scholarly journals Levodopa-Responsive Primary Slow Orthostatic Tremor: A Premotor Sign of Parkinson’s Disease?

2020 ◽  
Vol 12 (1) ◽  
pp. 1-6
Author(s):  
Fumihito Yoshii ◽  
Wakoh Takahashi ◽  
Koji Aono
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Surface Electromyography ◽  
Specific Binding ◽  
Low Frequency ◽  
Orthostatic Tremor ◽  
Specific Binding Ratio ◽  
Dopaminergic Medication ◽  
Neurological Signs ◽  
Dat Spect

We present a case of primary orthostatic tremor (OT) responsive to dopaminergic medication. The patient was a 62-year-old woman, who had leg tremor on standing for 2 years. No parkinsonian or other neurological signs were observed. Surface electromyography of the quadriceps muscles showed regular 5–6 Hz muscle discharges. [123I]-FP-CIT DAT-SPECT imaging revealed decreased specific binding ratio values in the striatum compared with age-matched controls. Her leg tremor almost completely disappeared following administration of levodopa 200 mg and pramipexole 0.75 mg. Since her OT with low-frequency discharge was responsive to dopaminergic medication, we speculate that it may be a premotor sign of Parkinson’s disease.

Asymmetric Dopaminergic Dysfunction in Brain-First versus Body-First Parkinson’s Disease Subtypes

2021 ◽  
pp. 1-11
Author(s):  
Karoline Knudsen ◽  
Tatyana D. Fedorova ◽  
Jacob Horsager ◽  
Katrine B. Andersen ◽  
Casper Skjærbæk ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
De Novo ◽  
Specific Binding ◽  
Asymmetry Index ◽  
The Body ◽  
Specific Binding Ratio ◽  
Dat Spect ◽  
Vagal Innervation ◽  
Nigrostriatal Degeneration

Background: We have hypothesized that Parkinson’s disease (PD) comprises two subtypes. Brain-first, where pathogenic α-synuclein initially forms unilaterally in one hemisphere leading to asymmetric nigrostriatal degeneration, and body-first with initial enteric pathology, which spreads through overlapping vagal innervation leading to more symmetric brainstem involvement and hence more symmetric nigrostriatal degeneration. Isolated REM sleep behaviour disorder has been identified as a strong marker of the body-first type. Objective: To analyse striatal asymmetry in [18F]FDOPA PET and [123I]FP-CIT DaT SPECT data from iRBD patients, de novo PD patients with RBD (PD +RBD) and de novo PD patients without RBD (PD - RBD). These groups were defined as prodromal body-first, de novo body-first, and de novo brain-first, respectively. Methods: We included [18F]FDOPA PET scans from 21 iRBD patients, 11 de novo PD +RBD, 22 de novo PD - RBD, and 18 controls subjects. Also, [123I]FP-CIT DaT SPECT data from iRBD and de novo PD patients with unknown RBD status from the PPPMI dataset was analysed. Lowest putamen specific binding ratio and putamen asymmetry index (AI) was defined. Results: Nigrostriatal degeneration was significantly more symmetric in patients with RBD versus patients without RBD or with unknown RBD status in both FDOPA (p = 0.001) and DaT SPECT (p = 0.001) datasets. Conclusion: iRBD subjects and de novo PD +RBD patients present with significantly more symmetric nigrostriatal dopaminergic degeneration compared to de novo PD - RBD patients. The results support the hypothesis that body-first PD is characterized by more symmetric distribution most likely due to more symmetric propagation of pathogenic α-synuclein compared to brain-first PD.

The Association of Visually Guided Saccades and DAT-SPECT Findings in Parkinson’s Disease

2021 ◽  
Vol 84 (2) ◽  
pp. 110-118
Author(s):  
Makoto Kobayashi ◽  
Satoshi Kuwabara
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Target Location ◽  
Photon Emission ◽  
Motor Dysfunction ◽  
Emission Computed Tomography ◽  
Visually Guided ◽  
Specific Binding Ratio ◽  
Dat Spect ◽  
Nigrostriatal Degeneration

