Objective: To investigate whether structural covariance networks (SCNs) can be used to detect disease-specific patterns of gray matter atrophy in Parkinson’s disease (PD) and secondly, how the integrity of these SCNs correspond with clinical progression.

Background: In PD, the relation between focal cortical brain atrophy on MRI and clinical progression is not straightforward. This is partly caused by insensitivity of MRI to detect subtle changes, but also by the spatial heterogeneity of possible changes. Determination of changes in SCNs, based on high-res 3D-T1-w MRI, has shown to be a more valuable approach than voxel-based techniques in this respect. A decrease in SCN integrity can be regarded as tissue loss of cortical and/or subcortical gray matter.

Methods: MRI was performed in 154 PD patients at a field strength of 3T. For network analysis, 9 standardized SCNs were first identified in 370 healthy controls, with an age range of 45-85 years. These 9 SCNs were used as a template in the analysis of PD data. All SCNs were determined and analyzed within the FSL (FMRIB Software Library tool) framework. Associations between SCN integrity and clinical measures were analyzed using general linear modelling. All analyses were adjusted for age, gender and disease duration. The MDS-UPDRS motor scale was used to quantify severity of motor symptoms. A previously established composite score of predominantly non-dopaminergic (PND) domains (postural instability and gait difficulty, cognitive impairment, depressive symptoms, psychotic symptoms, excessive daytime sleepiness, autonomic dysfunction) was used to measure severity of non-motor symptoms.

Results: Mean age was 64.8 ± 7.3 years; mean disease duration was 9.0 ± 4.5 years. Of the 9 SCNs, 2 networks, the posterior cingulate network and the anterior cingulate network, showed a decreased integrity with an increasing PND score, p=0.003 (partial η²=0.064) and p=0.004 (partial η²=0.061) respectively. In addition, we found an association between the anterior cingulate network integrity and the MDS-UPDRS motor score (p=0.037, partial η²=0.031).

Conclusions: Our data show that in persons with PD, tissue loss in highly specific cortical and subcortical regions in the brain is associated with the presence of more severe non-dopaminergic symptoms. Therefore, determination of SCNs may be useful to further explore disease progression in PD.

« Back to 2016 International Congress

MDS Abstracts - https://www.mdsabstracts.org/abstract/exploring-structural-covariance-networks-of-gray-matter-in-parkinsons-disease/