Szugye Nicholas
Department of Heart, Vascular & Thoracic, Division of Cardiology & Cardiovascular Medicine - Pediatric Cardiology, Cleveland Clinic Lerner College of Medicine, Cleveland, OH, USA.
Cardiovasc Diagn Ther. 2024 Dec 31;14(6):1176-1185. doi: 10.21037/cdt-24-363. Epub 2024 Dec 19.
As the population of adults with congenital heart disease (ACHD) grows, there also grows an expanded need for non-invasive surveillance methods to guide management and intervention. A multimodal imaging approach layers complementary insights from echocardiography, computed tomography (CT), magnetic resonance imaging (MRI), and other modalities into a clinician's view of patient physiology. Merely applying strategies from acquired adult cardiac disease would be inadequate and potentially misleading. As data amasses in this small but growing population, investigators in the field of ACHD have discovered population-specific imaging biomarkers that identify deterioration and pivotal time points where intervention may reduce morbidity and mortality. Moreover, due to the variety of physiologies and the modest number of ACHD patients relative to that of adults with acquired heart disease, multicenter registries will be key in advancing research. The integration of well-defined imaging variables into these databases can help identify important biomarkers. Emerging technologies like computational fluid dynamics (CFD) and artificial intelligence (AI) are also primed to enhance imaging capabilities and clinical workflows, though require careful adaption as ACHD patients are not meaningfully represented in the training data for these technologies. Ultimately, a multimodal imaging approach is essential for optimizing care for ACHD patients, enabling personalized medicine where interventions can be performed before clinical deterioration occurs.
随着先天性心脏病成年患者(ACHD)数量的增加,对于指导管理和干预的非侵入性监测方法的需求也在不断扩大。多模态成像方法将来自超声心动图、计算机断层扫描(CT)、磁共振成像(MRI)及其他模态的互补性见解融入临床医生对患者生理状况的观察中。仅仅应用获得性成人心脏病的策略是不够的,而且可能会产生误导。随着针对这一规模虽小但不断增长的人群的数据不断积累,ACHD领域的研究人员已经发现了针对该人群的成像生物标志物,这些标志物可识别病情恶化情况以及干预可能降低发病率和死亡率的关键时间点。此外,由于生理状况的多样性以及相对于获得性心脏病成年患者而言ACHD患者数量较少,多中心注册研究对于推动该领域的研究至关重要。将明确的成像变量整合到这些数据库中有助于识别重要的生物标志物。计算流体动力学(CFD)和人工智能(AI)等新兴技术也有望增强成像能力和临床工作流程,不过由于这些技术的训练数据中没有充分体现ACHD患者的情况,因此需要谨慎应用。最终,多模态成像方法对于优化ACHD患者的治疗至关重要,它能够实现个性化医疗,即在临床病情恶化之前就进行干预。