Unit of Academic Radiology, University of Sheffield, Sheffield, England; National Institute of Health Research, Cardiovascular Biomedical Research Unit, Sheffield, England.
Unit of Academic Radiology, University of Sheffield, Sheffield, England.
JACC Cardiovasc Imaging. 2013 Oct;6(10):1036-1047. doi: 10.1016/j.jcmg.2013.01.013. Epub 2013 Jun 13.
The aim of this study was to develop a composite numerical model based on parameters from cardiac magnetic resonance (CMR) imaging for noninvasive estimation of the key hemodynamic measurements made at right heart catheterization (RHC).
Diagnosis and assessment of disease severity in patients with pulmonary hypertension is reliant on hemodynamic measurements at RHC. A robust noninvasive approach that can estimate key RHC measurements is desirable.
A derivation cohort of 64 successive, unselected, treatment naive patients with suspected pulmonary hypertension from the ASPIRE (Assessing the Spectrum of Pulmonary Hypertension Identified at a Referral Centre) Registry, underwent RHC and CMR within 12 h. Predicted mean pulmonary arterial pressure (mPAP) was derived using multivariate regression analysis of CMR measurements. The model was tested in an independent prospective validation cohort of 64 patients with suspected pulmonary hypertension. Surrogate measures of pulmonary capillary wedge pressure (PCWP) and cardiac output (CO) were estimated by left atrial volumetry and pulmonary arterial phase contrast imaging, respectively. Noninvasive pulmonary vascular resistance (PVR) was calculated from the CMR-derived measurements, defined as: (CMR-predicted mPAP - CMR-predicted PCWP)/CMR phase contrast CO.
The following composite statistical model of mPAP was derived: CMR-predicted mPAP = -4.6 + (interventricular septal angle × 0.23) + (ventricular mass index × 16.3). In the validation cohort a strong correlation between mPAP and MR estimated mPAP was demonstrated (R(2) = 0.67). For detection of the presence of pulmonary hypertension the area under the receiver-operating characteristic (ROC) curve was 0.96 (0.92 to 1.00; p < 0.0001). CMR-estimated PVR reliably identified invasive PVR ≥3 Wood units (WU) with a high degree of accuracy, the area under the ROC curve was 0.94 (0.88 to 0.99; p < 0.0001).
CMR imaging can accurately estimate mean pulmonary artery pressure in patients with suspected pulmonary hypertension and calculate PVR by estimating all major pulmonary hemodynamic metrics measured at RHC.
本研究旨在建立一种基于心脏磁共振（CMR）成像参数的复合数值模型，以无创估计右心导管检查（RHC）中的关键血流动力学测量值。
肺动脉高压患者的诊断和疾病严重程度评估依赖于 RHC 的血流动力学测量值。理想情况下，需要一种能够估计关键 RHC 测量值的稳健无创方法。
ASPIRE（评估在转诊中心确定的肺动脉高压谱）注册中心连续入选了 64 例未经治疗的疑似肺动脉高压患者，这些患者在 12 小时内接受了 RHC 和 CMR 检查。通过对 CMR 测量值进行多元回归分析得出预测平均肺动脉压（mPAP）。该模型在 64 例疑似肺动脉高压的独立前瞻性验证队列中进行了测试。通过左心房容积测量和肺动脉期对比成像分别估计替代肺小动脉楔压（PCWP）和心输出量（CO）。通过 CMR 衍生测量值计算无创肺血管阻力（PVR），定义为：（CMR 预测 mPAP-CMR 预测 PCWP）/CMR 相位对比 CO。
得出了 mPAP 的以下复合统计模型：CMR 预测 mPAP = -4.6 +（室间隔角度×0.23）+（心室质量指数×16.3）。在验证队列中，mPAP 与 MR 估计 mPAP 之间存在很强的相关性（R（2）=0.67）。对于肺动脉高压的存在检测，ROC 曲线下面积为 0.96（0.92 至 1.00；p <0.0001）。CMR 估计的 PVR 能够可靠地识别侵入性 PVR≥3 Wood 单位（WU），准确性高，ROC 曲线下面积为 0.94（0.88 至 0.99；p <0.0001）。
CMR 成像可准确估计疑似肺动脉高压患者的平均肺动脉压，并通过估计 RHC 测量的所有主要肺血流动力学指标来计算 PVR。