<b><i>Background:</i></b> In individuals with Parkinson’s disease (PD), visually guided saccades (VGSs) reportedly reflect general motor dysfunction and cognitive impairments. However, it has not been fully elucidated whether the VGS abnormalities result from nigrostriatal degeneration or other PD-related neural changes. <b><i>Methods:</i></b> We measured VGS latency and gain in 50 PD participants and 56 age-matched normal controls (NCs), and PD participants underwent dopamine transporter (DAT) single-photon emission computed tomography (SPECT) within 2 months of the measurement. VGSs were evoked by a white dot on a monitor, which was presented at the center and pseudo-randomly jumped off horizontally (10° or 20° eccentricity) or vertically (10° or 15°). First, we compared the parameters between PD participants and NCs for each target location. Second, in the participants who exhibited striatal DAT asymmetry on SPECT, VGSs contralaterally directed to the more severely affected striatum were compared with those ipsilaterally directed. Third, effects of the DAT-SPECT specific binding ratio (SBR) on VGSs were analyzed. <b><i>Results:</i></b> PD participants demonstrated prolonged latencies when the target was presented at the upward 15° eccentricity and decreased gains at all target locations. Contralateral VGSs relative to the side of the more severely affected striatum were more delayed and hypometric than ipsilateral. The SBR had a significant positive effect on VGS gain. <b><i>Conclusions:</i></b> In participants with PD, saccadic abnormalities were emphasized when VGSs were directed contralaterally to the more severely affected striatum. Moreover, the dopaminergic nigrostriatal degeneration on DAT-SPECT was mainly associated with VGS gain.

The utility of the combined use of 123I-FP-CIT SPECT and neuromelanin MRI in differentiating Parkinson's disease from other parkinsonian syndromes

2018 ◽  
Vol 60 (2) ◽  
pp. 230-238 ◽  
Author(s):  
Eiji Matsusue ◽  
Yoshio Fujihara ◽  
Kenichiro Tanaka ◽  
Yuki Aozasa ◽  
Manabu Shimoda ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Single Photon ◽  
Photon Emission ◽  
Contrast Ratio ◽  
Emission Computed Tomography ◽  
Specific Information ◽  
Specific Binding Ratio ◽  
Significant Difference ◽  
Dat Spect

Background Neuromelanin magnetic resonance imaging (NmMRI) and 123I-FP-CIT dopamine transporter single photon emission computed tomography (DAT-SPECT) provide specific information that distinguishes Parkinson's disease (PD) from non-degenerative parkinsonian syndrome (NDPS). Purpose To determine whether a multiparametric scoring system (MSS) could improve accuracy compared to each parameter of DAT-SPECT and NmMRI in differentiating PD from NDPS. Material and Methods A total of 49 patients, including 14 with NDPS, 30 with PD, and five with atypical parkinsonian disorder (APD) underwent both NmMRI and DAT-SPECT and were evaluated. The average (Ave) and the asymmetry index (AI) were calculated in the substantia nigra compacta area (SNc-area), SNc midbrain-tegmentum contrast ratio (SNc-CR), and specific binding ratio (SBR). Cut-off values were determined, using receiver operating characteristic (ROC) analysis, for the differentiation of PD from NDPS on the statistically significant parameters. All cases were scored as either 1 (PD) or 0 (NDPS) for each parameter according to its threshold. These individual scores were totaled for each case, yielding a combined score for each case to obtain a cut-off value for the MSS. Results The Ave-SNc-area, Ave-SNc-CR, and Ave-SBR in PD were significantly lower than those in NDPS. The AI-SNc-area and AI-SBR in PD were significantly higher than those in NDPS. Of the five parameters, the highest accuracy was 93% for the Ave-SNc-area. For the MSS, a cut-off value of 3 was the accuracy of 96%. Besides, no significant difference was observed between PD and APD on all parameters. Conclusion An MSS has comparable or better accuracy compared to each parameter of DAT-SPECT and NmMRI in distinguishing PD from NDPS.

Imaging of the nigrostriatal system for evaluating the preclinical phase of Parkinson’s disease development: the utility of neuromelanin, diffusion MRI, and DAT-SPECT

2021 ◽  
Author(s):  
Hiroto Takahashi ◽  
Nobuo Kashiwagi ◽  
Atsuko Arisawa ◽  
Chisato Matsuo ◽  
Hiroki Kato ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Diffusion Tensor ◽  
Specific Binding ◽  
Mean Diffusivity ◽  
Substantia Nigra Pars Compacta ◽  
Nigrostriatal System ◽  
Sleep Behavior ◽  
Specific Binding Ratio ◽  
Preclinical Phase

