McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, 3801 University Street, Montreal, QC, H3A 2B4, Canada,
Int J Comput Assist Radiol Surg. 2015 Mar;10(3):329-41. doi: 10.1007/s11548-014-1068-y. Epub 2014 May 20.
Parkinson's disease (PD) is the second leading neurodegenerative disease after Alzheimer's disease. In PD research and its surgical treatment, such as deep brain stimulation (DBS), anatomical structural identification and references for spatial normalization are essential, and human brain atlases/templates are proven highly instrumental. However, two shortcomings affect current templates used for PD. First, many templates are derived from a single healthy subject that is not sufficiently representative of the PD-population anatomy. This may result in suboptimal surgical plans for DBS surgery and biased analysis for morphological studies. Second, commonly used mono-contrast templates lack sufficient image contrast for some subcortical structures (i.e., subthalamic nucleus) and biochemical information (i.e., iron content), a valuable feature in current PD research.
We employed a novel T1-T2* fusion MRI that visualizes both cortical and subcortical structures to drive groupwise registration to create co-registered multi-contrast (T1w, T2w, T1-T2 fusion, phase, and an R2* map) unbiased templates from 15 PD patients, and a high-resolution histology-derived 3D atlas is co-registered. For validation, these templates are compared against the Colin27 template for landmark registration and midbrain nuclei segmentation.
While the T1w, T2w, and T1-T2 fusion templates provide excellent anatomical details for both cortical and subcortical structures, the phase and R2* map contain the biochemical features. By one-way ANOVA tests, our templates significantly ([Formula: see text]) outperform the Colin27 template in the registration-based tasks.
The proposed unbiased templates are more representative of the population of interest and can benefit both the surgical planning and research of PD.
帕金森病(PD)是仅次于阿尔茨海默病的第二大神经退行性疾病。在 PD 的研究及其手术治疗中,如脑深部电刺激(DBS),解剖结构的识别和空间归一化的参考是必不可少的,而人脑图谱/模板被证明是非常有用的。然而,目前用于 PD 的模板存在两个缺点。首先,许多模板是从单个健康个体中得出的,对 PD 人群的解剖结构不够有代表性。这可能导致 DBS 手术的手术计划不够理想,以及形态学研究的分析存在偏差。其次,常用的单对比度模板对于一些皮质下结构(即丘脑底核)和生化信息(即铁含量)缺乏足够的图像对比度,而这在当前的 PD 研究中是一个有价值的特征。
我们采用了一种新颖的 T1-T2融合 MRI,它可以同时显示皮质和皮质下结构,通过群组配准来创建来自 15 名 PD 患者的配准多对比度(T1w、T2w、T1-T2融合、相位和 R2图)无偏模板,并与高分辨率组织学衍生的 3D 图谱进行配准。为了验证,我们将这些模板与 Colin27 模板进行了基于标志点的配准和中脑核团分割的比较。
虽然 T1w、T2w 和 T1-T2融合模板为皮质和皮质下结构提供了极好的解剖细节,但相位和 R2*图包含了生化特征。通过单向方差分析检验,我们的模板在基于注册的任务中显著([公式:见正文])优于 Colin27 模板。
所提出的无偏模板更能代表感兴趣的人群,可以同时有益于 PD 的手术规划和研究。