Motor Onset Topography and Progression in Parkinson's Disease: the Upper Limb Is First

Deep learning-based detection of affected body parts in Parkinson's disease and freezing of gait using time-series imaging

We proposed a deep learning method using a convolutional neural network on time-series (TS) images to detect and differentiate affected body parts in people with Parkinson's disease (PD) and freezing of gait (FOG) during 360° turning tasks. The 360° turning task was performed by 90 participants (60 people with PD [30 freezers and 30 nonfreezers] and 30 age-matched older adults (controls) at their preferred speed. The position and acceleration underwent preprocessing. The analysis was expanded from temporal to visual data using TS imaging methods. According to the PD vs. controls classification, the right lower third of the lateral shank (RTIB) on the least affected side (LAS) and the right calcaneus (RHEE) on the LAS were the most relevant body segments in the position and acceleration TS images. The RHEE marker exhibited the highest accuracy in the acceleration TS images. The identified markers for the classification of freezers vs. nonfreezers vs. controls were the left lateral humeral epicondyle (LELB) on the more affected side and the left posterior superior iliac spine (LPSI). The LPSI marker in the acceleration TS images displayed the highest accuracy. This approach could be a useful supplementary tool for determining PD severity and FOG.

What the trained eye cannot see: Quantitative kinematics and machine learning detect movement deficits in early-stage Parkinson's disease from videos

BACKGROUND

Evaluation of disease severity in Parkinson's disease (PD) relies on motor symptoms quantification. However, during early-stage PD, these symptoms are subtle and difficult to quantify by experts, which might result in delayed diagnosis and suboptimal disease management.

OBJECTIVE

To evaluate the use of videos and machine learning (ML) for automatic quantification of motor symptoms in early-stage PD.

METHODS

We analyzed videos of three movement tasks-Finger Tapping, Hand Movement, and Leg Agility- from 26 aged-matched healthy controls and 31 early-stage PD patients. Utilizing ML algorithms for pose estimation we extracted kinematic features from these videos and trained three classification models based on left and right-side movements, and right/left symmetry. The models were trained to differentiate healthy controls from early-stage PD from videos.

RESULTS

Combining left side, right side, and symmetry features resulted in a PD detection accuracy of 79 % from Finger Tap videos, 75 % from Hand Movement videos, 79 % from Leg Agility videos, and 86 % when combining the three tasks using a soft voting approach. In contrast, the classification accuracy varied between 40 % and 72 % when the movement side or symmetry were not considered.

CONCLUSIONS

Our methodology effectively differentiated between early-stage PD and healthy controls using videos of standardized motor tasks by integrating kinematic analyses of left-side, right-side, and bilateral symmetry movements. These results demonstrate that ML can detect movement deficits in early-stage PD from videos. This technology is easy-to-use, highly scalable, and has the potential to improve the management and quantification of motor symptoms in early-stage PD.

Calbindin and Girk2/Aldh1a1 define resilient vs vulnerable dopaminergic neurons in a primate Parkinson's disease model

The differential vulnerability of dopaminergic neurons of the substantia nigra pars compacta (SNc) is a critical and unresolved question in Parkinson´s disease. Studies in mice show diverse susceptibility of subpopulations of nigral dopaminergic neurons to various toxic agents. In the primate midbrain, the molecular phenotypes of dopaminergic neurons and their differential vulnerability are poorly characterized. We performed a detailed histological study to determine the anatomical distribution of different molecular phenotypes within identified midbrain neurons and their selective vulnerability in control and MPTP-treated monkeys. In the ventral tier of the SNc (nigrosome), neurons rich in Aldh1a1 and Girk2 are intermingled, whereas calbindin is the marker that best identifies the most resilient neurons located in the dorsal tier and ventral tegmental area, recapitulating the well-defined dorsoventral axis of susceptibility to degeneration of dopaminergic neurons. In particular, a loss of Aldh1a1+ neurons in the ventral SNc was observed in parallel to the progressive development of parkinsonism. Aldh1a1+ neurons were the main population of vulnerable dopaminergic nigrostriatal-projecting neurons, while Aldh1a1- neurons giving rise to nigropallidal projections remained relatively preserved. Moreover, bundles of entwined Aldh1a1+ dendrites with long trajectories extending towards the substantia nigra pars reticulata emerged from clusters of Aldh1a1+ neurons and colocalized with dense cannabinoid receptor 1 afferent fibers likely representing part of the striatonigral projection that is affected in human disorders, including Parkinson´s disease. In conclusion, vulnerable nigrostriatal-projecting neurons can be identified by using Aldh1a1 and Girk2. Further studies are needed to define the afferent/efferent projection patterns of these most vulnerable neurons.

