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Agreement between different input image types in brain atrophy measurement in multiple sclerosis using SIENAX and SIENA

机译:使用SIENAX和SIENA在多发性硬化症脑萎缩测量中不同输入图像类型之间的一致性

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摘要

Purpose: To investigate whether multiple sclerosis (MS) atrophy can be assessed by SIENA and SIENAX software using other image types from MS research protocols than T1-weighted images without contrast agent, which are not always available. Materials and Methods: We selected 46 MS patients with identical magnetic resonance imaging (MRI) protocols at two timepoints. We calculated normalized brain volume (NBV) using SIENAX, and percentage brain volume change (PBVC) using SIENA, from T1-weighted images with and without contrast agent, T2-weighted images, and (calculated) pseudo-T1-weighted images. Relative agreement of the results was assessed using variance component estimation. Results: Relative agreement with T1-weighted images without contrast agent was good for T1-weighted images with contrast agent (ICC = 0.86 for NBV, ICC = 0.77 for PBVC), and reasonably good for pseudo-T1 and T2-weighted images (T2: ICC = 0.72 for NBV, 0.58 for PBVC; pseudo-T1: ICC = 0.68 for NBV, 0.83 for PBVC). Conclusion: Brain atrophy can be studied using SIENA and SIENAX if T1-weighted images without contrast agent are not available. T1-weighted images with contrast agent should be used if available. Otherwise, pseudo-T1 and T2-weighted images seem acceptable and accessible alternatives. The use of these other images will greatly improve research possibilities, especially regarding older datasets. © 2008 Wiley-Liss, Inc.
机译:目的:研究是否可以通过SIENA和SIENAX软件使用来自MS研究方案的其他图像类型(除无造影剂的T1加权图像以外)评估多发性硬化症(MS)萎缩症(并非总是可用)。材料和方法:我们在两个时间点选择了具有相同磁共振成像(MRI)方案的46名MS患者。我们使用SIENAX,从有和没有造影剂的T1加权图像,T2加权图像和(计算的)伪T1加权图像中,使用SIENAX计算标准化的脑容量(NBV),并使用SIENA计算脑体积变化百分比(PBVC)。使用方差分量估计来评估结果的相对一致性。结果:与不含造影剂的T1加权图像的相对一致性对于带有造影剂的T1加权图像是好的(NBV的ICC = 0.86,PBVC的ICC = 0.77),对于伪T1和T2加权的图像(T2)也相当好:对于NBV,ICC = 0.72,对于PBVC为0.58;伪T1:对于NBV,ICC = 0.68,对于PBVC为0.83)。结论:如果没有造影剂的T1加权图像,可以使用SIENA和SIENAX研究脑萎缩。如果可用,应使用带有造影剂的T1加权图像。否则,伪T1和T2加权图像似乎可以接受并且可以替代。这些其他图像的使用将极大地改善研究可能性,尤其是对于较旧的数据集。 ©2008 Wiley-Liss,Inc.

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