Vision-Based Assessment of Parkinsonism and Levodopa-Induced Dyskinesia with Deep Learning Pose Estimation

Objective: To apply deep learning pose estimation algorithms for vision-based assessment of parkinsonism and levodopa-induced dyskinesia (LID). Methods: Nine participants with Parkinson's disease (PD) and LID completed a levodopa infusion protocol, where symptoms were assessed at regular intervals using the Unified Dyskinesia Rating Scale (UDysRS) and Unified Parkinson's Disease Rating Scale (UPDRS). A state-of-the-art deep learning pose estimation method was used to extract movement trajectories from videos of PD assessments. Features of the movement trajectories were used to detect and estimate the severity of parkinsonism and LID using random forest. Communication and drinking tasks were used to assess LID, while leg agility and toe tapping tasks were used to assess parkinsonism. Feature sets from tasks were also combined to predict total UDysRS and UPDRS Part III scores. Results: For LID, the communication task yielded the best results for dyskinesia (severity estimation: r = 0.661, detection: AUC = 0.930). For parkinsonism, leg agility had better results for severity estimation (r = 0.618), while toe tapping was better for detection (AUC = 0.773). UDysRS and UPDRS Part III scores were predicted with r = 0.741 and 0.530, respectively. Conclusion: This paper presents the first application of deep learning for vision-based assessment of parkinsonism and LID and demonstrates promising performance for the future translation of deep learning to PD clinical practices. Significance: The proposed system provides insight into the potential of computer vision and deep learning for clinical application in PD.Comment: 8 pages, 1 figure. Under revie

Solid Microneedles for Transdermal Delivery of Amantadine Hydrochloride and Pramipexole Dihydrochloride

The aim of this project was to study the influence of microneedles on transdermal delivery of amantadine hydrochloride and pramipexole dihydrochloride across porcine ear skin in vitro. Microchannel visualization studies were carried out and characterization of the microchannel depth was performed using confocal laser scanning microscopy (CLSM) to demonstrate microchannel formation following microneedle roller application. We also report, for the first time, the use of TA.XT Plus Texture Analyzer to characterize burst force in pig skin for transdermal drug delivery experiments. This is the force required to rupture pig skin. The mean passive flux of amantadine hydrochloride, determined using a developed LC–MS/MS technique, was 22.38 ± 4.73 μg/cm2/h, while the mean flux following the use of a stainless steel microneedle roller was 49.04 ± 19.77 μg/cm2/h. The mean passive flux of pramipexole dihydrochloride was 134.83 ± 13.66 μg/cm2/h, while the flux following the use of a stainless steel microneedle roller was 134.04 ± 0.98 μg/cm2/h. For both drugs, the difference in flux values following the use of solid stainless steel microneedle roller was not statistically significantly (p \u3e 0.05). Statistical analysis was carried out using the Mann–Whitney Rank sum test

Modulation of the 5-HT3 Receptor as a Novel Anti-Dyskinetic Target in Parkinson’s Disease