The lateralized effects of Parkinson's Disease on motor imagery: Evidence from mental chronometry

Alterations to the content of action representations may contribute to the movement challenges that characterize Parkinson's Disease (PD). One way to investigate action representations is through motor imagery. As PD motor symptoms typically have a unilateral onset, disease-related deficits related to action representations may follow a similarly lateralized pattern. The present study examined if temporal accuracy of motor imagery in individuals with PD differed according to the side of the body involved in the task. Thirty-eight participants with PD completed a mental chronometry task using their more affected and less affected side. Participants had significantly shorter mental versus physical movement times for the more affected. Higher imagery vividness in the kinaesthetic domain predicted shorter mental versus physical movement times for the more affected side, as did lower imagery vividness in the visual domain and poorer cognitive function. These results indicate that people with PD imagine movements differently when the target actions their more affected versus less affected side. It is additionally possible that side-specific deficits in the accurate processing of kinaesthetic information lead to an increased reliance on visual processes and cognitive resources to successfully execute motor imagery involving the more affected side.

3D Kinematics Quantifies Gait Response to Levodopa earlier and to a more Comprehensive Extent than the MDS-Unified Parkinson's Disease Rating Scale in Patients with Motor Complications

BACKGROUND

Quantitative 3D movement analysis using inertial measurement units (IMUs) allows for a more detailed characterization of motor patterns than clinical assessment alone. It is essential to discriminate between gait features that are responsive or unresponsive to current therapies to better understand the underlying pathophysiological basis and identify potential therapeutic strategies.

OBJECTIVES

This study aims to characterize the responsiveness and temporal evolution of different gait subcomponents in Parkinson's disease (PD) patients in their OFF and various ON states following levodopa administration, utilizing both wearable sensors and the gold-standard MDS-UPDRS motor part III.

METHODS

Seventeen PD patients were assessed while wearing a full-body set of 15 IMUs in their OFF state and at 20-minute intervals following the administration of a supra-threshold levodopa dose. Gait was reconstructed using a biomechanical model of the human body to quantify how each feature was modulated. Comparisons with non-PD control subjects were conducted in parallel.

RESULTS

Significant motor changes were observed in both the upper and lower limbs according to the MDS-UPDRS III, 40 minutes after levodopa intake. IMU-assisted 3D kinematics detected significant motor alterations as early as 20 minutes after levodopa administration, particularly in upper limbs metrics. Although all "pace-domain" gait features showed significant improvement in the Best-ON state, most rhythmicity, asymmetry, and variability features did not.

CONCLUSION

IMUs are capable of detecting motor alterations earlier and in a more comprehensive manner than the MDS-UPDRS III. The upper limbs respond more rapidly to levodopa, possibly reflecting distinct thresholds to levodopa across striatal regions.

The impact of subthalamic deep-brain stimulation in restoring motor symmetry in Parkinson's disease patients: a prospective study

BACKGROUND AND OBJECTIVES

The impact of subthalamic deep-brain stimulation (STN-DBS) on motor asymmetry and its influence on both motor and non-motor outcomes remain unclear. The present study aims at assessing the role of STN-DBS on motor asymmetry and how its modulation translates into benefits in motor function, activities of daily living (ADLs) and quality of life (QoL).

METHODS

Postoperative motor asymmetry has been assessed on the multicentric, prospective Predictive Factors and Subthalamic Stimulation in Parkinson's Disease cohort. Asymmetry was evaluated at both baseline (pre-DBS) and 1 year after STN-DBS. A patient was considered asymmetric when the right-to-left MDS-UPDRS part III difference was ≥ 5. In parallel, analyses have been carried out using the absolute right-to-left difference. The proportion of asymmetric patients at baseline was compared to that in the post-surgery evaluation across different medication/stimulation conditions.

