scholarly journals Visual Impairments Are Associated With Retinal Microvascular Density in Patients With Parkinson’s Disease

2021 ◽  
Vol 15 ◽  
Author(s):  
Min Zhou ◽  
Lei Wu ◽  
Qinyuan Hu ◽  
Congyao Wang ◽  
Jiacheng Ye ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Visual Impairment ◽  
Characteristic Curve ◽  
Microvascular Density ◽  
Inner Plexiform Layer ◽  
Healthy Controls ◽  
Fiber Layer ◽  
P100 Latency ◽  
Retinal Microvasculature

ObjectiveThis study aimed to evaluate retinal microvascular density in patients with Parkinson’s disease (PD) and its correlation with visual impairment.MethodsThis cross-sectional study included 24 eyes of 24 patients with PD and 23 eyes of 23 healthy controls. All participants underwent ophthalmic examination, visual evoked potential (VEP) test, 25-item National Eye Institute Visual Function Questionnaire (NEI VFQ-25), and optical coherence tomography angiography (OCTA) examination. The correlation between retinal microvascular density and visual parameter was evaluated using Spearman correlation analysis, and the area under receiver operating characteristic curve (AUROC) was calculated.ResultsParkinson’s disease patients had prolonged P100 latency (P = 0.041), worse vision-related quality of life (composite score and 3 of 12 subscales in NEI VFQ-25), and decreased vessel density (VD) in all sectors of 3-mm-diameter region (all P < 0.05) compared with healthy controls. There were no statistical differences in the ganglion cell-inner plexiform layer (GCIPL) thickness and retinal nerve fiber layer (RNFL) thickness between the two groups. A negative correlation was found between P100 latency and nasal and superior sectors of macular VD in a 3-mm-diameter region (r = −0.328, P = 0.030; r = −0.302, and P = 0.047, respectively). Macular VD in a 3-mm-diameter region showed diagnostic capacities to distinguish PD patients from healthy controls (AUROCs, ranging from 0.655 to 0.723).ConclusionThis study demonstrated that decreased retinal microvascular density was correlated with visual impairment in PD patients. Retinal microvasculature change may occur earlier than visual decline and retinal structure change and has the potential to be a promising diagnostic marker for early PD.

scholarly journals Foveal Remodeling of Retinal Microvasculature in Parkinson’s Disease

2021 ◽  
Vol 15 ◽  
Author(s):  
Ane Murueta-Goyena ◽  
Maitane Barrenechea ◽  
Asier Erramuzpe ◽  
Sara Teijeira-Portas ◽  
Marta Pengo ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Diagnostic Accuracy ◽  
Rating Scale ◽  
Cognitive Status ◽  
Retinal Layer ◽  
Inner Plexiform Layer ◽  
Retinal Microvasculature ◽  
Microvascular Alterations ◽  
Perfusion Density

BackgroundRetinal microvascular alterations have been previously described in Parkinson’s disease (PD) patients using optical coherence tomography angiography (OCT-A). However, an extensive description of retinal vascular morphological features, their association with PD-related clinical variables and their potential use as diagnostic biomarkers has not been explored.MethodsWe performed a cross-sectional study including 49 PD patients (87 eyes) and 40 controls (73 eyes). Retinal microvasculature was evaluated with Spectralis OCT-A and cognitive status with Montreal Cognitive Assessment. Unified PD Rating Scale and disease duration were recorded in patients. We extracted microvascular parameters from superficial and deep vascular plexuses of the macula, including the area and circularity of foveal avascular zone (FAZ), skeleton density, perfusion density, vessel perimeter index, vessel mean diameter, fractal dimension (FD) and lacunarity using Python and MATLAB. We compared the microvascular parameters between groups and explored their association with thickness of macular layers and clinical outcomes. Data were analyzed with General Estimating Equations (GEE) and adjusted for age, sex, and hypertension. Logistic regression GEE models were fitted to predict diagnosis of PD versus controls from microvascular, demographic, and clinical data. The discrimination ability of models was tested with receiver operating characteristic curves.ResultsFAZ area was significantly smaller in patients compared to controls in superficial and deep plexuses, whereas perfusion density, skeleton density, FD and lacunarity of capillaries were increased in the foveal zone of PD. In the parafovea, microvascular parameters of superficial plexus were associated with ganglion cell-inner plexiform layer thickness, but this was mainly driven by PD with mild cognitive impairment. No such associations were observed in controls. FAZ area was negatively associated with cognition in PD (non-adjusted models). Foveal lacunarity, combined with demographic and clinical confounding factors, yielded an outstanding diagnostic accuracy for discriminating PD patients from controls.ConclusionParkinson’s disease patients displayed foveal microvascular alterations causing an enlargement of the vascular bed surrounding FAZ. Parafoveal microvascular alterations were less pronounced but were related to inner retinal layer thinning. Retinal microvascular abnormalities helped discriminating PD from controls. All this supports OCT-A as a potential non-invasive biomarker to reveal vascular pathophysiology and improve diagnostic accuracy in PD.

