Yoo Byung Il, Lee Jung Jae, Han Ji Won, Oh San Yeo Wool, Lee Eun Young, MacFall James R, Payne Martha E, Kim Tae Hui, Kim Jae Hyoung, Kim Ki Woong
Department of Neuropsychiatry, Seoul National University Bundang Hospital, 166 Gumi-ro, Bundang, Seongnam, Gyeonggi-do, 463-707, Republic of Korea.
Neuroradiology. 2014 Apr;56(4):265-81. doi: 10.1007/s00234-014-1322-6. Epub 2014 Feb 4.
White matter hyperintensities (WMHs) are regions of abnormally high intensity on T2-weighted or fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI). Accurate and reproducible automatic segmentation of WMHs is important since WMHs are often seen in the elderly and are associated with various geriatric and psychiatric disorders.
We developed a fully automated monospectral segmentation method for WMHs using FLAIR MRIs. Through this method, we introduce an optimal threshold intensity (I O ) for segmenting WMHs, which varies with WMHs volume (V WMH), and we establish the I O -V WMH relationship.
Our method showed accurate validations in volumetric and spatial agreements of automatically segmented WMHs compared with manually segmented WMHs for 32 confirmatory images. Bland-Altman values of volumetric agreement were 0.96 ± 8.311 ml (bias and 95 % confidence interval), and the similarity index of spatial agreement was 0.762 ± 0.127 (mean ± standard deviation). Furthermore, similar validation accuracies were obtained in the images acquired from different scanners.
The proposed segmentation method uses only FLAIR MRIs, has the potential to be accurate with images obtained from different scanners, and can be implemented with a fully automated procedure. In our study, validation results were obtained with FLAIR MRIs from only two scanner types. The design of the method may allow its use in large multicenter studies with correct efficiency.
脑白质高信号(WMHs)是在T2加权或液体衰减反转恢复(FLAIR)磁共振成像(MRI)上显示为异常高强度的区域。由于WMHs常见于老年人并与多种老年病和精神疾病相关,因此对其进行准确且可重复的自动分割很重要。
我们开发了一种使用FLAIR MRI对WMHs进行全自动单光谱分割的方法。通过该方法,我们引入了一个用于分割WMHs的最佳阈值强度(IO),其随WMHs体积(VWMH)而变化,并建立了IO-VWMH关系。
与32张验证图像的手动分割WMHs相比,我们的方法在自动分割WMHs的体积和空间一致性方面显示出准确的验证结果。体积一致性的布兰德-奥特曼值为0.96±8.311毫升(偏差和95%置信区间),空间一致性的相似性指数为0.762±0.127(平均值±标准差)。此外,在从不同扫描仪获取的图像中也获得了相似的验证准确性。
所提出的分割方法仅使用FLAIR MRI,对于从不同扫描仪获得的图像有准确分割的潜力,并且可以通过全自动程序实现。在我们的研究中,仅使用了两种扫描仪类型的FLAIR MRI获得了验证结果。该方法的设计可能使其能够高效地用于大型多中心研究。