RESULTS

537 PD patients have been included. The proportion of asymmetric patients was significantly reduced after both STN-DBS and medication administration (asymmetric patients: 50% in pre-DBS MedOFF, 35% in MedOFF/StimON, 26% in MedON/StimOFF, and 12% in MedON/StimON state). Older patients at surgery and with higher baseline UPDRS II scores were significantly less likely to benefit from STN-DBS at the level of motor asymmetry. No significant correlation between motor asymmetry and ADLs (UPDRS II) or overall QoL (PDQ-39) score was observed. Asymmetric patients had significantly higher mobility, communication, and daily living PDQ-39 sub-scores.

CONCLUSIONS

Both STN-DBS and levodopa lead to a reduction in motor asymmetry. Motor symmetry is associated with improvements in certain QoL sub-scores.

Dopamine neuron activity encodes the length of upcoming contralateral movement sequences

Dopaminergic neurons (DANs) in the substantia nigra pars compacta (SNc) have been related to movement speed, and loss of these neurons leads to bradykinesia in Parkinson's disease (PD). However, other aspects of movement vigor are also affected in PD; for example, movement sequences are typically shorter. However, the relationship between the activity of DANs and the length of movement sequences is unknown. We imaged activity of SNc DANs in mice trained in a freely moving operant task, which relies on individual forelimb sequences. We uncovered a similar proportion of SNc DANs increasing their activity before either ipsilateral or contralateral sequences. However, the magnitude of this activity was higher for contralateral actions and was related to contralateral but not ipsilateral sequence length. In contrast, the activity of reward-modulated DANs, largely distinct from those modulated by movement, was not lateralized. Finally, unilateral dopamine depletion impaired contralateral, but not ipsilateral, sequence length. These results indicate that movement-initiation DANs encode more than a general motivation signal and invigorate aspects of contralateral movements.

Interhemispheric imbalance and bradykinesia features in Parkinson's disease

In patients with Parkinson's disease, the connectivity between the two primary motor cortices may be altered. However, the correlation between asymmetries of abnormal interhemispheric connections and bradykinesia features has not been investigated. Furthermore, the potential effects of dopaminergic medications on this issue remain largely unclear. The aim of the present study is to investigate the interhemispheric connections in Parkinson's disease by transcranial magnetic stimulation and explore the potential relationship between interhemispheric inhibition and bradykinesia feature asymmetry in patients. Additionally, we examined the impact of dopaminergic therapy on neurophysiological and motor characteristics. Short- and long-latency interhemispheric inhibition was measured in 18 Parkinson's disease patients and 18 healthy controls, bilaterally. We also assessed the corticospinal and intracortical excitability of both primary motor cortices. We conducted an objective analysis of finger-tapping from both hands. Correlation analyses were performed to explore potential relationships among clinical, transcranial magnetic stimulation and kinematic data in patients. We found that short- and long-latency interhemispheric inhibition was reduced (less inhibition) from both hemispheres in patients than controls. Compared to controls, finger-tapping movements in patients were slower, more irregular, of smaller amplitudes and characterized by a progressive amplitude reduction during movement repetition (sequence effect). Among Parkinson's disease patients, the degree of short-latency interhemispheric inhibition imbalance towards the less affected primary motor cortex correlated with the global clinical motor scores, as well as with the sequence effect on the most affected hand. The greater the interhemispheric inhibition imbalance towards the less affected hemisphere (i.e. less inhibition from the less to the most affected primary motor cortex than that measured from the most to the less affected primary motor cortex), the more severe the bradykinesia in patients. In conclusion, the inhibitory connections between the two primary motor cortices in Parkinson's disease are reduced. The interhemispheric disinhibition of the primary motor cortex may have a role in the pathophysiology of specific bradykinesia features in patients, i.e. the sequence effect.

Dopaminergic denervation and associated MRI microstructural changes in the nigrostriatal projection in early Parkinson's disease patients

