scholarly journals Detection of Parkinson’s Disease from 3T T1 Weighted MRI Scans Using 3D Convolutional Neural Network

Diagnostics ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 402
Author(s):  
Sabyasachi Chakraborty ◽  
Satyabrata Aich ◽  
Hee-Cheol Kim
Keyword(s):  
Neural Network ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Convolutional Neural Network ◽  
Dopaminergic Neurons ◽  
Aging Population ◽  
Substantia Nigra Pars Compacta ◽  
Progressive Loss ◽  
Mri Scans ◽  
Magnetic Resonance Imaging Mri

Parkinson’s Disease is a neurodegenerative disease that affects the aging population and is caused by a progressive loss of dopaminergic neurons in the substantia nigra pars compacta (SNc). With the onset of the disease, the patients suffer from mobility disorders such as tremors, bradykinesia, impairment of posture and balance, etc., and it progressively worsens in the due course of time. Additionally, as there is an exponential growth of the aging population in the world the number of people suffering from Parkinson’s Disease is increasing and it levies a huge economic burden on governments. However, until now no therapeutic method has been discovered for completely eradicating the disease from a person’s body after it’s onset. Therefore, the early detection of Parkinson’s Disease is of paramount importance to tackle the progressive loss of dopaminergic neurons in patients to serve them with a better life. In this study, 3T T1-weighted MRI scans were acquired from the Parkinson’s Progression Markers Initiative (PPMI) database of 406 subjects from baseline visit, where 203 were healthy and 203 were suffering from Parkinson’s Disease. Following data pre-processing, a 3D convolutional neural network (CNN) architecture was developed for learning the intricate patterns in the Magnetic Resonance Imaging (MRI) scans for the detection of Parkinson’s Disease. In the end, it was observed that the developed 3D CNN model performed superiorly by completely aligning with the hypothesis of the study and plotted an overall accuracy of 95.29%, average recall of 0.943, average precision of 0.927, average specificity of 0.9430, f1-score of 0.936, and Receiver Operating Characteristic—Area Under Curve (ROC-AUC) score of 0.98 for both the classes respectively.

scholarly journals 3D Textural, Morphological and Statistical Analysis of Voxel of Interests in 3T MRI Scans for the Detection of Parkinson’s Disease Using Artificial Neural Networks

Healthcare ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 34
Author(s):  
Sabyasachi Chakraborty ◽  
Satyabrata Aich ◽  
Hee-Cheol Kim
Keyword(s):  
Machine Learning ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Feature Extraction ◽  
Dopaminergic Neurons ◽  
Extraction Process ◽  
Machine Learning Algorithms ◽  
Subcortical Structures ◽  
Progressive Loss ◽  
Mri Scans

Parkinson’s disease is caused due to the progressive loss of dopaminergic neurons in the substantia nigra pars compacta (SNc). Presently, with the exponential growth of the aging population across the world the number of people being affected by the disease is also increasing and it imposes a huge economic burden on the governments. However, to date, no therapy or treatment has been found that can completely eradicate the disease. Therefore, early detection of Parkinson’s disease is very important so that the progressive loss of dopaminergic neurons can be controlled to provide the patients with a better life. In this study, 3T T1-MRI scans were collected from 906 subjects, out of which, 203 are control subjects, 66 are prodromal subjects and 637 are Parkinson’s disease patients. To analyze the MRI scans for the detection of neurodegeneration and Parkinson’s disease, eight subcortical structures were segmented from the acquired MRI scans using atlas based segmentation. Further, on the extracted eight subcortical structures, feature extraction was performed to extract textural, morphological and statistical features, respectively. After the feature extraction process, an exhaustive set of 107 features were generated for each MRI scan. Therefore, a two-level feature extraction process was implemented for finding the best possible feature set for the detection of Parkinson’s disease. The two-level feature extraction procedure leveraged correlation analysis and recursive feature elimination, which at the end provided us with 20 best performing features out of the extracted 107 features. Further, all the features were trained using machine learning algorithms and a comparative analysis was performed between four different machine learning algorithms based on the selected performance metrics. And at the end, it was observed that artificial neural network (multi-layer perceptron) performed the best by providing an overall accuracy of 95.3%, overall recall of 95.41%, overall precision of 97.28% and f1-score of 94%, respectively.

scholarly journals Co-Expression of Nogo-A in Dopaminergic Neurons of the Human Substantia Nigra Pars Compacta Is Reduced in Parkinson’s Disease

Cells ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 3368
Author(s):  
Gian-Carlo Eyer ◽  
Stefano Di Santo ◽  
Ekkehard Hewer ◽  
Lukas Andereggen ◽  
Stefanie Seiler ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Animal Model ◽  
Substantia Nigra ◽  
Dopaminergic Neurons ◽  
Substantia Nigra Pars Compacta ◽  
Collaborative Effort ◽  
Tissue Micro Array ◽  
Progressive Loss ◽  
Micro Array

