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心脏瓣膜磁共振成像在钙化性主动脉瓣疾病中的应用。

Valve tissue characterization by magnetic resonance imaging in calcific aortic valve disease.

机构信息

Département Multidisciplinaire De Cardiologie, Institut Universitaire de Cardiologie et de pneumologie de Québec, and Faculté de Médecine de l'Université Laval, Québec, Québec, Canada.

Département Multidisciplinaire De Cardiologie, Institut Universitaire de Cardiologie et de pneumologie de Québec, and Faculté de Médecine de l'Université Laval, Québec, Québec, Canada.

出版信息

Can J Cardiol. 2014 Dec;30(12):1676-83. doi: 10.1016/j.cjca.2014.09.036. Epub 2014 Oct 7.

Abstract

BACKGROUND

Calcific aortic valve disease affects 10%-15% of the elderly population, causing considerable morbidity and mortality. There is no imaging technique that allows for the assessment of tissue composition of the valve in vivo. We thus investigated whether multiparametric magnetic resonance imaging (MRI) could characterize and quantify lipid, fibrous, and mineralized tissues within aortic valve (AV) cusps.

METHODS

AV leaflets were explanted from patients with severe aortic stenosis at the time of valve replacement surgery. Aortic cusps were imaged ex vivo using 1.5 T MRI using 3 gradient-echo sequences with T1, moderate T2, and proton density weightings (T1w, T2w, and PDw). Histopathologic analysis was performed on coregistered slices to identify and measure mineralized tissue, fibrous tissue, and lipid-rich tissue. Area and mean grey values were measured in all 3 weightings by standardized software.

RESULTS

Four hundred ninety-two regions of interest from 30 AV leaflets were studied. Total leaflet surface and the areas of mineralized (P < 0.0001), fibrous (P = 0.002), and lipid-rich (P = 0.0001) tissues measured by MRI matched closely those measured by histopathologic examination. All 3 weightings provided significant discrimination between median grey values for mineralized, fibrous, and lipid-rich tissues (P < 0.0001 for T1w, moderate T2w, and PDw). A best-fit equation integrating the grey value data from all 3 weightings allowed multiparametric MRI to identify valve leaflet components with areas under the receiver operating characteristic curve of 0.92, 0.81, and 0.72, respectively.

CONCLUSIONS

AV leaflet characteristics, including tissue composition, distribution, and area, may be successfully measured by multiparametric MRI with good to excellent accuracy.

摘要

背景

钙化性主动脉瓣疾病影响 10%-15%的老年人群,导致相当高的发病率和死亡率。目前尚无影像学技术可用于评估活体瓣膜的组织成分。因此,我们研究了多参数磁共振成像(MRI)是否可以对主动脉瓣(AV)瓣叶中的脂质、纤维和矿化组织进行特征描述和定量分析。

方法

在主动脉瓣置换术时,从患有严重主动脉瓣狭窄的患者中取出 AV 瓣叶。使用 1.5 T MRI 对主动脉瓣进行离体成像,使用 3 个梯度回波序列进行 T1、中度 T2 和质子密度加权(T1w、T2w 和 PDw)。在注册切片上进行组织病理学分析,以识别和测量矿化组织、纤维组织和富含脂质的组织。使用标准化软件测量所有 3 个权重中的面积和平均灰度值。

结果

研究了 30 个 AV 瓣叶的 492 个感兴趣区。MRI 测量的总瓣叶表面积以及矿化(P < 0.0001)、纤维(P = 0.002)和富含脂质(P = 0.0001)组织的面积与组织病理学检查测量的结果非常吻合。所有 3 个权重均能显著区分矿化、纤维和富含脂质组织的中位数灰度值(T1w、中度 T2w 和 PDw 的 P < 0.0001)。一个整合了所有 3 个权重灰度值数据的最佳拟合方程使多参数 MRI 能够以 0.92、0.81 和 0.72 的曲线下面积分别识别瓣叶成分。

结论

AV 瓣叶特征,包括组织成分、分布和面积,可通过多参数 MRI 以良好到极好的准确性进行测量。

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