肌收缩功能的研究，将增进我们对NCCM的认识。临床上迫切需要 诊断技术，检测病理性致密化不全并识别有毁灭性风险的患者 并发症。这项研究具有临床意义，因为开发的预测模型可能会允许更多 为越来越多被诊断为骨质疏松症的患者提供有效的个性化预防性护理 心肌病。

Summary Non-compaction cardiomyopathy (NCCM) is a heterogeneous, poorly understood disorder characterized by a prominent inner layer of loose myocardial tissue. Patients with NCCM are at increased risk of heart failure, stroke, severe rhythm irregularities and death. Current imaging techniques cannot differentiate pathological from benign hypertrabeculation. In addition, current echo/MRI-based criteria of NCCM lead to over-diagnosis of NCCM, provide no prognostic value, and lead to implantation of defibrillators (ICD) and the use of anticoagulation without a positive benefit in many otherwise healthy individuals with non-compacted myocardium. For a growing population diagnosed with NCCM there is an urgent need for better risk stratification to appropriately allocate (or safely withhold) these impactful preventive measures. Our international consortium combines expertise in myocardial disease, cardiac imaging and advanced computer analytics from 5 centers dedicated to the care of patients with cardiomyopathies, and has the ultimate goal to improve care of patients with non-compaction cardiomyopathy. We hypothesize that comprehensive analysis of clinical, genetic, structural and functional information will improve risk stratification. In addition, we hypothesize that detailed structural analysis will allow for differentiation of pathological and benign patterns of non-compaction. In a large cohort of adult patients with suspected NCCM we will perform in-depth phenotyping, including clinical information, pedigree data, genetics, echocardiography and MRI, and follow patients for up to 3 years. We will apply machine-learning based analytics to develop predictive models and compare their performance to currently used models and treatment criteria. Secondly, in a subset of patients we will perform high-resolution cardiac CT for detailed structural characterization of the myocardial wall. Novel analytical methods will be developed to characterize the 3D architectural complexity based on pathophysiological hypothesis, but also using hypothesis-free analyses of raw images using deep learning techniques. In addition, we will investigate associations between myocardial structure and regional contractile function, as assessed by echo and MRI. The aim of this proposal is to identify a structural signature associated with pathological non-compaction and improve developed risk prediction models. This international consortium dedicated to NCCM will be the first to collect genetic and multi-modality imaging data. Discovery of pathological structural signatures through innovative imaging techniques, in relation to myocardial contractility, will advance our understanding of NCCM. There is an urgent clinical need for diagnostic techniques that detect pathological non-compaction and identify patients at risk of devastating complications. This study is clinically relevant because the developed predictive models may permit more effective, personalized preventive care in a growing number of individuals diagnosed with non-compaction cardiomyopathy.