Objectives: To assess the utility of examining the nigrostriatal system with magnetic resonance imaging (MRI) and dopamine transporter (DAT) imaging for evaluating the preclinical phase of Parkinson’s disease (PD). Methods: The subjects were 32 patients with early PD and a history of probable rapid eye movement sleep behavior disorder (RBD; PD group), 15 patients with idiopathic RBD (RBD group), and 24 age-matched healthy controls (HC group) who underwent neuromelanin and diffusion tensor MRI for analysis of the substantia nigra pars compacta (SNpc). The RBD and PD groups underwent DAT imaging. In the RBD group, totals of 39 MRI and 27 DAT imaging examinations were obtained longitudinally. For each value, intergroup differences and receiver-operating characteristic (ROC) analysis for diagnostic performance were examined statistically. Results: The neuromelanin value was significantly lower and the diffusion tensor values except fractional anisotropy were significantly higher in the RBD and PD groups than in the HC group. The DAT specific binding ratio (SBR) was significantly lower in the PD group than in the RBD group. The areas under the ROC curves (AUCs) for neuromelanin/mean diffusivity value in the SNpc were 0.76/0.82 for diagnosing RBD and 0.83/0.80 for diagnosing PD. The AUC for the SBR for discriminating PD from RBD was 0.87. Conclusions: MRI and DAT imaging may be useful for evaluating sequential nigrostriatal changes during the preclinical phase of PD. Advances in knowledge: MRI detects nigrostriatal changes in both RBD and early PD, and DAT imaging detects nigrostriatal changes during the transition to PD in RBD.

scholarly journals Implications of dopaminergic medication withdrawal in Parkinson’s disease

2021 ◽  
Author(s):  
J. Koschel ◽  
K. Ray Chaudhuri ◽  
L. Tönges ◽  
M. Thiel ◽  
V. Raeder ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Dopaminergic Medication ◽  
Medication Withdrawal

scholarly journals Bringing Advanced Therapies for Parkinson’s Disease to the Clinic: The Scientist’s Perspective

2021 ◽  
pp. 1-6
Author(s):  
Mark Tomishima ◽  
Agnete Kirkeby
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Clinical Trials ◽  
Phase I Clinical Trials ◽  
Preclinical Models ◽  
Preclinical Development ◽  
Dopaminergic Medication ◽  
Gene Therapies ◽  
Advanced Therapies ◽  
New Phase

After many years of preclinical development, cell and gene therapies have advanced from research tools in the lab to clinical-grade products for patients, and today they constitute more than a quarter of all new Phase I clinical trials for Parkinson’s disease. Whereas efficacy has been convincingly proven for many of these products in preclinical models, the field is now entering a new phase where the functionality and safety of these products will need to stand the test in clinical trials. If successful, these new products can have the potential to provide patients with a one-time administered treatment which may alleviate them from daily symptomatic dopaminergic medication.

scholarly journals Using Artificial Neural Network to Discriminate Parkinson’s Disease from Other Parkinsonisms by Focusing on Putamen of Dopamine Transporter SPECT Images

Biomedicines ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 12
Author(s):  
Chung-Yao Chien ◽  
Szu-Wei Hsu ◽  
Tsung-Lin Lee ◽  
Pi-Shan Sung ◽  
Chou-Ching Lin
Keyword(s):  
Neural Network ◽  
Parkinson’S Disease ◽  
Artificial Neural Network ◽  
Support Vector Machine ◽  
Parkinson's Disease ◽  
Dopamine Transporter ◽  
Support Vector ◽  
Dat Spect ◽  
Ann Classifier ◽  
Spect Images

Background: The challenge of differentiating, at an early stage, Parkinson’s disease from parkinsonism caused by other disorders remains unsolved. We proposed using an artificial neural network (ANN) to process images of dopamine transporter single-photon emission computed tomography (DAT-SPECT). Methods: Abnormal DAT-SPECT images of subjects with Parkinson’s disease and parkinsonism caused by other disorders were divided into training and test sets. Striatal regions of the images were segmented by using an active contour model and were used as the data to perform transfer learning on a pre-trained ANN to discriminate Parkinson’s disease from parkinsonism caused by other disorders. A support vector machine trained using parameters of semi-quantitative measurements including specific binding ratio and asymmetry index was used for comparison. Results: The predictive accuracy of the ANN classifier (86%) was higher than that of the support vector machine classifier (68%). The sensitivity and specificity of the ANN classifier in predicting Parkinson’s disease were 81.8% and 88.6%, respectively. Conclusions: The ANN classifier outperformed classical biomarkers in differentiating Parkinson’s disease from parkinsonism caused by other disorders. This classifier can be readily included into standalone computer software for clinical application.

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