scholarly journals TOMOGRAFÍA DE COHERENCIA ÓPTICA COMO MARCADOR PARA LAS ENFERMEDADES NEURODEGENERATIVAS DE ALZHEIMER Y PARKINSON.

2021 ◽  
Vol 32 (1) ◽  
Author(s):  
Victoria Coba ◽  
Cristina Paredes ◽  
Jorge Rivera
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Optical Coherence Tomography ◽  
Review Literature ◽  
Observational Research ◽  
Inner Plexiform Layer ◽  
Optical Coherence ◽  
Fiber Layer ◽  
Ancillary Test ◽  
Potential Biomarker

Background: Optical coherence tomography (OCT) is an ancillary test used in retinal pathology. The objective of the present dissertation is to review literature regarding (OCT) and its importance as a biomarker in neurodegenerative Alzheimer’s and Parkinson’s disease, through an analysis of medical journal articles published between 2015 and 2019. Methods: A retrospective systematic review without meta-analysis of literature was carried out using observational research design, allowing to summarize the results of multiple primary investigations. Ten studies published between 2015 and 2019 regarding the application of OCT and ANGIO OCT in adult patients older than 60 years of age with preclinical Alzheimer’s disease (AD) or Parkinson’s disease (PD) with retinal microvascular abnormalities, were selected. Results: Areas of increased thickness of ganglion cell-inner plexiform layer (GCIPL) and nerve fiber layer (NFL) adyacent to the macula suggest that dynamic changes can occur as a result of AD progression. Thinning of the retina is present during early stages of PD. This correlates with disease severity and may be related to degeneration of dopaminergic neurons in the substantia nigra. Conclusion: Optical Coherence Tomography is a potential biomarker for AD and PD, and if these pathologies are suspected early, and if these pathologies are suspected early, it could be requested as diagnostic support.

scholarly journals Soluble Triggering Receptor Expressed on Myeloid Cells 2 From Cerebrospinal Fluid in Sleep Disorders Related to Parkinson’s Disease

2021 ◽  
Vol 13 ◽  
Author(s):  
Mingshu Mo ◽  
Yuting Tang ◽  
Lijian Wei ◽  
Jiewen Qiu ◽  
Guoyou Peng ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Sleep Disorders ◽  
Characteristic Curve ◽  
Myeloid Cells ◽  
Diagnostic Value ◽  
Healthy Controls ◽  
Potential Biomarker ◽  
The Central Nervous System ◽  
The Relationship

Background: Triggering receptor expressed on myeloid cells 2 (TREM2) is a microglial receptor exclusively expressed in the central nervous system (CNS). It contributes to abnormal protein aggregation in neurodegenerative disorders, but its role in Parkinson’s disease (PD) is still unclear.Methods: In this case-control study, we measured the concentration of the soluble fragment of TREM2 (sTREM2) in PD patients, evaluated their sleep conditions by the PD sleep scale (PDSS), and analyzed the relationship between sTREM2 and PD symptoms.Results: We recruited 80 sporadic PD patients and 65 healthy controls without disease-related variants in TREM2. The concentration of sTREM2 in the CSF was significantly higher in PD patients than in healthy controls (p < 0.01). In the PD group, the concentration of sTREM2 had a positive correlation with α-syn in the CSF (Pearson r = 0.248, p = 0.027). Receiver operating characteristic curve (ROC) analyses showed that sTREM2 in the CSF had a significant diagnostic value for PD (AUC, 0.791; 95% CI, 0.711–0.871, p < 0.05). The subgroup analysis showed that PD patients with sleep disorders had a significantly higher concentration of sTREM2 in their CSF (p < 0.01). The concentration of sTREM2 in the CSF had a negative correlation with the PDSS score in PD patients (Pearson r = −0.555, p < 0.01). The ROC analyses showed that sTREM2 in the CSF had a significant diagnostic value for sleep disorders in PD (AUC, 0.733; 95% CI, 0.619–0.846, p < 0.05).Conclusion: Our findings suggest that CSF sTREM2 may be a potential biomarker for PD and it could help predict sleep disorders in PD patients, but multicenter prospective studies with more participants are still needed to confirm its diagnostic value in future.

