The Pirouette Test to Evaluate Asymmetry in Parkinsonian Gait Freezing.
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ABSTRACT:
SUBMITTER: Reich MM
PROVIDER: S-EPMC6182996 | biostudies-literature | 2014 Jun
REPOSITORIES: biostudies-literature
Publications
The Pirouette Test to Evaluate Asymmetry in Parkinsonian Gait Freezing.
Reich Martin M MM Sawalhe Anna D AD Steigerwald Frank F Johannes Silvia S Matthies Cordula C Volkmann Jens J
Movement disorders clinical practice 20140515 2
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Project description:Freezing of gait is one of the most debilitating symptoms in Parkinson's disease as it causes falls and reduces mobility and quality of life. The pedunculopontine nucleus is one of the major nuclei of the mesencephalic locomotor region and has neurons related to anticipatory postural adjustments preceding step initiation as well as to the step itself, thus it may be critical for coupling posture and gait to avoid freezing. Because freezing of gait and postural impairments have been related to frontal lesions and frontal dysfunction such as executive function, we hypothesized that freezing is associated with disrupted connectivity between midbrain locomotor regions and medial frontal cortex. We used diffusion tensor imaging to quantify structural connectivity of the pedunculopontine nucleus in patients with Parkinson's disease with freezing of gait, without freezing, and healthy age-matched controls. We also included behavioural tasks to gauge severity of freezing of gait, quantify gait metrics, and assess executive cognitive functions to determine whether between-group differences in executive dysfunction were related to pedunculopontine nucleus structural network connectivity. Using seed regions from the pedunculopontine nucleus, we were able to delineate white matter connections between the spinal cord, cerebellum, pedunculopontine nucleus, subcortical and frontal/prefrontal cortical regions. The current study is the first to demonstrate differences in structural connectivity of the identified locomotor pathway in patients with freezing of gait. We report reduced connectivity of the pedunculopontine nucleus with the cerebellum, thalamus and multiple regions of the frontal cortex. Moreover, these structural differences were observed solely in the right hemisphere of patients with freezing of gait. Finally, we show that the more left hemisphere-lateralized the pedunculopontine nucleus tract volume, the poorer the performance on cognitive tasks requiring the initiation of appropriate actions and/or the inhibition of inappropriate actions, specifically within patients with freezing. These results support the notion that freezing of gait is strongly related to structural deficits in the right hemisphere's locomotor network involving prefrontal cortical areas involved in executive inhibition function.
| S-EPMC3722352 | biostudies-literature
Project description:Parkinson's disease is a neurodegenerative disease characterized by gait dysfunction in the advanced stages of the disease. The unilateral 6-hydroxydopamine toxin-induced model is the most studied animal model of Parkinson's disease, which reproduces gait dysfunction after >68% dopamine loss in the substantia nigra pars compacta. The extent to which the neural activity in hemi-parkinsonian rats correlates to gait dysfunction and dopaminergic cell loss is not clear. In this article, we report the effects of unilateral dopamine depletion on cerebellar vermis activity using micro-electrocorticography during walking and freezing on a runway. Gait and neural activity were measured in 6-hydroxydopamine- and sham-lesioned rats aged between 4 and 5 months at 14, 21 and 28 days after infusion of 6-hydroxydopamine or control vehicle into the medial forebrain bundle (n = 20). Gait deficits in 6-hydroxydopamine rats were different from sham rats at 14 days (P < 0.05). Gait deficits in 6-hydroxydopamine rats improved at 21 and 28 days except for run speed, which decreased at 28 days (P = 0.018). No differences in gait deficits were observed in sham-lesioned rats at any time points. Hemi-parkinsonian rats showed hyperactivity in the cerebellar vermis at 21 days (P < 0.05), but not at 14 and 28 days, and the activity was reduced during freezing epochs in Lobules VIa, VIb and VIc (P < 0.05). These results suggest that dopaminergic cell loss causes pathological cerebellar activity at 21 days post-lesion and suggest that compensatory mechanisms from the intact hemisphere contribute to normalized cerebellar activity at 28 days. The decrease in cerebellar oscillatory activity during freezing may be indicative of neurological changes during freezing of gait in patients with Parkinson's disease making this region a potential location for biomarker detection. Although the unilateral 6-hydroxydopamine model presents gait deficits that parallel clinical presentations of Parkinson's disease, further studies in animal models of bilateral dopamine loss are needed to understand the role of the cerebellar vermis in Parkinson's disease.
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Project description:BackgroundThe preferable position of Deep Brain Stimulation (DBS) electrodes is proposed to be located in the dorsolateral subthalamic nucleus (STN) to improve general motor performance. The optimal DBS electrode localization for the post-operative improvement of balance and gait is unknown.MethodsIn this single-center, retrospective analyses, 66 Parkinson's disease (PD) patients (24 female, age 63 ± 7 years) were assessed pre- and post-operatively (8.45 ± 4.2 months after surgery) by using MDS-UPDRS, freezing of gait (FoG) score, Giladi's gait and falls questionnaire and Berg balance scale. The clinical outcome was related to the DBS electrode coordinates in x, y, z plane as revealed by image-based reconstruction (SureTune™). Binomial generalized linear mixed models with fixed-effect variables electrode asymmetry, parkinsonian subtype, medication, age class and clinical DBS induced changes were analyzed.ResultsSubthalamic nucleus-deep brain stimulation improved all motor, balance and FoG scores in MED OFF condition, however there were heterogeneous results in MED ON condition. DBS electrode reconstructed coordinates impacted the responsiveness of axial symptoms. FoG and balance responders showed slightly more medially located STN electrode coordinates and less medio-lateral asymmetry of the electrode reconstructed coordinates across hemispheres compared to non-responders.ConclusionDeep brain stimulation electrode reconstructed coordinates, particularly electrode asymmetry on the medio-lateral axis affected the post-operative responsiveness of balance and FoG symptoms in PD patients.