La L-3,4-dihydroxyphénylalanine (L-DOPA) est le traitement le plus efficace de la maladie de Parkinson. Cependant, avec une administration chronique de L-DOPA, les patients développent des complications motrices telles que les dyskinésies. Des études antérieures ont montré que le blocage des récepteurs type 3 de la sérotonine (5-HT3) réduit les niveaux de dopamine dans les ganglions de la base, suggérant qu'il pourrait atténuer la libération de dopamine qui caractérise l'état dyskinétique. Ici, nous avons étudié les effets de l’ondansétron, un antagoniste hautement sélectif du récepteur 5-HT3 à diminuer et à prévenir le développement des dyskinésies induites par L-DOPA chez le rat lésé a la 6-hydroxydopamine. Dans la première expérience, les rats sensibilisés avec L-DOPA pour induire des mouvements involontaires anormaux (AIMs), ont reçu L-DOPA en combinaison avec l'ondansétron ou un véhicule. Dans la seconde expérience, les doses efficaces d'ondansétron ont été administrées simultanément avec L-DOPA pendant 22 jours, et la sévérité des dyskinésies a été évaluée. Après 3 jours d’élimination, L-DOPA a été administré en aigu et la sévérité des dyskinésies évaluée. Nous avons trouvé que l'ondansétron 0,0001 mg/kg en combinaison avec L-DOPA, a significativement diminué la sévérité des dyskinésies par rapport à L-DOPA seul. Ondansétron 0,0001 mg/kg, administré en même temps que L-DOPA, a retardé le développement des dyskinésies. L'action anti-dyskinétique de l'ondansétron n'a pas compromis le bénéfice thérapeutique conféré par la L-DOPA. Ces résultats suggèrent que l'antagonisme des récepteurs 5-HT3 est une stratégie thérapeutique potentiellement nouvelle et efficace pour soulager la sévérité et prévenir le développement des dyskinésies.L-3,4-dihydroxyphenylalanine (L-DOPA) is the most effective treatment for Parkinson’s disease However, with chronic administration of L-DOPA, patients develop motor complications such as dyskinesia. Previous studies have shown that 5-HT3 receptor blockade reduces dopamine levels within the basal ganglia, suggesting that it could mitigate the aberrant dopamine release that characterises the dyskinetic state. Here, we investigated the effects of the highly-selective 5-HT3 antagonist ondansetron at diminishing the expression of established, and preventing the development of L-DOPA-induced dyskinesia in the 6-hydroxydopamine-lesioned rat. In the first set of experiments, rats were primed with L-DOPA to induce abnormal involuntary movements (AIMs), after which L-DOPA was administered, in combination with ondansetron or vehicle. The effect of ondansetron on L-DOPA anti-parkinsonian action was subsequently determined by the cylinder test. In the second set of experiments, rats were administered effective doses of ondansetron, started concurrently with L-DOPA for 22 days, during which dyskinesia severity was monitored. After a 3-day washout period, an acute challenge of L-DOPA was administered and AIMs severity was assessed. We found that acute challenges of ondansetron 0.0001 mg/kg in combination with L-DOPA, significantly diminished the severity of AIMs compared to L-DOPA alone. Ondansetron 0.0001 mg/kg, when started concurrently with L-DOPA, attenuated the priming process leading to the development of dyskinesia. The anti-dyskinetic action of ondansetron did not compromise the therapeutic benefit conferred by L-DOPA. These results suggest that 5-HT3 receptor antagonism is a potentially new and effective therapeutic strategy to alleviate the severity, and prevent the development of dyskinesia

Objective evaluation of Parkinson's disease bradykinesia

Bradykinesia is the fundamental motor feature of Parkinson’s disease - obligatory for diagnosis and central to monitoring. It is a complex clinicalsign that describes movements with slow speed, small amplitude, irregular rhythm, brief pauses and progressive decrements. Clinical ascertainment of the presence and severity of bradykinesia relies on subjective interpretation of these components, with considerable variability amongst clinicians, and this may contribute to diagnostic error and inaccurate monitoring in Parkinson’s disease. The primary aim of this thesis was to assess whether a novel non-invasive device could objectively measure bradykinesia and predict diagnostic classification of movement data from Parkinson’s disease patients and healthy controls. The second aim was to evaluate how objective measures of bradykinesia correlate with clinical measures of bradykinesia severity. The third aim was to investigate the characteristic kinematic features of bradykinesia. Forty-nine patients with Parkinson’s disease and 41 healthy controls were recruited in Leeds. They performed a repetitive finger-tapping task for 30 seconds whilst wearing small electromagnetic tracking sensors on their finger and thumb. Movement data was analysed using two different methods - statistical measures of the separable components of bradykinesia and a computer science technique called evolutionary algorithms. Validation data collected independently from 13 patients and nine healthy controls in San Francisco was used to assess whether the results generalised. The evolutionary algorithm technique was slightly superior at classifying the movement data into the correct diagnostic groups, especially for the mildest clinical grades of bradykinesia, and they generalised to the independent group data. The objective measures of finger tapping correlated well with clinical grades of bradykinesia severity. Detailed analysis of the data suggests that a defining feature of Parkinson’s disease bradykinesia called the sequence effect may be a physiological rather than a pathological phenomenon. The results inform the development of a device that may support clinical diagnosis and monitoring of Parkinson’s disease and also be used to investigate bradykinesia

Microelectrode cluster technology for precise interactions with neuronal circuits. Towards highly specific adaptive deep brain stimulation.