Parkinson’s disease is mainly characterized by a progressive loss of dopaminergic neurons in the substantia nigra pars compacta. Together with the small number, the high vulnerability of the dopaminergic neurons is a major pathogenic culprit of Parkinson’s disease. Our previous findings of a higher survival of dopaminergic neurons in the substantia nigra co-expressing Nogo-A in an animal model of Parkinson’s disease suggested that Nogo-A may be associated with dopaminergic neurons resilience against Parkinson’s disease neurodegeneration. In the present study, we have addressed the expression of Nogo-A in the dopaminergic neurons in the substantia nigra in postmortem specimens of diseased and non-diseased subjects of different ages. For this purpose, in a collaborative effort we developed a tissue micro array (TMA) that allows for simultaneous staining of many samples in a single run. Interestingly, and in contrast to the observations gathered during normal aging and in the animal model of Parkinson’s disease, increasing age was significantly associated with a lower co-expression of Nogo-A in nigral dopaminergic neurons of patients with Parkinson’s disease. In sum, while Nogo-A expression in dopaminergic neurons is higher with increasing age, the opposite is the case in Parkinson’s disease. These observations suggest that Nogo-A might play a substantial role in the vulnerability of dopaminergic neurons in Parkinson’s disease.

scholarly journals Neuroinflammation in the pathophysiology of Parkinson’s disease and therapeutic evidence of anti-inflammatory drugs

2015 ◽  
Vol 73 (7) ◽  
pp. 616-623 ◽  
Author(s):  
Taysa Bervian Bassani ◽  
Maria A.B.F. Vital ◽  
Laryssa K. Rauh
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Dopaminergic Neurons ◽  
Inflammatory Process ◽  
Epidemiological Studies ◽  
Substantia Nigra Pars Compacta ◽  
Fine Motor ◽  
Progressive Degeneration ◽  
Inflammatory Drugs ◽  
Anti Inflammatory

Parkinson’s disease (PD) is the second most common neurodegenerative disease affecting approximately 1.6% of the population over 60 years old. The cardinal motor symptoms are the result of progressive degeneration of substantia nigra pars compacta dopaminergic neurons which are involved in the fine motor control. Currently, there is no cure for this pathology and the cause of the neurodegeneration remains unknown. Several studies suggest the involvement of neuroinflammation in the pathophysiology of PD as well as a protective effect of anti-inflammatory drugs both in animal models and epidemiological studies, although there are controversial reports. In this review, we address evidences of involvement of inflammatory process and possible therapeutic usefulness of anti-inflammatory drugs in PD.

scholarly journals p38-TFEB pathways promote microglia activation through inhibiting CMA-mediated NLRP3 degradation in Parkinson's disease

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Jialong Chen ◽  
Kanmin Mao ◽  
Honglin Yu ◽  
Yue Wen ◽  
Hua She ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Nlrp3 Inflammasome ◽  
Dopaminergic Neurons ◽  
Microglia Activation ◽  
Microglial Cells ◽  
Substantia Nigra Pars Compacta ◽  
Mice Model ◽  
Chaperone Mediated Autophagy

Abstract Background Parkinson’s disease (PD) is characterized by degeneration of dopaminergic neurons in the substantia nigra pars compacta (SNpc), accompanied by accumulation of α-synuclein, chronic neuroinflammation and autophagy dysfunction. Previous studies suggested that misfolded α-synuclein induces the inflammatory response and autophagy dysfunction in microglial cells. The NLRP3 inflammasome signaling pathway plays a crucial role in the neuroinflammatory process in the central nervous system. However, the relationship between autophagy deficiency and NLRP3 activation induced by α-synuclein accumulation is not well understood. Methods Through immunoblotting, immunocytochemistry, immunofluorescence, flow cytometry, ELISA and behavioral tests, we investigated the role of p38-TFEB-NLRP3 signaling pathways on neuroinflammation in the α-synuclein A53T PD models. Results Our results showed that increased protein levels of NLRP3, ASC, and caspase-1 in the α-synuclein A53T PD models. P38 is activated by overexpression of α-synuclein A53T mutant, which inhibited the master transcriptional activator of autophagy TFEB. And we found that NLRP3 was degraded by chaperone-mediated autophagy (CMA) in microglial cells. Furthermore, p38-TFEB pathways inhibited CMA-mediated NLRP3 degradation in Parkinson's disease. Inhibition of p38 had a protective effect on Parkinson's disease model via suppressing the activation of NLRP3 inflammasome pathway. Moreover, both p38 inhibitor SB203580 and NLRP3 inhibitor MCC950 not only prevented neurodegeneration in vivo, but also alleviated movement impairment in α-synuclein A53T-tg mice model of Parkinson’s disease. Conclusion Our research reveals p38-TFEB pathways promote microglia activation through inhibiting CMA-mediated NLRP3 degradation in Parkinson's disease, which could be a potential therapeutic strategy for PD. Graphical abstract p38-TFEB pathways promote microglia activation through inhibiting CMA-mediated NLRP3 degradation in Parkinson's disease. In this model, p38 activates NLRP3 inflammasome via inhibiting TFEB in microglia. TFEB signaling negatively regulates NLRP3 inflammasome through increasing LAMP2A expression, which binds to NLRP3 and promotes its degradation via chaperone-mediated autophagy (CMA). NLRP3-mediated microglial activation promotes the death of dopaminergic neurons.

