Cognitive impairment in Parkinson’s Disease (PD) is the most prevalent non-motor symptom that requires analysis of anatomical associations to cognitive decline in PD. The objective of this study is to analyse the morphological variations of the subcortical structures to assess cognitive dysfunction in PD. In this study, T1 MR images of 58 Healthy Control (HC) and 135 PD subjects categorised as 91 Cognitively normal PD (NC-PD), 25 PD with Mild Cognitive Impairment (PD-MCI) and 19 PD with Dementia (PD-D) subjects, based on cognitive scores are utilised. The 132 anatomical regions are segmented using spatially localized multi-atlas model and volumetric analysis is carried out. The morphological alterations through textural features are captured to differentiate among the HC and PD subjects under different cognitive domains. The volumetric differences in the segmented subcortical structures of accumbens, amygdala, caudate, putamen and thalamus are able to predict cognitive impairment in PD. The volumetric distribution of the subcortical structures in PD-MCI subjects exhibit an overlap with the HC group due to lack of spatial specificity in their atrophy levels. The 3D GLCM features extracted from the significant subcortical structures could discriminate HC, NC-PD, PD-MCI and PD-D subjects with better classification accuracies. The disease related atrophy levels of the subcortical structures captured through morphological analysis provide sensitive evaluation of cognitive impairment in PD.

帕金森病 (PD) 的认知障碍是最常见的非运动症状，需要分析与 PD 认知能力下降的解剖学关联。本研究的目的是分析皮质下结构的形态变化，以评估帕金森病的认知功能障碍。在这项研究中，58 名健康对照 (HC) 和 135 名帕金森病受试者的 T1 MR 图像被分类为 91 名认知正常帕金森病 (NC-PD)、25 名患有轻度认知障碍的帕金森病 (PD-MCI) 和 19 名患有痴呆症的帕金森病 (PD-D) ）使用基于认知分数的受试者。使用空间局部多图谱模型对 132 个解剖区域进行分割，并进行体积分析。通过捕获纹理特征的形态变化来区分不同认知领域下的 HC 和 PD 受试者。伏隔核、杏仁核、尾状核、壳核和丘脑分段皮质下结构的体积差异能够预测帕金森病的认知障碍。PD-MCI 受试者皮质下结构的体积分布与 HC 组重叠，因为其萎缩水平缺乏空间特异性。从重要皮质下结构中提取的 3D GLCM 特征可以以更好的分类精度区分 HC、NC-PD、PD-MCI 和 PD-D 受试者。通过形态学分析捕获的皮层下结构的疾病相关萎缩水平为帕金森病认知障碍提供了敏感的评估。