使用心脏磁共振成像评估肺动脉高压

Shaimaa Saeed Mohamed, Mona Mansour Ahmed, T. M. Ali, R. Elkorashy, A M Osman, Maryam Aly Abd Elkader, Sameh Nabil Kamel
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引用次数: 0

摘要

通过基于心脏磁共振的数字模型,评估心脏磁共振成像在无创估算右心导管测量的主要血液动力学参数(即平均肺动脉压、肺血管阻力和肺动脉楔压)方面的实用性。 研究随机选取了 29 名符合纳入标准的肺动脉高压患者。在一个月内进行了心脏磁共振成像和右侧心脏导管(RHC)检查。测试了 3 个基于心脏核磁共振成像的模型,这些模型在文献中显示出较高的准确性。mPAP 的两个计算公式为:mPAP=-231.423 + 53.8(loge 室间隔角度)+log10(右心室质量除以左心室质量),即心室质量指数 X 8.708+ 舒张期肺动脉面积 X 0.009;mPAP = -4.6+(0.32* 室间隔角度)+(心室质量指数 × 16.3)。PAWP 的计算公式为:PAWP = 左心房容积指数 +6.43 × 0.22。 有创测量的 mPAP 与 CMR 估算的 mPAP 之间的 Altman 和 Bland 相关性良好,基于 CMR 的 mPAP 模型 1 和 2 分别为 r= 0.594 和 r=0.599 (P<0.001)。对于基于 CMR 的 mPAP 模型 1 和 2,RHC 导出的 mPAP 与 CMR 估算的 mPAP 之间的计算平均偏差分别为 7.9(一致区间 -24.8 至 40.6 mm Hg)和平均偏差 -3(一致区间 -34.8 至 28.2 mm Hg)。对于基于 CMR 的 PAWP 模型,有创测量和 CMR 估算的 PAWP 之间没有相关性(P =0.092)。RHC 导出的 PAWP 与 CMR 估算的 PAWP 之间的平均偏差为 2.4(一致区间为 -13.5 至 18.2 mm Hg)。有创计算的 PVR 与 CMR 估算的 PVR 之间具有良好的相关性,基于 CMR 的 PVR 模型 1 和 2 分别为 r=0.703 和 r=0.704 (P<0.001)。对于基于 CMR 的 mPAP 模型 1 和 2,RHC 测量的 mPAP 与 CMR 估算的 mPAP 之间的平均偏差分别为 0.6(一致区间 -11.6 至 12.8 mm Hg)和平均偏差-1.3(一致区间 -12.1 至 9.5 mm Hg)。 我们的结果表明,CMR 结果与 RHC 之间在 mPAP 和 PVR 方面存在良好的相关性。因此,使用 CMR 无创估计 mPAP、PAWP 和 PVR 是可行的,但需要进一步研究以提高准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The use of cardiac magnetic resonance imaging for the evaluation of pulmonary hypertension
Evaluate the utility of cardiac magnetic resonance imaging to estimate the principle hemodynamic parameters that are measured by right heart catheterization in a noninvasive manner i.e. mean pulmonary artery pressure, pulmonary vascular resistance and pulmonary artery wedge pressure through cardiac magnetic resonance based numerical models. 29 pulmonary hypertension patients, fitting the inclusion criteria were randomly selected and included in the study. CMR Imaging and right side heart catheter (RHC) were performed within one month. 3 Cardiac MRI based models in literature that showed high accuracy were tested. Two equations for mPAP calculation; mPAP=-231.423 + 53.8(loge inter-ventricular septal angle)+log10(right ventricular mass divided by left ventricular mass) i.e ventricular mass index X 8.708+area of pulmonary artery in diastole X 0.009 and mPAP = –4.6+(0.32*septal angle)+(ventricular mass index × 16.3). One equation for PAWP; PAWP = left atrial volume index +6.43 × 0.22. The Altman and Bland correlation between mPAP invasively measured and CMR-estimated mPAP had good correlation with r= 0.594 and r=0.599 (P<0.001) for CMR based mPAP model 1 and 2, respectively. The calculated mean bias between the RHC-derived and CMR-estimated mPAP was 7.9 (agreement interval -24.8 to 40.6 mm Hg) and mean bias -3 (agreement interval -34.8 to 28.2 mm Hg) for CMR based mPAP model 1 and 2, respectively. There was no correlation between invasively measured and CMR-estimated PAWP with (P =0.092) for CMR based PAWP model. The mean bias between the RHC-derived and CMR-estimated PAWP was 2.4 (agreement interval –13.5 to 18.2 mm Hg). The correlation between invasively calculated and CMR-estimated PVR had good correlation with r=0.703 and r=0.704 (P<0.001) for CMR based PVR model 1 and 2, respectively. The mean bias between the RHC-measured and CMR-estimated mPAP was 0.6 (agreement interval -11.6 to 12.8 mm Hg) and mean bias -1.3 (agreement interval -12.1 to 9.5 mm Hg) for CMR based mPAP model 1 and 2, respectively. Our results showed good correlations between CMR findings and RHC as regard mPAP and PVR. Thus, estimation of mPAP, PAWP and PVR non-invasively using CMR is feasible but needs further studies to improve accuracy.
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