scholarly journals 4302 Decreased structural basal ganglia motor loop connections in Vascular Parkinsonism compared to Parkinson’s disease and healthy aging

2020 ◽  
Vol 4 (s1) ◽  
pp. 94-94
Author(s):  
Christine Cooper ◽  
Federico Rodriguez-Porcel ◽  
Travis Turner ◽  
Gonzalo Revuelta ◽  
Jens Jensen ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Basal Ganglia ◽  
Healthy Aging ◽  
Lower Body ◽  
Vascular Parkinsonism ◽  
Whole Brain ◽  
Brain Connectome ◽  
Clinical Scores ◽  
Motor Loop

OBJECTIVES/GOALS: This study uses diffusion kurtosis imaging (DKI) to investigate the structural profiles of basal ganglia (BG) motor circuitry in Vascular Parkinsonism (VP), Parkinson’s disease (PD), and healthy aging controls (HC). VP is a clinical diagnosis of lower body predominant parkinsonism without significant benefit from levodopa. VP is distinct from PD, yet the concept of VP remains debated due to the inability of prior studies to identify specific causative changes. One reason for this may be limitations in measuring intricate BG connectivity in vivo. Given the predominant lower body parkinsonism symptoms in VP, we hypothesized that VP would be associated with decreased connectivity specifically within the BG motor loop. METHODS/STUDY POPULATION: We obtained DKI brain imaging in subjects with VP (N = 7), PD (N = 21), and HCs (N = 58), the latter of which had cardiovascular risk factors but no neurological symptoms. The VP and PD groups were evaluated by a parkinsonism-focused motor exam and brief cognitive testing. We compared BG motor loop connectivity between groups and investigated for correlation between connectivity and clinical scores. To account for differences in fiber counts due to the different imaging scanners and protocols between cohorts, we used a BG motor loop proportion, which was the ratio of the BG motor loop fiber count over a control loop, the visual processing pathway. We used Kruskal-Wallis rank sum test with post-hoc Dunn tests to assess imaging findings between subject groups, and Pearson’s correlation to look for correlation between clinical scores and fiber counts. RESULTS/ANTICIPATED RESULTS: The whole brain connectome showed the fewest number of fibers in VP, followed by PD, and then HC (p<0.0001). The BG motor loop proportion fiber count of the BG motor loop was lower in the VP group, compared to the PD and HC cohorts (p = 0.031). In the VP group, the whole brain connectome fiber count correlated with a gait and balance subscore of the Movement Disorders Society - Unified Parkinson Disease Rating Scale (R = −0.87, p = 0.01). DISCUSSION/SIGNIFICANCE OF IMPACT: This study indicates that VP is associated with decreased structural connectivity, with a disproportionate degree of loss in the BG motor circuitry. While the etiology for this susceptibility to injury and preferential damage to BG remains to be defined, these findings can provide an important starting point for a biological understanding of VP, and a potential future marker for diagnosis and tracking disease progression.

scholarly journals Identifying a Whole-brain Connectome-based Model in Drug-naïve Parkinson’s Disease for Predicting Motor Impairment

2021 ◽  
Author(s):  
Haoting Wu ◽  
Cheng Zhou ◽  
Tao Guo ◽  
Jingjing Wu ◽  
Xueqin Bai ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Predictive Model ◽  
Motor Impairment ◽  
Compensatory Mechanism ◽  
Whole Brain ◽  
Default Mode ◽  
Brain Connectome ◽  
Network Connections ◽  
Drug Naïve

Abstract Background The functional alternation of distinct brain networks contribute to motor impairment in Parkinson’s disease (PD) remains unclear. Identifying a whole-brain connectome-based predictive model (CPM) in drug-naïve patients and verifying its predictability among drug-managed patients would be helpful to detect generalizable brain-behavior association and reflect intrinsic functional underpinning of motor impairment. Methods Resting-state functional data of 47 drug-naïve patients were enrolled to construct a predictive model by using the CPM approach, which was subsequently validated in 115 drug-managed patients. The severity of motor impairment was assessed by calculating Unified Parkinson’s Disease Rating Scale part III (UPDRS III) scores. Predictive performance was evaluated with the correlation coefficient(rtrue) and the mean squared error (MSE) between observed and predicted scores. Results A CPM for predicting individual motor impairment in drug-naïve PD was identified with significant performance (rtrue=0.845, p < 0.001, MSE = 137.57). Two connection patterns were recognized according to the correlation coefficients between the connections’ strength and motor impairment severity. The negative motor-impairment-related network contained more within-network connections in the motor, visual-related, and default mode networks, while the positive motor-impairment-related network was constructed mostly with between-network connections coupled motor-visual, motor-limbic, and motor-basal ganglia networks. The predictability of constructed model was further confirmed in drug-managed patients (r = 0.209, p = 0.025, MSE = 182.96), suggesting generalizability in PD patients with lasting dopaminergic medication influence. Conclusions This study identified a whole-brain connectome-based model that could predict the severity of motor impairment for PD. The connection patterns generated from the model reflected that functional segregation of motor, visual-related, and default mode networks play an important role in PD motor impairment, and higher connections coupling motor and non-motor regions might demonstrate a compensatory mechanism to overcome motor impairment.

