Cardiac Magnetic Resonance in Pulmonary Hypertension-an Update.

IF 0.6 Q4 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Current Cardiovascular Imaging Reports Pub Date : 2020-01-01 Epub Date: 2020-11-07 DOI:10.1007/s12410-020-09550-2

Samer Alabed, Pankaj Garg, Christopher S Johns, Faisal Alandejani, Yousef Shahin, Krit Dwivedi, Hamza Zafar, James M Wild, David G Kiely, Andrew J Swift

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Abstract

Purpose of review: This article reviews advances over the past 3 years in cardiac magnetic resonance (CMR) imaging in pulmonary hypertension (PH). We aim to bring the reader up-to-date with CMR applications in diagnosis, prognosis, 4D flow, strain analysis, T₁ mapping, machine learning and ongoing research.

Recent findings: CMR volumetric and functional metrics are now established as valuable prognostic markers in PH. This imaging modality is increasingly used to assess treatment response and improves risk stratification when incorporated into PH risk scores. Emerging techniques such as myocardial T₁ mapping may play a role in the follow-up of selected patients. Myocardial strain may be used as an early marker for right and left ventricular dysfunction and a predictor for mortality. Machine learning has offered a glimpse into future possibilities. Ongoing research of new PH therapies is increasingly using CMR as a clinical endpoint.

Summary: The last 3 years have seen several large studies establishing CMR as a valuable diagnostic and prognostic tool in patients with PH, with CMR increasingly considered as an endpoint in clinical trials of PH therapies. Machine learning approaches to improve automation and accuracy of CMR metrics and identify imaging features of PH is an area of active research interest with promising clinical utility.

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肺动脉高压的心脏磁共振--最新进展。

综述目的：本文回顾了过去三年来肺动脉高压（PH）心脏磁共振（CMR）成像的进展。我们旨在向读者介绍 CMR 在诊断、预后、四维血流、应变分析、T1 图谱、机器学习和正在进行的研究中的最新应用：最近的发现：CMR 容量和功能指标现已被确定为 PH 有价值的预后指标。这种成像模式越来越多地用于评估治疗反应，并在纳入 PH 风险评分时改善风险分层。心肌 T1 图谱等新兴技术可能会在选定患者的随访中发挥作用。心肌应变可作为左右心室功能障碍的早期标志和死亡率的预测指标。机器学习让我们看到了未来的可能性。摘要：在过去的三年中，已有多项大型研究将CMR确立为PH患者的重要诊断和预后工具，CMR也越来越多地被视为PH疗法临床试验的终点。机器学习方法可提高CMR指标的自动化和准确性，并识别PH的成像特征，是一个具有良好临床应用前景的研究领域。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Current Cardiovascular Imaging Reports RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-

CiteScore

2.20

自引率

0.00%

发文量

期刊介绍： Cardiovascular imaging technologies now play an expanded role in clinical practice. Beyond the diagnosis of a disease process, these techniques are rapidly transitioning to help guide therapy. The journal aims to keep readers current with rapidly evolving advances in instrumentation and imaging procedures that support the expanded role of these technologies in clinical practice. The journal intends to place the entire area of cardiovascular imaging in its proper prospective by establishing the indications and limitations of each imaging technique and by summarizing recent clinical advances. We accomplish this aim by appointing international authorities to serve as Section Editors in key subject areas across the field, including cardiac magnetic resonance, nuclear imaging, echocardiography, cardiac computed tomography, intravascular, molecular, and hybrid imaging. Section Editors select topics for which leading experts contribute comprehensive review articles that emphasize new developments and recently published papers of major importance, highlighted by annotated reference lists. An Editorial Board of internationally diverse members ensures that topics include emerging research and suggests topics of special interest to their country/region. We also provide commentaries from well-known figures in the field.