scholarly journals Meta-Analysis of Visual Evoked Potential and Parkinson’s Disease

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Song-bin He ◽  
Chun-yan Liu ◽  
Lin-di Chen ◽  
Zhi-nan Ye ◽  
Ya-ping Zhang ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Visual Evoked Potential ◽  
Evoked Potential ◽  
Meta Analysis ◽  
Case Control ◽  
Healthy Controls ◽  
Case Control Studies ◽  
P100 Latency ◽  
Visual Evoked

Background. Previous studies suggested that visual evoked potential (VEP) was impaired in patients with Parkinson’s disease (PD), but the results were inconsistent. Methods. We conducted a systematic review and meta-analysis to explore whether the VEP was significantly different between PD patients and healthy controls. Case-control studies of PD were selected through an electronic search of the databases PubMed, Embase, and the Cochrane Central Register of Controlled Trials. We calculated the pooled weighted mean differences (WMDs) and 95% confidence intervals (CIs) between individuals with PD and controls using the random-effects model. Results. Twenty case-control studies which met our inclusion criteria were included in the final meta-analysis. We found that the P100 latency in PD was significantly higher compared with healthy controls (pooled WMD = 6.04, 95% CI: 2.73 to 9.35, P=0.0003, n=20). However, the difference in the mean amplitude of P100 was not significant between the two groups (pooled WMD = 0.64, 95% CI: −0.06 to 1.33, P=0.07) based on 10 studies with the P100 amplitude values available. Conclusions. The higher P100 latency of VEP was observed in PD patients, relative to healthy controls. Our findings suggest that electrophysiological changes and functional defect in the visual pathway of PD patients are important to our understanding of the pathophysiology of visual involvement in PD.

scholarly journals Parkinson’s disease: deep learning with a parameter-weighted structural connectome matrix for diagnosis and neural circuit disorder investigation

2021 ◽  
Author(s):  
Koichiro Yasaka ◽  
Koji Kamagata ◽  
Takashi Ogawa ◽  
Taku Hatano ◽  
Haruka Takeshige-Amano ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Learning ◽  
Basal Ganglia ◽  
Neural Circuit ◽  
Characteristic Curve ◽  
Diffusion Kurtosis Imaging ◽  
Healthy Controls ◽  
Structural Connectome ◽  
Learning Technique

Abstract Purpose To investigate whether Parkinson’s disease (PD) can be differentiated from healthy controls and to identify neural circuit disorders in PD by applying a deep learning technique to parameter-weighted and number of streamlines (NOS)–based structural connectome matrices calculated from diffusion-weighted MRI. Methods In this prospective study, 115 PD patients and 115 healthy controls were enrolled. NOS-based and parameter-weighted connectome matrices were calculated from MRI images obtained with a 3-T MRI unit. With 5-fold cross-validation, diagnostic performance of convolutional neural network (CNN) models using those connectome matrices in differentiating patients with PD from healthy controls was evaluated. To identify the important brain connections for diagnosing PD, gradient-weighted class activation mapping (Grad-CAM) was applied to the trained CNN models. Results CNN models based on some parameter-weighted structural matrices (diffusion kurtosis imaging (DKI)–weighted, neurite orientation dispersion and density imaging (NODDI)–weighted, and g-ratio-weighted connectome matrices) showed moderate performance (areas under the receiver operating characteristic curve (AUCs) = 0.895, 0.801, and 0.836, respectively) in discriminating PD patients from healthy controls. The DKI-weighted connectome matrix performed significantly better than the conventional NOS-based matrix (AUC = 0.761) (DeLong’s test, p < 0.0001). Alterations of neural connections between the basal ganglia and cerebellum were indicated by applying Grad-CAM to the NODDI- and g-ratio-weighted matrices. Conclusion Patients with PD can be differentiated from healthy controls by applying the deep learning technique to the parameter-weighted connectome matrices, and neural circuit disorders including those between the basal ganglia on one side and the cerebellum on the contralateral side were visualized.

