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首页> 外文期刊>Journal of magnetic resonance imaging: JMRI >Reliability of two techniques for assessing cerebral iron deposits with structural magnetic resonance imaging.
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Reliability of two techniques for assessing cerebral iron deposits with structural magnetic resonance imaging.

机译:两种技术的可靠性评估具有结构磁共振成像的脑制铁沉积物。

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摘要

PURPOSE: To test the reliability of two computational methods for segmenting cerebral iron deposits (IDs) in the aging brain, given that its measurement in magnetic resonance imaging (MRI) is challenging due to the similar effect produced by other minerals, especially calcium, on T2*-weighted sequences. MATERIALS AND METHODS: T1-, T2*-weighted, and fluid-attenuated inversion recovery (FLAIR) MR brain images obtained at 1.5T from 70 subjects in their early 70s who displayed a wide range of brain IDs were analyzed. The first segmentation method used a multispectral approach based on the fusion of two or more structural sequences registered and mapped in the red/green color space followed by Minimum Variance Quantization. The second method employed a combined thresholding, size and shape analysis using T2*-weighted images augmented with visual information from T1-weighted data. RESULTS: Both segmentation techniques had high intra- and interobserver agreement (95% confidence interval [CI] = +/- 57 voxels in a range from 0 to 1800), which decreased in subjects with significant microbleeds and/or IDs. However, the thresholding method was more observer dependent in identifying microbleeds and IDs boundaries than the multispectral approach. CONCLUSION: Both techniques proved to be in agreement and have good intra- and interobserver reliability. However, they have limitations, specifically with regard to automation and observer independence, so further work is required to develop fully user-independent methods of identifying cerebral IDs.
机译:目的:测试两种计算方法的可靠性,用于在老化大脑中分割脑制铁沉积物(IDS),因为其在磁共振成像(MRI)中的测量由于其他矿物质产生的类似效果,尤其是钙而挑战T2 * - 重量序列。材料和方法:T1-,T2 * - 重量和流体减毒的反转恢复(Flair)Mr脑图像在其70岁的70个受试者中获得的1.5T在其70岁的70岁均显示出各种脑ID。第一分割方法基于在红色/绿色空间中登记的两个或更多个结构序列的融合,然后在红色/绿色空间中进行最小方差量化来使用多光谱方法。第二种方法使用使用来自T1加权数据的视觉信息增强的T2 * -weighted图像的组合阈值,大小和形状分析。结果:两种分割技术具有高内和interobserver协议(95%置信区间[CI] = +/- 57体素,从0到1800的范围内),其在具有显着微妙和/或ID的受试者中降低。然而,阈值处理方法更加观察到识别微微斑点和IDS边界而不是多光谱方法。结论:这两种技术都证明是一致的,具有良好的内部和Interobserver可靠性。然而,他们有局限性,特别是关于自动化和观察者独立性,因此需要进一步的工作来开发完全用户独立的识别脑ID的方法。

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