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实时 3D 融合超声心动图。

Real-time 3D fusion echocardiography.

机构信息

Department of Cardiovascular Medicine, University of Oxford, Oxford, UK.

出版信息

JACC Cardiovasc Imaging. 2010 Jul;3(7):682-90. doi: 10.1016/j.jcmg.2010.03.010.

Abstract

OBJECTIVES

This study assessed 3-dimensional fusion echocardiography (3DFE), combining several real-time 3-dimensional echocardiography (RT3DE) full volumes from different transducer positions, for improvement in quality and completeness of the reconstructed image.

BACKGROUND

The RT3DE technique has limited image quality and completeness of datasets even with current matrix transducers.

METHODS

RT3DE datasets were acquired in 32 participants (mean age 33.7 +/- 18.8 years; 27 men, 5 women). The 3DFE technique was also performed on a cardiac phantom. The endocardial border definition of RT3DE and 3DFE segments was graded for quality: good (2), intermediate (1), poor (0), or out of sector. Short-axis and apical images were compared in RT3DE and 3DFE, yielding 2,048 segments. The images were processed to generate 3DFE and then compared with cardiac magnetic resonance.

RESULTS

In the heart phantom, fused datasets showed improved contrast to noise ratio from 49.4 +/- 25.1 (single dataset) to 125.4 +/- 25.1 (6 datasets fused together). In subjects, more segments were graded as good quality with 3DFE (805 vs. 435; p < 0.0001) and fewer as intermediate (184 vs. 283; p = 0.017), poor (31 vs. 265; p < 0.0001), or out of sector (4 vs. 41; p < 0.001) compared with the single 3-dimensional dataset. End-diastolic volume (EDV) and end-systolic volume (ESV) obtained from 3-dimensional fused datasets were equivalent to those from single datasets (EDV 118.2 +/- 39 ml vs. 119.7 +/- 43 ml; p = 0.41; ESV 48.1 +/- 30 ml vs. 48.4 +/- 35 ml; p = 0.87; ejection fraction [EF] 61.0 +/- 10% vs. 61.8 +/- 10%; p = 0.44). Bland-Altman analysis showed good 95% limits of agreement for the nonfused datasets (EDV +/-46 ml; ESV +/-36 ml; EF +/-14%) and the fused datasets (EDV +/-45 ml; ESV +/-35 ml; EF +/-16%), when compared with cardiac magnetic resonance.

CONCLUSIONS

Fusion of full-volume datasets resulted in an improvement in endocardial borders, image quality, and completeness of the datasets.

摘要

目的

本研究评估了三维融合超声心动图(3DFE),该技术将来自不同探头位置的多个实时三维超声心动图(RT3DE)全容积结合起来,以提高重建图像的质量和完整性。

背景

即使使用当前的矩阵换能器,RT3DE 技术的图像质量和数据集的完整性也有限。

方法

在 32 名参与者(平均年龄 33.7 ± 18.8 岁;27 名男性,5 名女性)中采集 RT3DE 数据集。还在心脏模型上进行了 3DFE 技术。对 RT3DE 和 3DFE 节段的心内膜边界定义进行质量分级:优(2)、中(1)、差(0)或不在扇区。在 RT3DE 和 3DFE 中比较短轴和心尖图像,产生 2048 个节段。对图像进行处理以生成 3DFE,并与心脏磁共振进行比较。

结果

在心脏模型中,融合数据集的对比噪声比从 49.4 ± 25.1(单个数据集)提高到 125.4 ± 25.1(融合在一起的 6 个数据集)。在患者中,3DFE 可获得更多的优质节段(805 个比 435 个;p < 0.0001),较少的中质节段(184 个比 283 个;p = 0.017)、差质节段(31 个比 265 个;p < 0.0001)或不在扇区节段(4 个比 41 个;p < 0.001)与单个三维数据集相比。从三维融合数据集获得的舒张末期容积(EDV)和收缩末期容积(ESV)与从单个数据集获得的容积相当(EDV 118.2 ± 39 ml 比 119.7 ± 43 ml;p = 0.41;ESV 48.1 ± 30 ml 比 48.4 ± 35 ml;p = 0.87;射血分数 [EF] 61.0 ± 10% 比 61.8 ± 10%;p = 0.44)。Bland-Altman 分析显示,与心脏磁共振相比,非融合数据集(EDV ±46 ml;ESV ±36 ml;EF ±14%)和融合数据集(EDV ±45 ml;ESV ±35 ml;EF ±16%)的 95%一致性界限良好。

结论

全容积数据集的融合提高了心内膜边界、图像质量和数据集的完整性。

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