Loss of dopaminergic neurons in the substantia nigra pars compacta (SNc) and a profound reduction of striatal dopamine are two hallmarks of Parkinson's disease (PD). However, it's unclear whether degeneration starts at the neuronal soma or the striatal presynaptic terminals, and how microstructural degeneration is linked to dopaminergic loss is also uncertain. In this study, thirty de novo PD patients and twenty healthy subjects (HS) underwent 6-[18F]-fluoro-L-dopa (FDOPA) PET and MRI studies no later than 12 months from clinical diagnosis. FDOPA uptake rate (Ki), fractional volume of free-water (FW), and iron-sensitive R2* relaxometry were quantified within nigrostriatal regions. Inter-group differences (PD vs HS) were studied using non-parametric statistics and complemented with Cohen's d effect sizes and Bayesian statistics. Correlation analyses were performed exploring biomarker dependencies and their association with bradykinesia scores. PD patients exhibited a significant decline in nigrostriatal dopaminergic activity, being post-commissural putamen (-67%) and posterolateral SNc (-11.7%) the most affected subregions within striatum and SNc respectively. Microstructural alterations (FW) were restricted to the hemisphere corresponding to the most affected side and followed similar spatial gradients as FDOPA Ki (+20% in posterior putamen and +11% in posterolateral SNc). R2* revealed no relevant significant changes. FDOPA and FW were correlated within the posterolateral SNc, and clinical severity was associated with FDOPA Ki loss. The asymmetry between striatal and SNc changes for both dopaminergic depletion and microstructural degeneration biomarkers is consistent with a neurodegenerative process that begins in the striatal terminals before progressing toward the cell bodies in the SNc.

An Interpretable Deep Learning Optimized Wearable Daily Detection System for Parkinson's Disease

Walking detection in the daily life of patients with Parkinson's disease (PD) is of great significance for tracking the progress of the disease. This study aims to implement an accurate, objective, and passive detection algorithm optimized based on an interpretable deep learning architecture for the daily walking of patients with PD and to explore the most representative spatiotemporal motor features. Five inertial measurement units attached to the wrist, ankle, and waist are used to collect motion data from 100 subjects during a 10-meter walking test. The raw data of each sensor are subjected to the continuous wavelet transform to train the classification model of the constructed 6-channel convolutional neural network (CNN). The results show that the sensor located at the waist has the best classification performance with an accuracy of 98.01%±0.85% and the area under the receiver operating characteristic curve (AUC) of 0.9981±0.0017 under ten-fold cross-validation. The gradient-weighted class activation mapping shows that the feature points with greater contribution to PD were concentrated in the lower frequency band (0.5~3Hz) compared with healthy controls. The visual maps of the 3D CNN show that only three out of the six time series have a greater contribution, which is used as a basis to further optimize the model input, greatly reducing the raw data processing costs (50%) while ensuring its performance (AUC=0.9929±0.0019). To the best of our knowledge, this is the first study to consider the visual interpretation-based optimization of an intelligent classification model in the intelligent diagnosis of PD.

Longitudinal assessment of social cognition in de novo Parkinson's disease patients and its relationship with dopaminergic innervation

BACKGROUND

Social Cognition (SC) has been scarcely studied in Parkinson's disease (PD), and findings in early disease are controversial. SC encompasses different capacities such as facial emotion recognition (FER); Theory of Mind (ToM), the ability to understand other people's intentions (cognitive-ToM) and emotions (affective-ToM); and self-monitoring, the ability to regulate one's own behavior in social contexts. A relationship between dopaminergic deficit and SC in PD has been suggested.

OBJECTIVES

To prospectively assess, over a two-year period, SC in newly diagnosed drug-naïve, cognitively normal and non-depressed PD patients. Furthermore, we aimed to evaluate the relationship between SC and Fluorodopa (Positron Emission Tomography) Ki uptake, which is a marker of dopaminergic depletion.

METHODS

We compared SC performance between 25 de novo PD patients and 20 healthy controls (HC), and within-patients at baseline and two-year follow-up. The SC assessment included FER, ToM, as well as self-monitoring measures. The relationship between SC and dopaminergic innervation was also assessed in patients.

RESULTS

SC scores did not differ between PD and HC groups at baseline, nor between baseline and follow-up evaluation in PD. A significant positive correlation between self-monitoring and Fluorodopa Ki uptake in the left pallidum in PD patients was found at baseline. At follow-up, ToM (stories) positively correlated with Fluorodopa Ki uptake in the right thalamus and the left putamen.

CONCLUSION

SC appears to be preserved in de novo PD and remains stable in the short-term. Although more evidence is needed, our results support a relationship between dopamine innervation in subcortical regions and SC.