scholarly journals Global efficiency of the motor network is decreased in Parkinson's disease in comparison with essential tremor and healthy controls

2021 ◽  
Author(s):  
Natalia Pelizari Novaes ◽  
Joana Bisol Balardin ◽  
Fabiana Campos Hirata ◽  
Luciano Melo ◽  
Edson Amaro ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Essential Tremor ◽  
Healthy Controls ◽  
Global Efficiency ◽  
Motor Network

Vestibular semicircular canal function as detected by video Head Impulse Test (vHIT) is essentially unchanged in people with Parkinson’s disease compared to healthy controls

2021 ◽  
pp. 1-9
Author(s):  
Kim E. Hawkins ◽  
Elodie Chiarovano ◽  
Serene S. Paul ◽  
Ann M Burgess ◽  
Hamish G. MacDougall ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Semicircular Canal ◽  
Neurodegenerative Disorder ◽  
Vestibular Function ◽  
Head Impulse Test ◽  
Healthy Controls ◽  
Video Head Impulse Test ◽  
Head Impulse ◽  
Vestibulo Ocular Reflex

BACKGROUND: Parkinson’s disease (PD) is a common multi-system neurodegenerative disorder with possible vestibular system dysfunction, but prior vestibular function test findings are equivocal. OBJECTIVE: To report and compare vestibulo-ocular reflex (VOR) gain as measured by the video head impulse test (vHIT) in participants with PD, including tremor dominant and postural instability/gait dysfunction phenotypes, with healthy controls (HC). METHODS: Forty participants with PD and 40 age- and gender-matched HC had their vestibular function assessed. Lateral and vertical semicircular canal VOR gains were measured with vHIT. VOR canal gains between PD participants and HC were compared with independent samples t-tests. Two distinct PD phenotypes were compared to HC using Tukey’s ANOVA. The relationship of VOR gain with PD duration, phenotype, severity and age were investigated using logistic regression. RESULTS: There were no significant differences between groups in vHIT VOR gain for lateral or vertical canals. There was no evidence of an effect of PD severity, phenotype or age on VOR gains in the PD group. CONCLUSION: The impulsive angular VOR pathways are not significantly affected by the pathophysiological changes associated with mild to moderate PD.

scholarly journals Oral Factors That Impact the Oral Microbiota in Parkinson’s Disease

2021 ◽  
Vol 9 (8) ◽  
pp. 1616
Author(s):  
Natalia S. Rozas ◽  
Gena D. Tribble ◽  
Cameron B. Jeter
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Oral Health ◽  
Soft Tissue ◽  
Oral Hygiene ◽  
Beta Diversity ◽  
Oral Microbiota ◽  
Healthy Controls ◽  
Microbiota Composition ◽  
Salivary Ph

Patients with Parkinson’s disease (PD) are at increased risk of aspiration pneumonia, their primary cause of death. Their oral microbiota differs from healthy controls, exacerbating this risk. Our goal was to explore if poor oral health, poor oral hygiene, and dysphagia status affect the oral microbiota composition of these patients. In this cross-sectional case-control study, the oral microbiota from hard and soft tissues of patients with PD (n = 30) and age-, gender-, and education-matched healthy controls (n = 30) was compared using 16S rRNA gene sequencing for bacterial identification. Study participants completed dietary, oral hygiene, drooling, and dysphagia questionnaires, and an oral health screening. Significant differences in soft tissue beta-diversity (p < 0.005) were found, and a higher abundance of opportunistic oral pathogens was detected in patients with PD. Factors that significantly influenced soft tissue beta-diversity and microbiota composition include dysphagia, drooling (both p < 0.05), and salivary pH (p < 0.005). Thus, patients with PD show significant differences in their oral microbiota compared to the controls, which may be due, in part, to dysphagia, drooling, and salivary pH. Understanding factors that alter their oral microbiota could lead to the development of diagnostic and treatment strategies that improve the quality of life and survivability of these patients.

