Arterial spin labeling MRI based perfusion pattern related to motor dysfunction and L-DOPA reactivity in Parkinson's disease

Abstract

Objective: Identifying intrinsic pattern of Parkinson's disease (PD) helps to better understand of PD and provide insights to disease identification and treatment monitoring. Here we confirmed the PD-related covariance pattern (PDRP) by using arterial spin labelling technology (ASL-PDRP) and explore its potential for predicting motor progression and levodopa (L-DOPA) reactivity reduction.

Methods: Data from an original cohort of 179 PD and 62 normal controls (NC) and a validation cohort including 36 PD and 19 NC to construct and validate the ASL-PDRP. The correlations between the pattern and motor symptoms were analyzed cross-sectionally and longitudinally (71 PD owned longitudinal data) with hierarchical linear regression analysis. Kaplan-Meier analysis was conducted in 54 L-DOPA-managed PD patients to predict the levodopa reactivity reduction.

Results: The first principal component was predominantly recognized as the ASL-PDRP, with its expression being higher in PD than NC in both sets (original: P = 0.017, AUC = 0.598; validation: P = 0.024, AUC = 0.661). The pattern expression was associated with UPDRS III (P = 0.006) and sub-symptoms (axial: P < 0.001; rigidity: P = 0.003; bradykinesia: P = 0.015) at baseline. The ASL-PDRP could predict the progression of UPDRS III (P = 0.021, β = 4.930). Higher expression of the pattern had slower rate of levodopa reactivity reduction in PD patients with axial symptom (P = 0.031).

Conclusion: The identified ASL-PDRP may have potential for characterizing PD with the ability to predict motor progression and L-DOPA reactivity reduction.

Keywords: Arterial spin labelling; Levodopa reactivity; Magnetic resonance imaging; Motor symptoms; Neuroimaging; Parkinson’s disease; Pattern.

Graphical abstract

Fig. 1

Overview of the study methodology. A. The process of inclusion and exclusion of subjects and the total sample was divided into the original and validation sets according to inclusion time. B. PCA-SSM analysis was employed to help identify the PD-related perfusion pattern. C. The PD-related perfusion pattern could be detected in an independent validation set with TPR algorithm, and AUC value, sensitivity, specificity were calculated to assess efficiency of pattern. D. Clinical data were collected before and after follow-up and correlated with the PD-related perfusion pattern. There were 71 of 179 PD patients owning longitudinal clinical data. E. There were 54 L-DOPA-managed PD patients owning longitudinal clinical data. Multivariate Cox regression analysis and Kaplan-Meier curve was applied to explore the effect of high/low expression of the PD-related perfusion pattern on motor-specific L-DOPA reactivity. Abbreviations: PD = Parkinson's disease; NC = Normal controls; Repeated CV = Repeated Cross Validation; AUC = Area under curve; L-DOPA = levodopa.

Fig. 2

A. Axial orthogonal tomographic views of ASL-PDRP from the original cohort, overlaid on a standard anatomical MRI template. The stability of ASL-PDRP was confirmed through 500 repetitions of cross-validation. The ASL-PDRP maps illustrated relatively higher perfusion weight in the warm color regions and relatively lower perfusion weight in the cool color regions. A threshold of |z| > 1.96 was used to identify voxels that significantly contributed to the PC patterns, corresponding to a two-tailed P < 0.05¹⁵. B. The ROC curves of the 8 PCs and PC_all were examined to determine their ability to distinguish PD_ori from NC_ori in original set (179 PD + 62 NC). C. Differences in network expression scores of ASL-PDRP between the PD and NC groups were evaluated in both the original and validation sets, respectively. * P < 0.05, ** P < 0.01, *** P < 0.001. Abbreviations: PD_ori, PD_val = PD patients in original or validation cohort; NC_ori, NC_val = normal controls in original or validation cohort. PC_all = linear logistic regression combination of PC1, PC3, PC4, PC7, PC11, PC12, PC14 and PC15.

Fig. 3

Partial Correlation Analysis between PC1 and UPDRS III / its sub-scores at baseline in original cohort. The expression of PC1 exhibited a significant association with symptoms such as axial, rigidity, UPDRS III, and bradykinesia, but not tremor. The vertical coordinate on the right side represented the P value, while the horizontal coordinate represented the partial correlation coefficients. Gender and age were included as covariates in the analysis. Abbreviations: UPDRS III = Unified Parkinson’s Disease Rating Scale scores of motor.

Fig. 4

Baseline expression of PC1 predicted L-DOPA reactivity reduction in L-DOPA-administered PD subjects with axial symptom. The L-DOPA reactivity reduction was analyzed in 54 L-DOPA-administered PD. In Kaplan-Meier curve analysis, higher baseline expression of PC1 (> 0.282) was associated with slower rate of L-DOPA reactivity reduction in PD patients with axial symptom. An outcome event was defined as reduced L-DOPA reactivity (improvement rate less than 30 % in axial symptom) following L-DOPA treatment. The event time referred to the number of months of follow-up.