Depletion of dopamine in Parkinson's disease and relevant therapeutic options: A review of the literature

Parkinson's disease (PD) is a progressive neurodegenerative disorder that affects motor and cognition functions. The etiology of Parkinson's disease remains largely unknown, but genetic and environmental factors are believed to play a role. The neurotransmitter dopamine is implicated in regulating movement, motivation, memory, and other physiological processes. In individuals with Parkinson's disease, the loss of dopaminergic neurons leads to a reduction in dopamine levels, which causes motor impairment and may also contribute to the cognitive deficits observed in some patients. Therefore, it is important to understand the pathophysiology that leads to the loss of dopaminergic neurons, along with reliable biomarkers that may help distinguish PD from other conditions, monitor its progression, or indicate a positive response to a therapeutic intervention. Important advances in the treatment, etiology, and pathogenesis of Parkinson's disease have been made in the past 50 years. Therefore, this review tries to explain the different possible mechanisms behind the depletion of dopamine in PD patients such as alpha-synuclein abnormalities, mitochondrial dysfunction, and 3,4-dihydroxyphenylacetaldehyde (DOPAL) toxicity, along with the current therapies we have and the ones that are in development. The clinical aspect of Parkinson's disease such as the manifestation of both motor and non-motor symptoms, and the differential diagnosis with similar neurodegenerative disease are also discussed.

Altered functional connectivity of the primary motor cortex in tremor dominant and postural instability gait difficulty subtypes of early drug-naive Parkinson's disease patients

Background

The primary motor cortex (M1) is an important hub in the motor circuitry of Parkinson's disease (PD), but the subregions' function and their correlation to tremor dominant (TD) and postural instability and gait disturbance (PIGD) with PD remain unclear. This study aimed to determine whether the functional connectivity (FC) of the M1 subregions varied between the PD and PIGD subtypes.

Methods

We recruited 28 TD patients, 49 PIGD patients, and 42 healthy controls (HCs). M1 was divided into 12 regions of interest using the Human Brainnetome Atlas template to compare FC among these groups.

Results

Compared with HCs, TD and PIGD patients exhibited increased FC between the left upper limb region (A4UL_L) and the right caudate nucleus (CAU)/left putamen (PUT), between the right A4UL (A4UL_R) and the left anterior cingulate and paracingulate gyri (ACG)/bilateral cerebellum4_5 (CRBL4_5)/left PUT/right CAU/left supramarginal gyrus/left middle frontal gyrus (MFG), as well as decreased connectivity between the A4UL_L and the left postcentral gyrus and the bilateral cuneus, and between the A4UL_R and the right inferior occipital gyrus. TD patients showed increased FC between the right caudal dorsolateral area 6 (A6CDL_R) and the left ACG/right MFG, between the A4UL_L and the right CRBL6/right middle frontal gyrus, orbital part/bilateral inferior frontal gyrus, and orbital part (ORBinf), and between the A4UL_R and the left ORBinf/right MFG/right insula (INS). PIGD patients displayed increased connectivity between the A4UL_L and the left CRBL4_5. Compared with PIGD patients, TD patients exhibited increased connectivity between the A6CDL_R and the left ACG/right MFG and between the A4UL_R and the left ACG/left ORBinf/right INS/right MFG. Furthermore, in TD and PIGD groups, the FC strength between the A6CDL_R and right MFG was negatively correlated with PIGD scores, while the FC strength between the A4UL_R and left ORBinf/right INS was positively correlated with TD scores and tremor scores.

Conclusion

Our results demonstrated that early TD and PIGD patients share some common injury and compensatory mechanisms. TD patients occupied more resources in the MFG, ORBinf, INS, and ACG, which can be used as biomarkers to distinguish them from PIGD patients.

Rate control deficits during pinch grip and ankle dorsiflexion in early-stage Parkinson's disease

BACKGROUND

Much of our understanding of the deficits in force control in Parkinson's disease (PD) relies on findings in the upper extremity. Currently, there is a paucity of data pertaining to the effect of PD on lower limb force control.

OBJECTIVE

The purpose of this study was to concurrently evaluate upper- and lower-limb force control in early-stage PD and a group of age- and gender-matched healthy controls.

METHODS

Twenty individuals with PD and twenty-one healthy older adults participated in this study. Participants performed two visually guided, submaximal (15% of maximum voluntary contractions) isometric force tasks: a pinch grip task and an ankle dorsiflexion task. PD were tested on their more affected side and after overnight withdrawal from antiparkinsonian medication. The tested side in controls was randomized. Differences in force control capacity were assessed by manipulating speed-based and variability-based task parameters.

