0541
Progressive microstructural alterations in subcortical nuclei in Parkinson's disease: a diffusion magnetic resonance imaging study1The second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
Synopsis
In this study, we employed diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) to measure the microstructural alterations in subcortical nuclei across PD patients at different disease stages. Individual diagnostic model was constructed to test the performance of diffusion metrics in identifying PD patients at different stages. We found that PD patients at different stages have progressive microstructural alterations in the main nuclei of widely acknowledged nigral-pallidal and thalamo-cortical pathways. DKI is sensitive to detect microstructural changes in GP and thalamus between early stage PD and moderate-late stage PD patients. The combination of kurtosis and tensor metrics can achieve a good performance in diagnosing PD.
Abstract
Background：In clinical practice, Parkinson's disease (PD) patients at different disease stages may present differential manifestations and may show different progressive rates. The heterogeneous clinical symptoms in PD indicate that the degenerative patterns of the nigrostrital-nigropallidal and thalamo-cortical pathways may be different during PD progression, which have yet to be elucidated.Objectives: In the present study, we aim to explore the microstructural alterations in subcortical nuclei across Parkinson's disease (PD) patients at different stages with diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) techniques and to test the performance of diffusion metrics in identifying PD patients at different stages.
Methods: 110 PD patients and 64 healthy controls (HC) were recruited. According to the Hoehn-Yahr stage, 65 patients with Hoehn–Yahr stage ≤ 2 were grouped into the early-stage PD (EPD) group, and 45 patients with Hoehn–Yahr stage ≥ 2.5 were grouped into the moderate-late-stage PD (MLPD) group. All subjects were scanned on a 3.0 Tesla MR imaging system (Discovery MR750, GE Healthcare). Two-shell diffusion images were acquired using spin-echo echo-planar imaging sequence with 60 gradient directions for non-zero b values (b value = 1000 s/mm2, 30 directions; b value = 2000 s/mm2, 30 directions); Diffusion images were preprocessed using FMRIB Software Library (FSL, https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/), including the brain extraction and the correction of eddy current distortion and inter-volume head motion. After the data preprocessing, tensor and kurtosis metrics, including fractional anisotropy (FA) and mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), mean kurtosis (MK), axial kurtosis (AK), and radial kurtosis (RK) were estimated using a constrained weighted linear least squares approach by Diffusion Kurtosis Imaging Matlab Toolbox (https://cai2r.net/resources/software/diffusion-kurtosis-imaging-matlab-toolbox). Regions of interest (ROI) include bilateral substantia nigra (SN), caudate head, putamen, globus pallidus (GP) and thalamus (Fig. 1). FA, MD, AD, RD, MK, AK, RK in the subcortical nuclei were compared among the three groups. Partial correlation was used to correlate the diffusion metrics and Unified Parkinson's Disease Rating Scale part-III (UPDRS-III) score. Logistic regression and receiving operator characteristic analayses were applied to test the diagnostic performance of the diffusion metrics.
Results: Compared with HC, both EPD and MLPD patients showed higher FA and AD, lower MK and AK in substantia nigra, lower MK and RK in GP and thalamus (all p < 0.05) (Fig. 2). Higher MD in SN and lower FA in thalamus were only detected in MLPD (both p < 0.05). Compared with EPD patients, MLPD showed lower MK, RK in GP and thalamus (all p < 0.05), while no significant diffusion metrics difference in SN was observed. No significant diffusion difference in other nuclei (e.g., caudate nucleus and putamen) was observed among the three groups. MK and RK in GP and thalamus were negatively correlated with UPDRS-III score ((MK in the GP: r = - 0.316, p = 0.001; RK in the GP: r = - 0.346, p < 0.001; MK in the thalamus: r = - 0.394, p < 0.001; RK in the thalamus: r = - 0.392, p < 0.001) (Fig. 3). Before binary logistic regression analysis, no significant multi-colliearity among the diffusional metrics was observed. In detail, the metrics comprising the discriminating combination from the regression model for PD were: FA, MD, and AK in SN, RK in GP, and MK in thalamus. The ROC curves of the altered diffusion metrics with statistical significance in logistic regression model and their combinations from the model for discriminating PD patients from HC or between EPD (and MLPD) and HC are presented in Fig. 4. The combination of kurtosis and tensor metrics from different nuclei contributed to a better diagnostic performance than that from derived from each metric (all p < 0.05). The AUC of combined metrics to diagnose PD, EPD, MLPD were 0.833 (95% CI: 0.692-0.854), 0.773 (95% CI: 0.772-0.894), and 0.931 (95% CI: 0.884-0.978), respectively(Fig. 4).
Conclusions: PD patients at different stages have progressive microstructural alterations in the main nuclei of widely acknowledged nigral-pallidal and thalamo-cortical pathways. DKI is sensitive to detect microstructural changes in GP and thalamus between EPD and MLPD and the combination of kurtosis and tensor metrics can achieve a good performance in diagnosing PD.
Acknowledgements
We would like to thank all our subjects for participating this research. This study was supported by the 13th Five-year Plan for National Key Research and Development Program of China (Grant No. 2016YFC1306600), the National Natural Science Foundation of China (Grant Nos. 81971577, 81571654, 81701647 and 81771820).References
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