Ruiz Maya Tania, Ciosek Ashley, Frech Tracy, Maldonado Genessis, Myers Kevin, Chew Erin, Baba Justin, Donato Anthony, Gupta Deepak, Ross Laura
Vanderbilt University Medical Center, 1215 21st Ave 5th Floor, Nashville, TN 37232, USA.
Vanderbilt University Medical Center, Nashville, TN, USA.
Ther Adv Musculoskelet Dis. 2025 Aug 1;17:1759720X251357188. doi: 10.1177/1759720X251357188. eCollection 2025.
While severe vasculopathic manifestations of systemic sclerosis (SSc) are well-recognized, characterization of subclinical progressive vasculopathy contributing to cardiac involvement remains an unmet clinical need. This review highlights the evolving understanding of SSc heart involvement (SHI), including current standard clinical cardiac evaluation methods, prevalence of various cardiac manifestations of SHI, and advances at the forefront of precision medicine. Informed by this growing body of literature, we describe the development of a novel interdisciplinary cardio-rheumatology clinic at the Vanderbilt University Medical Center. Utilizing advances in imaging techniques and systemic retrieval and analysis of complex data sets, our dedicated cardio-rheumatology clinic offers opportunities for therapeutic advances and personalized medicine through mechanistic disease phenotyping in SSc. Nailfold capillaroscopy, thermography, and hand ultrasound with Doppler are acquired to characterize small vessel vasculopathy, while echocardiogram, ambulatory cardiac rhythm monitoring, cardiac magnetic resonance imaging, and cardiac positron emission tomography/computed tomography are utilized to characterize cardiac disease. By correlating vasculopathy imaging with cardiac manifestations, our cardio-rheumatology clinic aims to identify patients with SSc who would benefit from additional cardiac investigation even in the absence of cardiac symptomatology. This interdisciplinary collaboration may allow earlier detection of primary SHI, which is a common cause of death in SSc patients, resulting from both morpho-functional and electrical cardiac abnormalities. Our shared model of care and robust data acquisition facilitate clinical investigation by utilizing technological advances in data management. Using deep learning and pattern recognition, artificial intelligence (AI) offers opportunities to integrate data from imaging and monitoring techniques outlined in this report to provide quantifiable markers of disease progression and treatment efficacy. Given the potential for extensive AI data processing but the low prevalence of SSc, developing a multicenter cloud-based image sharing platform would accelerate clinical investigation in the field. Ultimately, we aim to tailor therapeutic decisions and risk mitigation strategies to improve SSc patient outcomes.
虽然系统性硬化症（SSc）的严重血管病变表现已广为人知，但对导致心脏受累的亚临床进行性血管病变的特征描述仍是一项未满足的临床需求。本综述强调了对SSc心脏受累（SHI）的不断发展的认识，包括当前标准的临床心脏评估方法、SHI各种心脏表现的患病率以及精准医学前沿的进展。基于这一不断增长的文献资料，我们描述了范德比尔特大学医学中心一个新型跨学科心脏风湿病诊所的发展情况。利用成像技术的进步以及对复杂数据集的系统检索和分析，我们专门的心脏风湿病诊所通过对SSc进行疾病机制表型分析，为治疗进展和个性化医疗提供了机会。获取甲襞毛细血管镜检查、热成像和带多普勒的手部超声检查结果以表征小血管病变，同时利用超声心动图、动态心律监测、心脏磁共振成像和心脏正电子发射断层扫描/计算机断层扫描来表征心脏疾病。通过将血管病变成像与心脏表现相关联，我们的心脏风湿病诊所旨在识别即使在没有心脏症状的情况下也能从额外心脏检查中受益的SSc患者。这种跨学科合作可能有助于更早地检测原发性SHI，原发性SHI是SSc患者常见的死亡原因，由心脏形态功能和电异常共同导致。我们共享的护理模式和强大的数据采集通过利用数据管理方面的技术进步促进了临床研究。利用深度学习和模式识别，人工智能（AI）提供了整合本报告中概述的成像和监测技术数据的机会，以提供疾病进展和治疗效果的可量化指标。鉴于AI数据处理潜力巨大但SSc患病率较低，开发一个基于云的多中心图像共享平台将加速该领域的临床研究。最终，我们旨在制定治疗决策和风险缓解策略，以改善SSc患者的预后。