RESULTS

Compared with controls, PD demonstrated slower rates of force development and force relaxation during the foot task, and a slower rate of relaxation during the hand task. Force variability was similar across groups but greater in the foot than in the hand in both PD and controls. Lower limb rate control deficits were greater in PD with more severe symptoms based on the Hoehn and Yahr stage.

CONCLUSIONS

Together, these results provide quantitative evidence of an impaired capacity in PD to produce submaximal and rapid force across multiple effectors. Moreover, results suggest that force control deficits in the lower limb may become more severe with disease progression.

Striatal Blood-Brain Barrier Opening in Parkinson's Disease Dementia: A Pilot Exploratory Study

BACKGROUND

Parkinson's disease (PD) exhibits a high prevalence of dementia as disease severity and duration progress. Focused ultrasound (FUS) has been applied for transient blood-brain barrier (BBB) opening of cortical regions in neurodegenerative disorders. The striatum is a primary target for delivery of putative therapeutic agents in PD.

OBJECTIVE

Here, we report a prospective, single-arm, nonrandomized, proof-of-concept, phase I clinical trial (NCT03608553 amended) in PD with dementia to test the safety and feasibility of striatal BBB opening in PD patients.

METHODS

Seven PD patients with cognitive impairment were treated for BBB opening in the posterior putamen. This was performed in two sessions separated by 2 to 4 weeks, where the second session included bilateral putamina opening in 3 patients. Primary outcome measures included safety and feasibility of focal striatal BBB opening. Changes in motor and cognitive functions, magnetic resonance imaging (MRI), ¹⁸ F-fluorodopa (FDOPA), and β-amyloid PET (positron emission tomography) images were determined.

RESULTS

The procedure was feasible and well tolerated, with no serious adverse events. No neurologically relevant change in motor and cognitive (battery of neuropsychological tests) functions was recognized at follow-up. MRI revealed putamen BBB closing shortly after treatment (24 hours to 14 days) and ruled out hemorrhagic and ischemic lesions. There was a discrete but significant reduction in β-amyloid uptake in the targeted region and no change in FDOPA PET.

CONCLUSIONS

These initial results indicate that FUS-mediated striatal BBB opening is feasible and safe and therefore could become an effective tool to facilitate the delivery of putative neurorestorative molecules in PD. © 2022 International Parkinson and Movement Disorder Society.

Machine Learning Classifiers to Evaluate Data From Gait Analysis With Depth Cameras in Patients With Parkinson's Disease

Introduction

The assessments of the motor symptoms in Parkinson's disease (PD) are usually limited to clinical rating scales (MDS UPDRS III), and it depends on the clinician's experience. This study aims to propose a machine learning technique algorithm using the variables from upper and lower limbs, to classify people with PD from healthy people, using data from a portable low-cost device (RGB-D camera). And can be used to support the diagnosis and follow-up of patients in developing countries and remote areas.

Methods

We used Kinect®eMotion system to capture the spatiotemporal gait data from 30 patients with PD and 30 healthy age-matched controls in three walking trials. First, a correlation matrix was made using the variables of upper and lower limbs. After this, we applied a backward feature selection model using R and Python to determine the most relevant variables. Three further analyses were done using variables selected from backward feature selection model (Dataset A), movement disorders specialist (Dataset B), and all the variables from the dataset (Dataset C). We ran seven machine learning models for each model. Dataset was divided 80% for algorithm training and 20% for evaluation. Finally, a causal inference model (CIM) using the DoWhy library was performed on Dataset B due to its accuracy and simplicity.

Results

The Random Forest model is the most accurate for all three variable Datasets (Dataset A: 81.8%; Dataset B: 83.6%; Dataset C: 84.5%) followed by the support vector machine. The CIM shows a relation between leg variables and the arms swing asymmetry (ASA) and a proportional relationship between ASA and the diagnosis of PD with a robust estimator (1,537).

Conclusions

Machine learning techniques based on objective measures using portable low-cost devices (Kinect®eMotion) are useful and accurate to classify patients with Parkinson's disease. This method can be used to evaluate patients remotely and help clinicians make decisions regarding follow-up and treatment.

