Basic study for constructing the statistical patient analysis system by using multi-modality of MRI

基于体素的类群分析（VBA）是脑全白质（WM）最有效的检查方法之一。然而，由于体素中嵌入的噪声，VBA往往存在统计功率低（错误发现率高）的问题。为了改善这一问题，已经提出了将VBA与预分割的WM相结合。另一方面，我们提出了三维全脑WM图谱（ABA：基于图谱的分析），以获得WM分析检验的统计能力。在本报告中，我们试图进一步扩展ABA，以获得比VBA更强的统计检测能力。我们提出了一种基于亚图谱的分析方法（SBA），它使用由WM图谱拟合曲线组成的三维平面。从离群值检验的结果来看，SBA的检测能力明显受到异常面积及其值的影响。另一方面，VBA的检测能力不受异常区域的影响，仅受异常值的影响。在簇异常情况下，SBA的检测能力受到异常面积和异常值的双重影响。由于异常区排列方式的不同，其影响与随机异常相反。VBA的检测能力也受异常面积和异常值的影响。结果表明，这两种方法对簇状异常排列的检测能力优于随机异常排列。这意味着异常值的分布影响了vbm式检测方法的检测能力。我们提出了一种新的分析脑白质异常的方法“SBA”。我们将该方法与传统的ABA方法进行了比较。在强迫症（OCD）患者中，SBA比ABA具有更大的异常检测能力，即使该方法自然包含了错误发现率。

The voxel-based group analysis(VBA) is one of the most effective examination methods of the entire white matter(WM) of brain. However, the VBA often suffers from low statistical power(high false discovery rate), which caused by embedded noise in voxels. To ameliorate this problem, the combination of the VBA with a pre-segmented WM has already been proposed. On the other hand, 3D whole brain WM atlas(ABA : atlas-based analysis) was proposed to gain statistical power on the examination of the WM analysis. In this report, we attempted to further extend the ABA to obtain statistically stronger detection power than the VBA. We proposed a sub-atlas-based analysis(SBA), which uses 3D plane made from the fitting curves to the WM atlas. From the results of outlier test, the detection power of SBA was clearly affected by both abnormal area and its value. On the other hand, the detection power of VBA was not affected abnormal area and it was only affected by abnormal values. In the case of cluster abnormality, the detection power of SBA was affected by both abnormal area and value. The affection of abnormal area was opposite from random abnormality due to the difference of their arrangement. The detection power of VBA was also affected by both abnormal area and value. From the results, these two methods showed better detection power on the cluster abnormal arrangement than the random abnormal arrangement. This means that the distribution of abnormal values affects the detection power of VBM-style examination methods. We proposed new method"SBA"to analyse abnormality within the white matter in brain. We compared our proposed method with conventional ABA. The SBA had a larger abnormality detection power than the ABA in the case of obsessive-compulsive disorder(OCD) patients, even if the method is naturally including false discovery rate.