scholarly journals Identifying a Whole-brain Connectome-based Model in Drug-naïve Parkinson’s Disease for Predicting Motor Impairment

2021 ◽  
Author(s):  
Haoting Wu ◽  
Cheng Zhou ◽  
Tao Guo ◽  
Jingjing Wu ◽  
Xueqin Bai ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Predictive Model ◽  
Rating Scale ◽  
Motor Impairment ◽  
Predictive Performance ◽  
Whole Brain ◽  
Brain Connectome ◽  
Network Connections ◽  
Drug Naïve

Abstract Identifying a whole-brain connectome-based predictive model in drug-naïve patients with Parkinson’s disease and verifying its predictions on drug-managed patients would be useful in determining the intrinsic functional underpinnings of motor impairment and establishing general brain-behavior associations. In this study, we constructed a predictive model from the resting-state functional data of 47 drug-naïve patients by using a connectome-based approach. This model was subsequently validated in 115 drug-managed patients. The severity of motor impairment was assessed by calculating Unified Parkinson’s Disease Rating Scale Part III scores. The predictive performance of model was evaluated using the correlation coefficient (rtrue) between predicted and observed scores. As a result, a connectome-based model for predicting individual motor impairment in drug-naïve patients was identified with significant performance (rtrue = 0.845, p < 0.001, ppermu = 0.002). Two patterns of connection were identified according to correlations between connection strength and the severity of motor impairment. The negative motor-impairment-related network contained more within-network connections in the motor, visual-related, and default mode networks, whereas the positive motor-impairment-related network was constructed mostly with between-network connections coupling the motor-visual, motor-limbic, and motor-basal ganglia networks. Finally, this predictive model constructed around drug-naïve patients was confirmed with significant predictive efficacy on drug-managed patients (r = 0.209, p = 0.025), suggesting a generalizability in Parkinson’s disease patients under long-term drug influence. In conclusion, this study identified a whole-brain connectome-based model that could predict the severity of motor impairment in Parkinson’s patients and furthers our understanding of the functional underpinnings of the disease.

The influence of Parkinson's disease on the functional connectivity of the motor loop of human basal ganglia

2019 ◽  
Vol 63 ◽  
pp. 100-105 ◽  
Author(s):  
Clara Rodriguez-Sabate ◽  
Ingrid Morales ◽  
Fernando Monton ◽  
Manuel Rodriguez
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Basal Ganglia ◽  
Functional Connectivity ◽  
Motor Loop

SPECT-Befunde bei Hemiparkinson-Syndrom mit 99mTc-HMPAO

1989 ◽  
Vol 28 (03) ◽  
pp. 92-94 ◽  
Author(s):  
C. Neumann ◽  
H. Baas ◽  
R. Hefner ◽  
G. Hör
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Basal Ganglia ◽  
Neuronal Activity ◽  
Tracer Uptake ◽  
The Body ◽  
99Mtc Hmpao ◽  
Do So

The symptoms of Parkinson’s disease often begin on one side of the body and continue to do so as the disease progresses. First SPECT results in 4 patients with hemiparkinsonism using 99mTc-HMPAO as perfusion marker are reported. Three patients exhibited reduced tracer uptake in the contralateral basal ganglia One patient who was under therapy for 1 year, showed a different perfusion pattern with reduced uptake in both basal ganglia. These results might indicate reduced perfusion secondary to reduced striatal neuronal activity.

scholarly journals Corticostriatal Plastic Changes in Experimental L-DOPA-Induced Dyskinesia

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Veronica Ghiglieri ◽  
Vincenza Bagetta ◽  
Valentina Pendolino ◽  
Barbara Picconi ◽  
Paolo Calabresi
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Basal Ganglia ◽  
Experimental Models ◽  
Striatal Neurons ◽  
Da Receptors ◽  
Electrophysiological Studies ◽  
Plastic Changes ◽  
Stimulation Of

In Parkinson’s disease (PD), alteration of dopamine- (DA-) dependent striatal functions and pulsatile stimulation of DA receptors caused by the discontinuous administration of levodopa (L-DOPA) lead to a complex cascade of events affecting the postsynaptic striatal neurons that might account for the appearance of L-DOPA-induced dyskinesia (LID). Experimental models of LID have been widely used and extensively characterized in rodents and electrophysiological studies provided remarkable insights into the inner mechanisms underlying L-DOPA-induced corticostriatal plastic changes. Here we provide an overview of recent findings that represent a further step into the comprehension of mechanisms underlying maladaptive changes of basal ganglia functions in response to L-DOPA and associated to development of LID.

scholarly journals The whole-brain pattern of magnetic susceptibility perturbations in Parkinson’s disease

Brain ◽  
2016 ◽  
Vol 140 (1) ◽  
pp. 118-131 ◽  
Author(s):  
Julio Acosta-Cabronero ◽  
Arturo Cardenas-Blanco ◽  
Matthew J. Betts ◽  
Michaela Butryn ◽  
Jose P. Valdes-Herrera ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Magnetic Susceptibility ◽  
Whole Brain ◽  
Brain Pattern
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