Garg Amanmeet, Appel-Cresswell Silke, Popuri Karteek, McKeown Martin J, Beg Mirza Faisal
Medical Image Analysis Laboratory, School of Engineering Science, Simon Fraser University Burnaby, BC, Canada.
Neurology, Pacific Parkinson's Research Center, University of British Columbia Vancouver, BC, Canada.
Front Neurosci. 2015 Mar 31;9:101. doi: 10.3389/fnins.2015.00101. eCollection 2015.
Like many neurodegenerative diseases, the clinical symptoms of Parkinsons disease (PD) do not manifest until significant progression of the disease has already taken place, motivating the need for sensitive biomarkers of the disease. While structural imaging is a potentially attractive method due to its widespread availability and non-invasive nature, global morphometric measures (e.g., volume) have proven insensitive to subtle disease change. Here we use individual surface displacements from deformations of an average surface model to capture disease related changes in shape of the subcortical structures in PD. Data were obtained from both the University of British Columbia (UBC) [n = 54 healthy controls (HC) and n = 55 Parkinsons disease (PD) patients] and the publicly available Parkinsons Progression Markers Initiative (PPMI) [n = 137 (HC) and n = 189 (PD)] database. A high dimensional non-rigid registration algorithm was used to register target segmentation labels (caudate, putamen, pallidum, and thalamus) to a set of segmentation labels defined on the average-template. The vertex-wise surface displacements were significantly different between PD and HC in thalamic and caudate structures. However, overall displacements did not correlate with disease severity, as assessed by the Unified Parkinson's Disease Rating Scale (UPDRS). The results from this study suggest disease-relevant shape abnormalities can be robustly detected in subcortical structures in PD. Future studies will be required to determine if shape changes in subcortical structures are seen in the prodromal phases of the disease.
与许多神经退行性疾病一样,帕金森病(PD)的临床症状直到疾病已经有显著进展时才会显现,这促使人们需要灵敏的疾病生物标志物。虽然结构成像因其广泛可用性和非侵入性的特点而具有潜在吸引力,但整体形态测量指标(如体积)已被证明对细微的疾病变化不敏感。在此,我们利用平均表面模型变形产生的个体表面位移来捕捉帕金森病患者皮质下结构形状的疾病相关变化。数据来自英属哥伦比亚大学(UBC)[n = 54名健康对照者(HC)和n = 55名帕金森病(PD)患者]以及公开可用的帕金森病进展标志物倡议(PPMI)[n = 137名(HC)和n = 189名(PD)]数据库。使用一种高维非刚性配准算法将目标分割标签(尾状核、壳核、苍白球和丘脑)配准到在平均模板上定义的一组分割标签。在丘脑和尾状核结构中,帕金森病患者和健康对照者之间的逐顶点表面位移存在显著差异。然而,如统一帕金森病评定量表(UPDRS)所评估的,整体位移与疾病严重程度不相关。本研究结果表明,在帕金森病患者的皮质下结构中可以可靠地检测到与疾病相关的形状异常。未来的研究将需要确定在疾病的前驱期是否能观察到皮质下结构的形状变化。