Neuro-electronic interfaces, which can be used for stable communication between neurons-computers over long periods of time, would be valuable for understanding and interacting with the nervous system. A major challenge has been to overcome the tissue reactions towards implanted electrodes. Flexible microelectrodes that cause less implantation injury and which can follow the micromotions of the brain have been considered as a solution to achieve stable neuronal recordings and stimulations. The aim of this thesis work was therefore to develop and evaluate biocompatible neuro-electronic interfaces, as well as introduce new implantation methods which together allow stable recordings and spatially precise stimulation of the brainTo this end, we have developed a new generation of ultrathin flexible electrode arrays based on 12.5 µm thin wires embedded in a gelatin vehicle providing structural support during implantation. The gelatin embedded electrodes were implanted in rat brains via a narrow track line and spread out as a cluster in the target area. In the first study, we evaluated the performance of the neural recordings for eight weeks with respect to impedance, signal amplitudes and noise levels. We found impedance, and signal to noise ratio of single units to be quite stable, suggesting high biocompatibility. In the second study, we developed a gelatin embedded microelectrode array consisting of 16 microelectrodes, distally equipped with silicone cushions to reduce vascular damage. This array was implanted medial to the subthalamic nucleus, in 6-hydroxydopamine lesioned rats (a classical animal model for Parkinson’s disease), and the effects of deep brain stimulation were evaluated for 6 weeks. Stimulation with subsets of 4-8 electrodes evoked specific motor behaviors in all the tested rats. Depending on the exact electrode combination, stimulation elicited either improvement of locomotion, or grooming and rearing, increased turning, dyskinesia, or no movement. These results suggest that improved stimulation specificity can be obtained by choosing the right group of electrodes from the cluster. In the third study, we hypothesized that reducing the tissue resistance during the insertion of the electrodes would minimize the implantation injury. To address this problem, we coated gelatin embedded needles with a layer of ice, which on melting, provided a super slippery surface during insertion into the brain. The addition of a layer of melting ice decreased the insertion force by approximately 50%, significantly reduced neuronal loss, as well as the astrocytic response, but did not have any obvious effect on microglial activation.In conclusion, this thesis presents a novel design for implantable and biocompatible neuro-electronic interfaces comprising highly flexible microelectrodes rendering stable recording properties and improved stimulation specificity. In addition, a novel implantation vehicle was developed to reduce the acute tissue reactions in response to the implantatio

Objective and automatic classification of Parkinson disease with Leap Motion controller

Background: The main objective of this paper is to develop and test the ability of the Leap Motion controller (LMC) to assess the motor dysfunction in patients with Parkinson disease (PwPD) based on the MDS-UPDRSIII exercises. Four exercises (thumb forefinger tapping, hand opening/closing, pronation/supination, postural tremor) were used to evaluate the characteristics described in MDS-UPDRSIII. Clinical ratings according to the MDS/UPDRS-section III items were used as target. For that purpose, 16 participants with PD and 12 healthy people were recruited in Ospedale Cisanello, Pisa, Italy. The participants performed standardized hand movements with camera-based marker. Time and frequency domain features related to velocity, angle, amplitude, and frequency were derived from the LMC data. Results: Different machine learning techniques were used to classify the PD and healthy subjects by comparing the subjective scale given by neurologists against the predicted diagnosis from the machine learning classifiers. Feature selection methods were used to choose the most significant features. Logistic regression (LR), naive Bayes (NB), and support vector machine (SVM) were trained with tenfold cross validation with selected features. The maximum obtained classification accuracy with LR was 70.37%; the average area under the ROC curve (AUC) was 0.831. The obtained classification accuracy with NB was 81.4%, with AUC of 0.811. The obtained classification accuracy with SVM was 74.07%, with AUC of 0.675. Conclusions: Results revealed that the system did not return clinically meaningful data for measuring postural tremor in PwPD. In addition, it showed limited potential to measure the forearm pronation/supination. In contrast, for finger tapping and hand opening/closing, the derived parameters showed statistical and clinical significance. Future studies should continue to validate the LMC as updated versions of the software are developed. The obtained results support the fact that most of the set of selected features contributed significantly to classify the PwPD and healthy subjects