Development of standardized regression-based formulas to assess meaningful cognitive change in early Parkinson’s disease

2020 ◽  
Author(s):  
Hannah L Combs ◽  
Kate A Wyman-Chick ◽  
Lauren O Erickson ◽  
Michele K York
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Test Scores ◽  
Prediction Models ◽  
Early Stage ◽  
Cognitive Change ◽  
Cognitive Test ◽  
Healthy Controls ◽  
Change Over Time ◽  
Over Time

Abstract Objective Longitudinal assessment of cognitive and emotional functioning in patients with Parkinson’s disease (PD) is helpful in tracking progression of the disease, developing treatment plans, evaluating outcomes, and educating patients and families. Determining whether change over time is meaningful in neurodegenerative conditions, such as PD, can be difficult as repeat assessment of neuropsychological functioning is impacted by factors outside of cognitive change. Regression-based prediction formulas are one method by which clinicians and researchers can determine whether an observed change is meaningful. The purpose of the current study was to develop and validate regression-based prediction models of cognitive and emotional test scores for participants with early-stage idiopathic PD and healthy controls (HC) enrolled in the Parkinson’s Progression Markers Initiative (PPMI). Methods Participants with de novo PD and HC were identified retrospectively from the PPMI archival database. Data from baseline testing and 12-month follow-up were utilized in this study. In total, 688 total participants were included in the present study (NPD = 508; NHC = 185). Subjects from both groups were randomly divided into development (70%) and validation (30%) subsets. Results Early-stage idiopathic PD patients and healthy controls were similar at baseline. Regression-based models were developed for all cognitive and self-report mood measures within both populations. Within the validation subset, the predicted and observed cognitive test scores did not significantly differ, except for semantic fluency. Conclusions The prediction models can serve as useful tools for researchers and clinicians to study clinically meaningful cognitive and mood change over time in PD.

scholarly journals Inner and outer retinal layer thickness alterations in pediatric and juvenile craniopharyngioma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ga-In Lee ◽  
Kyung-Ah Park ◽  
Sei Yeul Oh ◽  
Doo-Sik Kong ◽  
Sang Duk Hong
Keyword(s):  
Layer Thickness ◽  
Outer Nuclear Layer ◽  
Plexiform Layer ◽  
Visual Field Defects ◽  
Retinal Layer ◽  
Inner Plexiform Layer ◽  
Healthy Controls ◽  
Fiber Layer ◽  
Photoreceptor Layer ◽  
Chiasmal Compression

AbstractWe evaluated postoperative retinal thickness in pediatric and juvenile craniopharyngioma (CP) patients with chiasmal compression using optical coherence tomography (OCT) auto-segmentation. We included 18 eyes of 18 pediatric or juvenile patients with CP and 20 healthy controls. Each thickness of the macular retinal nerve fiber layer (RNFL), ganglion cell layer (GCL), inner plexiform layer (IPL), inner nuclear layer, outer plexiform layer, outer nuclear layer, and photoreceptor layer was compared between the CP patients and healthy controls. There was significant thinning in the macular RNFL (estimates [μm], superior, − 10.68; inferior, − 7.24; nasal, − 14.22), all quadrants of GCL (superior, − 16.53; inferior, − 14.37; nasal, − 24.34; temporal, − 9.91) and IPL (superior, − 11.45; inferior, − 9.76; nasal, − 15.25; temporal, − 4.97) in pediatric and juvenile CP patients postoperatively compared to healthy control eyes after adjusting for age and refractive errors. Thickness reduction in the average and nasal quadrant of RNFL, GCL, and IPL was associated with peripapillary RNFL thickness, and reduced nasal quadrant GCL and IPL thicknesses were associated with postoperative visual field defects. In pediatric and juvenile patients with CP, decreased inner retinal layer thickness following chiasmal compression was observed. The changes in retinal structures were closely related to peripapillary RNFL thinning and functional outcomes.

Sign in / Sign up

Export Citation Format

Share Document