scholarly journals Depopulation of α-synuclein aggregates is associated with rescue of dopamine neuron dysfunction and death in a new Parkinson’s disease model

2018 ◽  
Author(s):  
Michal Wegrzynowicz ◽  
Dana Bar-On ◽  
Laura Calo’ ◽  
Oleg Anichtchik ◽  
Mariangela Iovino ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cell Death ◽  
Dopaminergic Neurons ◽  
Dopamine Release ◽  
Striatal Dopamine ◽  
Substantia Nigra Pars Compacta ◽  
Motor Deficit ◽  
Promising Therapeutic Approach ◽  
Striatal Dopamine Release

SUMMARYParkinson’s Disease (PD) is characterized by the presence of α-synuclein aggregates known as Lewy bodies and Lewy neurites, whose formation is linked to disease development. The causal relation between α-synuclein aggregates and PD is not well understood. We generated a new transgenic mouse line (MI2) expressing human, aggregation-prone truncated 1-120 α-synuclein under the control of the tyrosine hydroxylase promoter. MI2 mice exhibit progressive aggregation of α-synuclein in dopaminergic neurons of the substantia nigra pars compacta and their striatal terminals. This is associated with a progressive reduction of striatal dopamine release, reduced striatal innervation and significant nigral dopaminergic nerve cell death starting from 6 and 12 months of age, respectively. Overt impairment in motor behavior was found in MI2 mice at 20 months of age, when 50% of dopaminergic neurons are lost. These changes were associated with an increase in the number and density of 20-500nm α-synuclein species as shown by dSTORM. Treatment with the oligomer modulator anle138b, from 9-12 months of age, restored striatal dopamine release and prevented dopaminergic cell death. These effects were associated with a reduction of the inner density of α-synuclein aggregates and an increase in dispersed small α-synuclein species as revealed by dSTORM. The MI2 mouse model recapitulates the progressive dopaminergic deficit observed in PD, showing that early synaptic dysfunction precedes dopaminergic axonal loss and neuronal death that become associated with a motor deficit upon reaching a certain threshold. Our data also provide new mechanistic insight for the effect of anle138b’s function in vivo supporting that targeting α-synuclein aggregation is a promising therapeutic approach for PD.

scholarly journals TFE3-Mediated Autophagy is Involved in Dopaminergic Neurodegeneration in Parkinson’s Disease

2021 ◽  
Vol 9 ◽  
Author(s):  
Xin He ◽  
Yue Xie ◽  
Qiongping Zheng ◽  
Zeyu Zhang ◽  
Shanshan Ma ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cell Death ◽  
Transcription Factor ◽  
Dopaminergic Neurons ◽  
Essential Role ◽  
Dopaminergic Neurodegeneration ◽  
Promising Strategy ◽  
Progressive Loss ◽  
Mptp Model

Impairment of autophagy has been strongly implicated in the progressive loss of nigral dopaminergic neurons in Parkinson’s disease (PD). Transcription factor E3 (TFE3), an MiTF/TFE family transcription factor, has been identified as a master regulator of the genes that are associated with lysosomal biogenesis and autophagy. However, whether TFE3 is involved in parkinsonian neurodegeneration remains to be determined. In this study, we found decreased TFE3 expression in the nuclei of the dopaminergic neurons of postmortem human PD brains. Next, we demonstrated that TFE3 knockdown led to autophagy dysfunction and neurodegeneration of dopaminergic neurons in mice, implying that reduction of nuclear TFE3 may contribute to autophagy dysfunction-mediated cell death in PD. Further, we showed that enhancement of autophagy by TFE3 overexpression dramatically reversed autophagy downregulation and dopaminergic neurons loss in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) model of PD. Taken together, these findings demonstrate that TFE3 plays an essential role in maintaining autophagy and the survival of dopaminergic neurons, suggesting TFE3 activation may serve as a promising strategy for PD therapy.

Parkinson's Disease

2019 ◽  
pp. 252-273 ◽  
Author(s):  
Vaibhav Walia ◽  
Ashish Gakkhar ◽  
Munish Garg
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Substantia Nigra ◽  
Dopaminergic Neurons ◽  
Older Patients ◽  
Neurodegenerative Disorder ◽  
Progressive Loss ◽  
The Brain

Parkinson's disease (PD) is a neurodegenerative disorder in which a progressive loss of the dopaminergic neurons occurs. The loss of the neurons is most prominent in the substantia nigra region of the brain. The prevalence of PD is much greater among the older patients suggesting the risk of PD increases with the increase of age. The exact cause of the neurodegeneration in PD is not known. In this chapter, the authors introduce PD, demonstrate its history, pathogenesis, neurobiology, sign and symptoms, diagnosis, and pharmacotherapy.

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