基于图像导航的自动化冠状动脉磁共振血管造影术用于检测冠状动脉狭窄。

Image navigator-based, automated coronary magnetic resonance angiography for the detection of coronary artery stenosis.

作者信息

Wood Gregory, Hajhosseiny Reza, Pedersen Alexandra Uglebjerg, Littlewood Simon, Hansen Tina Juul, Neji Radhouene, Kunze Karl P, Wetzl Jens, Nørgaard Bjarne Linde, Jensen Jesper Møller, Maeng Michael, Madsen Per Lav, Vejlstrup Niels, Prieto Claudia, Botnar René M, Kim Won Yong

机构信息

Department of Cardiology, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.

National Heart and Lung Institute, Imperial College London, London, United Kingdom; School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.

出版信息

J Cardiovasc Magn Reson. 2024;26(2):101097. doi: 10.1016/j.jocmr.2024.101097. Epub 2024 Sep 16.

DOI:10.1016/j.jocmr.2024.101097

PMID:39293786

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11647470/

Abstract

BACKGROUND

Coronary computed tomography angiography (CCTA) is recommended as the first-line diagnostic imaging modality in low-to-intermediate-risk individuals suspected of stable coronary artery disease (CAD). However, CCTA exposes patients to ionizing radiation and potentially nephrotoxic contrast agents. Invasive coronary angiography is the gold-standard investigation to guide coronary revascularisation strategy; however, invasive procedures incur an inherent risk to the patient. Coronary magnetic resonance angiography (CMRA) avoids these issues. Nevertheless, clinical implementation is currently limited due to extended scanning durations, inconsistent image quality, and consequent lack of diagnostic accuracy. Several technical CMRA innovations, including advanced respiratory motion correction with 100% scan efficiency (no data rejection), fast image acquisition with motion-corrected undersampled image reconstruction, and deep-learning-based automated planning, have been implemented and now await clinical validation in multi-center trials.

METHODS

The objective of the image navigator-based, automated CMRA prospective multi-center study is to evaluate the diagnostic accuracy of a newly developed, state-of-the-art, standardized, and automated CMRA framework compared to CCTA in 201 patients undergoing clinical investigation for CAD. The study protocol mandates the administration of oral beta-blockers to decrease heart rate to below 60 bpm and the use of sublingual nitroglycerine spray to induce vasodilation. Additionally, the study incorporates the utilization of standardized postprocessing with sliding-thin-slab multiplanar reformatting, in combination with evaluation of the source images, to optimize the visualization of coronary artery stenosis.

DISCUSSION

If proven effective, CMRA could provide a non-invasive, needle-free, yet also clinically viable, alternative to CCTA.

TRIAL REGISTRATION

This study is registered at ClinicalTrials.gov (NCT05473117).

摘要

背景

对于疑似患有稳定型冠状动脉疾病（CAD）的低至中度风险个体，冠状动脉计算机断层扫描血管造影（CCTA）被推荐作为一线诊断成像方式。然而，CCTA会使患者暴露于电离辐射和潜在的肾毒性造影剂中。有创冠状动脉造影是指导冠状动脉血运重建策略的金标准检查；然而，有创操作对患者存在固有风险。冠状动脉磁共振血管造影（CMRA）可避免这些问题。尽管如此，由于扫描时间延长、图像质量不一致以及随之而来的诊断准确性不足，CMRA目前在临床中的应用受到限制。包括具有100%扫描效率（无数据剔除）的先进呼吸运动校正、基于运动校正欠采样图像重建的快速图像采集以及基于深度学习的自动规划在内的多项CMRA技术创新已经实施，目前正等待在多中心试验中进行临床验证。

方法

基于图像导航仪的自动CMRA前瞻性多中心研究的目的是，在201例接受CAD临床检查的患者中，评估一种新开发的、最先进的、标准化且自动化的CMRA框架与CCTA相比的诊断准确性。研究方案要求服用口服β受体阻滞剂以使心率降至60次/分以下，并使用舌下硝酸甘油喷雾剂诱导血管扩张。此外，该研究采用标准化后处理结合滑动薄板多平面重新格式化，并结合源图像评估，以优化冠状动脉狭窄的可视化。