Objective: The objective of this study was to analyze the differences in structural connectivity and white matter (WM) microstructural integrity in people with early-PD over a 12-month follow-up.

Background: Parkinson’s disease (PD) is a neurodegenerative disease that leads to significant disability and morbidity [1]. Diffusion tensor imaging (DTI) using MRI informs white matter (WM) alterations using fractional anisotropy (FA). Additionally, structural connectivity can be investigated with tractography [2]. Here, we used a novel and expanded approach to analyze structural connectivity and WM integrity in people with early-PD over a 12-month follow-up (baseline and M12). Data were downloaded from the PPMI database.

Method: Thirty-five unmedicated early-PD (baseline-age mean ± S.D. = 62 ± 10 years; 13 females) were included. All subjects completed the geriatric depression scale (GDS) test. Pre-processing was performed by Mrtrix3 [3], FSL [4], and ANTs. Tractography was performed with 5 million seeds using the iFOD2 algorithm [5]. The connectome was generated from the Desikan-Killiany parcellation file from FreeSurfer. The COMMIT2 algorithm [6] was used to re-establish the correct link between tractography and tissue microstructure. A two-compartment Ball-and-Stick model was used to generate intracellular (IC) and isotropic (ISO) compartments.

Results: The two time-points (TPs) did not differ in GDS (Wilcoxon Signed-Ranks: Z=-0.3571; p=0.71884). Surprisingly, compared with the baseline, higher values of FA and IC and lower values of ISO were found at M12 in several WM areas. (Figures 1 and Table 1). Connectometry analysis found differences between TPs in seven tracts with M12>baseline, and in other five tracts with M12<baseline (Figure 2 and Table 2).

Conclusion: We used a robust processing of DTI data to detect alterations in WM integrity and structural connectivity in early-PD. Other longitudinal studies using PPMI have shown increased FA during follow-up, which may be due to DTI limitations in regions of crossing fibers [7]. Here, we used an analytic approach that can specifically overcome such limitations related to crossing fibers. Our results demonstrate that elevated FA, IC, and structural connectivity in early-PD after 12 months cannot merely be attributed to methodological confounding factors, but rather may indicate true pathophysiological evolution in PD.

References: [1] de Lau LM, Breteler MM. Epidemiology of Parkinson’s disease. Lancet Neurol. 2006;5(6):525-35. [2] Yeh CH, Jones DK, Liang X, Descoteaux M, Connelly A. Mapping Structural Connectivity Using Diffusion MRI: Challenges and Opportunities. J Magn Reson Imaging. 2020 Jun 17. doi: 10.1002/jmri.27188. [3] Tournier JD, Smith R, Raffelt D, et al. MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation. NeuroImage. 2019;202:116137. [4] Jenkinson M, Beckmann CF, Behrens TE, Woolrich MW, Smith SM. FSL. NeuroImage. 2012;62(2):782-790 [5] Willats L, Raffelt D, Smith RE, Tournier JD, Connelly A, Calamante F. Quantification of track-weighted imaging (TWI): characterisation of within-subject reproducibility and between-subject variability. NeuroImage. 2014;87:18-31. [6] Schiavi S, Ocampo-Pineda M, Barakovic M, Petit L, Descoteaux M, Thiran JP, Daducci A. A new method for accurate in vivo mapping of human brain connections using microstructural and anatomical information. Sci Adv. 2020 Jul 29;6(31): eaba8245. doi: 10.1126/sciadv.aba8245. eCollection 2020 Jul. [7] Tuch DS , Reese TG, Wiegell MR, Wedeen VJ. Diffusion MRI of complex neural architecture. Neuron. 2003 Dec 4;40(5):885-95. doi: 10.1016/s0896-6273(03)00758-x.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/analysis-of-brain-structural-connectivity-networks-and-white-matter-integrity-in-patients-with-early-parkinsons-disease-a-longitudinal-study/