BIOMECHANICAL MARKERS AS INDICATORS OF POSTURAL INSTABILITY PROGRESSION IN PARKINSON'S DISEASE

The long term objective of this research is to identify quantitative biomechanical parameters of postural instability in patients with Parkinson’s disease (PD) that can in turn be used to assess fall risk. Currently, clinical assessments in PD are not sufficiently sensitive to predict fall risk, making a history of falls to be the best predictor of a future fall. Identifying biomechanical measures to predict risk of falls in PD would provide a quantitative justification to implement fall-reducing therapies prior to a first fall and help prevent the associated debilitating fractures or even morbidity. While past biomechanical studies have shown the presence of balance deficits in PD patients, which often include a broad spectrum of disease stages, compared to healthy controls (HC), no studies have assessed whether such parameters can distinguish the onset of postural instability prior to clinical presentation, and if such parameters persist following clinical presentation of postural instability. Toward this end this study had three goals: • Determine if biomechanical assessment of a quasi-static task, postural sway, could provide preclinical indication of postural instability in PD. • Define a mathematical model (based on principal component analysis, PCA) with biomechanical and clinical measures as inputs to quantitatively score earlier postural instability presence and progression in PD. • Investigate if biomechanical assessment of a dynamic task, gait initiation, could provide preclinical indication of postural instability in PD. Specific Aim 1 determined that some biomechanical postural sway variables showed evidence of preclinical postural instability and increased with PD progression. This aim distinguished mild PD (Hoehn and Yahr stage (H&Y) 2, without postural deficits) compared to HC suggesting preclinical indication of postural instability, and confirmed these parameters persisted in moderate PD (H&Y 3, with postural deficits). Specifically, trajectory, variation, and peak measures of the center of pressure (COP) during postural sway showed significant differences (p < .05) in mild PD compared to healthy controls, and these differences persisted in moderate PD. Schwab and England clinical score best correlated with the COP biomechanical measures. These results suggest that postural sway COP measures may provide preclinical indication of balance deficits in PD and increase with clinical PD progression. Specific Aim 2 defined a PCA model based on biomechanical measures of postural sway and clinical measures in mild PD, moderate PD, and HC. PCA modeling based on a correlation matrix structure identified both biomechanical and clinical measures as the primary drivers of variation in the data set. Further, a PCA model based on these selected parameters was able to significantly differentiate (p < .05) all 3 groups, suggesting PCA scores may help with preclinical indication of postural instability (mild PD versus HC) and could be sensitive to clinical disease progression (mild PD versus moderate PD and moderate PD versus HC). AP sway path length and a velocity parameter were the 2 primary measures that explained the variability in the data set, suggesting further investigation of these parameters and mathematical models for scoring postural instability progression is warranted. Specific Aim 3 determined that a velocity measure from biomechanical assessment of gait initiation (peak COP velocity towards the swing foot during locomotion) showed evidence of preclinical postural instability in PD. Because balance is a complex task, having a better understanding of both quasi-static (postural sway) and dynamic (gait initiation) tasks can provide further insight about balance deficits resulting from PD. Several temporal and kinematic parameters changed with increasing disease progression, with significant difference in moderate PD versus HC, but missed significance in mild PD compared to HC. Total Unified Parkinson’s Disease Rating Scale (UPDRS) and Pull Test clinical scores best correlated with the biomechanical measures of the gait initiation response. These results suggest dynamic biomechanical assessment may provide additional information in quantifying preclinical postural instability and progression in PD. In summary, reducing fall risk in PD is a high priority effort to maintain quality of life by allowing continued independence and safe mobility. Since no effective screening method exists to measure fall risk, our team is developing a multi-factorial method to detect postural instability through clinical balance assessment, and in doing so, provide the justification for implementing fall reducing therapies before potentially debilitating falls begin