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通过自动化磁共振检查实现心脏成像的普及。

Democratizing cardiac imaging with an automated magnetic resonance exam.

作者信息

Kara Danielle, Deb Ashmita, Le Hoa, Wee Daniel, Nakashima Makiya, Darayi Mohsen, Moura Tassia Ribeiro Salles, Robakowski Mary, Kohut Heather, Kazim Madihah, Mao Yuncong, Deng Lifu, Kanj Fayez, Pak Yea-Lyn, Goff Zackary, Houston Angel, Kohut Kathy, Mai Dingheng, Garrett Thomas, Wexler Emma, Mlakar Jeffrey, Dupuis Andrew, Fan Yiling, Sugawara Masafumi, Roche Ellen, Griswold Mark, Grimm Richard, Kapadia Samir, Svensson Lars, Wazni Oussama, Jones Stephen, Nakagawa Hiroshi, Tang H W Wilson, Bolen Michael, Lockwood Daniel, Goswami Debkalpa, Kwon Deborah, Chen David, Nguyen Christopher

机构信息

Cleveland Clinic.

Case Western Reserve University.

出版信息

Res Sq. 2025 Jul 18:rs.3.rs-6857034. doi: 10.21203/rs.3.rs-6857034/v1.

Abstract

Advanced imaging of the heart, including cardiovascular magnetic resonance imaging (CMR), has revolutionized the diagnosis and prognosis for cardiovascular disease. For the past 40 years, CMR has primarily relied on the acquisition of numerous breath-held 2D images resulting in complex scanner operation, patient discomfort, long scan durations, and cumbersome image interpretation. These limitations constrain CMR use to major academic hospital systems and severely limit patient access to CMR, which makes up < 1% of total cardiovascular imaging despite being represented in two thirds of all AHA/ACC guidelines. By leveraging advanced multidimensional physics and artificial intelligence, we overcome these challenges by developing a 30-minute end-to-end automated CMR exam (AutoCMR) that delivers 4D anatomical, functional, and tissue characterization of the whole heart in a single click without breath-holds. AutoCMR was rigorously validated in three cohorts: preclinical large animals, patients scanned in an academic hospital setting with over 40 years of CMR experience, and patients scanned in a community health center with no prior CMR experience. While providing simplified CMR acquisition and automated analysis, we demonstrated that AutoCMR was not significantly different than conventional CMR in imaging biomarkers and human interpretation. With its 4D whole thoracic coverage, we further showcased that AutoCMR can enable next generation patient analytics including personalized digital twins, 3D printing, virtual reality, and automated clinical structured summaries. Due to its inherent scalability, we anticipate AutoCMR will promote the democratization of CMR, increasing patient access for all including underserved health communities, while enabling powerful downstream cutting-edge technologies aimed at personalized medicine.

摘要

心脏的先进成像技术,包括心血管磁共振成像(CMR),已经彻底改变了心血管疾病的诊断和预后评估。在过去的40年里,CMR主要依赖于采集大量屏气二维图像,这导致扫描操作复杂、患者不适、扫描时间长以及图像解读繁琐。这些局限性使得CMR的使用仅限于大型学术医院系统,严重限制了患者获得CMR检查的机会,尽管CMR在所有美国心脏协会/美国心脏病学会指南中有三分之二的内容涉及,但它在全部心血管成像中所占比例不到1%。通过利用先进的多维物理学和人工智能技术,我们开发了一种30分钟的端到端自动化CMR检查(AutoCMR),无需屏气,只需一键操作就能提供全心脏的四维解剖、功能和组织特征,从而克服了这些挑战。AutoCMR在三个队列中进行了严格验证:临床前大型动物、在拥有40多年CMR经验的学术医院环境中扫描的患者,以及在之前没有CMR经验的社区健康中心扫描的患者。在提供简化的CMR采集和自动分析的同时,我们证明了AutoCMR在成像生物标志物和人工解读方面与传统CMR没有显著差异。凭借其四维全胸覆盖,我们进一步展示了AutoCMR能够实现下一代患者分析,包括个性化数字孪生、3D打印、虚拟现实和自动临床结构化总结。由于其固有的可扩展性,我们预计AutoCMR将促进CMR的普及,增加包括医疗服务不足社区在内的所有患者获得CMR检查的机会,同时推动旨在实现个性化医疗的强大下游前沿技术的发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ef5/12288535/b203e176620e/nihpp-rs6857034v1-f0001.jpg

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