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Functional brain connectome architecture in a large cohort of Parkinson’s disease patients
Silvia Basaia1, Federica Agosta1, Homa Zahedmanesh1,2, Tanja Stojkovic3, Vladana Markovic3, Iva Stankovic3, Igor Petrovic3, Elka Stefanova3, Vladimir Kostic3, and Massimo Filippi1,4

1Neuroimaging Research Unit, INSPE, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy, 2Department of Electronics, Information, and Bioengineering (DEIB), Politecnico di Milano, Milano, Italy, 3Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Yugoslavia, 4Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy

Synopsis

In this study, we investigated functional neural pathway organization in patients with Parkinson’s disease (PD) using advanced network-based techniques. At the regional network level, compared to controls, PD groups showed decreased functional connectivity within basal ganglia/sensorimotor network and parietal regions. Compared to early PD cases, mild-to-severe PD patients were characterized by a greater involvement of basal ganglia/sensorimotor networks. This study suggests that graph analysis and connectomics might represent a powerful approach to understand the pathophysiological process across different stages of the disease.

Introduction

Graph analysis and connectomics may be a powerful approach to assess brain network degradation in PD. In particular, in this study we investigated functional neural pathway organization in patients with Parkinson’s disease (PD) using advanced network-based techniques.

Methods

134 PD patients (82 early PD [Hoehn and Yahr {HY} 1-1.5] and 52 mild-to-severe PD [HY 2-4]) and 99 age- and sex-matched controls performed clinical evaluation and resting state functional MRI (RS fMRI). Graph analysis and connectomics assessed global and local topological network properties and regional functional connectivity (FC). The human macroscale connectome was constructed from RS fMRI. RS fMRI images were pre-processed using FSL. Preprocessing consisted of motion correction, removal of nonbrain tissue, spatial smoothing using a 6 mm full width at half maximum Gaussian kernel, and high-pass temporal filtering equivalent to 100 s (0.01 Hz). FC matrices were obtained on the basis of correlation analysis. A mean RS fMRI time-series was obtained averaging over the time-series of all voxels contained in brain region i. Likewise, a mean RS fMRI time-series was obtained for region i. The Pearson correlation coefficient between these mean time-series, indicating the level of FC between regions i and j, entered into cell c(i,j) of the matrix. Negative correlation coefficients, reflecting functional distinct brain regions, were set to 0 to mark these brain regions as unconnected. Affected functional connections were investigated using Network-Based Statistic (p<0.01, 10.000 permutations).

Results

Compared with controls, PD groups did not show altered global functional network properties. However, they showed altered functional topological features (lower mean nodal strength and longer mean path length) of the sensorimotor and parietal lobes relative to controls, with mild-to-severe cases showing the greatest alterations. Moreover, mild-to-severe PD patients had a reduced mean nodal strength in the temporal lobe relative to early PD patients. At the regional network level, compared to controls, PD groups showed decreased FC within basal ganglia/sensorimotor network (involving right caudate, and thalamus, putamen, precentral, paracentral and postcentral gyri bilaterally), parietal regions such as posterior cingulate and precuneus bilaterally, and bilateral superior frontal and middle temporal areas. Compared to early PD cases, mild-to-severe PD patients were characterized by a greater involvement of basal ganglia/sensorimotor connections linking putamen, caudate and postcentral gyri bilaterally, parietal network involving posterior cingulate, precuneus and supramarginal bilaterally, and pathways to the bilateral hippocampus.

Discussion

This study showed widespread motor and extra-motor functional network degeneration in PD patients at different disease stage. Furthermore, this study suggests that graph analysis and connectomics might represent a powerful approach to understand the pathophysiological process across different stages of the disease.

Conclusions

Network-based advanced MRI analyses might help understanding the pathophysiological process across different stages of PD and hold promise to provide an objective in vivo marker of disease-related pathological changes.

Acknowledgements

Supported by the Ministry of Education and Science Republic of Serbia (Grant #175090).

References

No reference found.
Proc. Intl. Soc. Mag. Reson. Med. 26 (2018)
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