Onset pattern of nigrostriatal denervation in early Parkinson's disease

The striatal dopaminergic deficit in Parkinson's disease exhibits a typical pattern, extending from the caudal and dorsal putamen at onset to its more rostral region as the disease progresses. Clinically, upper-limb onset of cardinal motor features is the rule. Thus, according to current understanding of striatal somatotopy (i.e. the lower limb is dorsal to the upper limb) the assumed pattern of early dorsal striatal dopaminergic denervation in Parkinson's disease does not fit with an upper-limb onset. We have examined the topography of putaminal denervation in a cohort of 23 recently diagnosed de novo Parkinson's disease patients and 19 age-/gender-matched healthy subjects assessed clinically and by 18F-DOPA PET; 15 patients were re-assessed after 2 years. There was a net upper-limb predominance of motor features at onset. Caudal denervation of the putamen was confirmed in both the more- and less-affected hemispheres and corresponding hemibodies. Spatial covariance analysis of the most affected hemisphere revealed a pattern of 18F-DOPA uptake rate deficit that suggested focal dopamine loss starting in the posterolateral and intermediate putamen. Functional MRI group-activation maps during a self-paced motor task were used to represent the somatotopy of the putamen and were then used to characterize the decline in 18F-DOPA uptake rate in the upper- and lower-limb territories. This showed a predominant decrement in both hemispheres, which correlated significantly with severity of bradykinesia. A more detailed spatial analysis revealed a dorsoventral linear gradient of 18F-DOPA uptake rate in Parkinson's disease patients, with the highest putamen denervation in the caudal intermediate subregion (dorsoventral plane) compared to healthy subjects. The latter area coincides with the functional representation of the upper limb. Clinical motor assessment at 2-year follow-up showed modest worsening of parkinsonism in the primarily affected side and more noticeable increases in the upper limb in the less-affected side. Concomitantly, 18F-DOPA uptake rate in the less-affected putamen mimicked that recognized on the most-affected side. Our findings suggest that early dopaminergic denervation in Parkinson's disease follows a somatotopically related pattern, starting with the upper-limb representation in the putamen and progressing over a 2-year period in the less-affected hemisphere. These changes correlate well with the clinical presentation and evolution of motor features. Recognition of a precise somatotopic onset of nigrostriatal denervation may help to better understand the onset and progression of dopaminergic neurodegeneration in Parkinson's disease and eventually monitor the impact of putative therapies.

Motor and non-motor circuit disturbances in early Parkinson disease: which happens first?

For the last two decades, pathogenic concepts in Parkinson disease (PD) have revolved around the toxicity and spread of α-synuclein. Thus, α-synuclein would follow caudo-rostral propagation from the periphery to the central nervous system, first producing non-motor manifestations (such as constipation, sleep disorders and hyposmia), and subsequently impinging upon the mesencephalon to account for the cardinal motor features before reaching the neocortex as the disease evolves towards dementia. This model is the prevailing theory of the principal neurobiological mechanism of disease. Here, we scrutinize the temporal evolution of motor and non-motor manifestations in PD and suggest that, even though the postulated bottom-up mechanisms are likely to be involved, early involvement of the nigrostriatal system is a key and prominent pathophysiological mechanism. Upcoming studies of detailed clinical manifestations with newer neuroimaging techniques will allow us to more closely define, in vivo, the role of α-synuclein aggregates with respect to neuronal loss during the onset and progression of PD.

Remote Evaluation of Parkinson's Disease Using a Conventional Webcam and Artificial Intelligence

Objective: This study aimed to prove the concept of a new optical video-based system to measure Parkinson's disease (PD) remotely using an accessible standard webcam.

Methods: We consecutively enrolled a cohort of 42 patients with PD and healthy subjects (HSs). The participants were recorded performing MDS-UPDRS III bradykinesia upper limb tasks with a computer webcam. The video frames were processed using the artificial intelligence algorithms tracking the movements of the hands. The video extracted features were correlated with clinical rating using the Movement Disorder Society revision of the Unified Parkinson's Disease Rating Scale and inertial measurement units (IMUs). The developed classifiers were validated on an independent dataset.

Results: We found significant differences in the motor performance of the patients with PD and HSs in all the bradykinesia upper limb motor tasks. The best performing classifiers were unilateral finger tapping and hand movement speed. The model correlated both with the IMUs for quantitative assessment of motor function and the clinical scales, hence demonstrating concurrent validity with the existing methods.

Conclusions: We present here the proof-of-concept of a novel webcam-based technology to remotely detect the parkinsonian features using artificial intelligence. This method has preliminarily achieved a very high diagnostic accuracy and could be easily expanded to other disease manifestations to support PD management.

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

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.