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Project description:Freezing of gait (FOG) in Parkinson's disease (PD) rises in prevalence when the effect of medications decays. It is known that auditory rhythmic stimulation improves gait in patients without FOG (PD-FOG), but its putative effect on patients with FOG (PD+FOG) at the end of dose has not been evaluated yet. This work evaluates the effect of auditory rhythmic stimulation on PD+FOG at the end of dose. 10 PD+FOG and 9 PD-FOG patients both at the end of dose periods, and 10 healthy controls were asked to perform several walking tasks. Tasks were performed in the presence and absence of auditory sensory stimulation. All PD+FOG suffered FOG during the task. The presence of auditory rhythmic stimulation (10% above preferred walking cadence) led PD+FOG to significantly reduce FOG. Velocity and cadence were increased, and turn time reduced in all groups. We conclude that auditory stimulation at the frequency proposed may be useful to avoid freezing episodes in PD+FOG.
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Project description:BackgroundExercises with motor complexity induce neuroplasticity in individuals with Parkinson's disease (PD), but its effects on freezing of gait are unknown. The objective of this study was to verify if adapted resistance training with instability - exercises with motor complexity will be more effective than traditional motor rehabilitation - exercises without motor complexity in improving freezing-of-gait severity, outcomes linked to freezing of gait, and brain function.MethodsFreezers were randomized either to the adapted resistance training with instability group (n = 17) or to the active control group (traditional motor rehabilitation, n = 15). Both training groups performed exercises 3 times a week for 12 weeks. The primary outcome was the New Freezing of Gait Questionnaire. Secondary outcomes were freezing of gait ratio (turning task), cognitive inhibition (Stroop-III test), motor signs (Unified Parkinson's Disease Rating Scale part-III [UPDRS-III]), quality of life (PD Questionnaire 39), anticipatory postural adjustment (leg-lifting task) and brain activation during a functional magnetic resonance imaging protocol of simulated anticipatory postural adjustment task. Outcomes were evaluated before and after interventions.ResultsOnly adapted resistance training with instability improved all the outcomes (P < 0.05). Adapted resistance training with instability was more effective than traditional motor rehabilitation (in improving freezing-of-gait ratio, motor signs, quality of life, anticipatory postural adjustment amplitude, and brain activation; P < 0.05). Our results are clinically relevant because improvement in the New Freezing of Gait Questionnaire (-4.4 points) and UPDRS-III (-7.4 points) scores exceeded the minimally detectable change (traditional motor rehabilitation group data) and the moderate clinically important difference suggested for PD, respectively. The changes in mesencephalic locomotor region activation and in anticipatory postural adjustment amplitude explained the changes in New Freezing of Gait Questionnaire scores and in freezing-of-gait ratio following adapted resistance training with instability, respectively.ConclusionsAdapted resistance training with instability is able to cause significant clinical improvement and brain plasticity in freezers. © 2020 International Parkinson and Movement Disorder Society.
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Project description:Freezing of Gait (FOG) is a prevalent symptom in advanced Parkinson's Disease (PD), characterized by intermittent transitions between normal gait and freezing episodes. This study introduces a novel graph-theoretic approach to detect FOG from video data of PD patients. We construct a sequence of pose graphs that represent the spatial relations and temporal progression of a patient's posture over time. Each graph node corresponds to an estimated joint position, while the edges reflect the anatomical connections and their proximity. We propose a hypothesis testing procedure that deploys the Fréchet statistics to identify break points in time between regular gait and FOG episodes, where we model the central tendency and dispersion of the pose graphs in the presentation of graph Laplacian matrices by computing their Fréchet mean and variance. We implement binary segmentation and incremental computation in our algorithm for efficient calculation. The proposed framework is validated on two datasets, Kinect3D and AlphaPose, demonstrating its effectiveness in detecting FOG from video data. The proposed approach that extracts matrix features is distinct from the prevailing pixel-based deep learning methods. It provides a new perspective on feature extraction for FOG detection and potentially contributes to improved diagnosis and treatment of PD.
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Project description:Freezing of gait (FOG) is a poorly understood heterogeneous gait disorder seen in patients with parkinsonism which contributes to significant morbidity and social isolation. FOG is currently measured with scales that are typically performed by movement disorders specialists (i.e., MDS-UPDRS), or through patient completed questionnaires (N-FOG-Q) both of which are inadequate in addressing the heterogeneous nature of the disorder and are unsuitable for use in clinical trials The purpose of this study was to devise a method to measure FOG objectively, hence improving our ability to identify it and accurately evaluate new therapies. A major innovation of our study is that it is the first study of its kind that uses the largest sample size (>30 h, N = 57) in order to apply explainable, multi-task deep learning models for quantifying FOG over the course of the medication cycle and at varying levels of parkinsonism severity. We trained interpretable deep learning models with multi-task learning to simultaneously score FOG (cross-validated F1 score 97.6%), identify medication state (OFF vs. ON levodopa; cross-validated F1 score 96.8%), and measure total PD severity (MDS-UPDRS-III score prediction error ≤ 2.7 points) using kinematic data of a well-characterized sample of N = 57 patients during levodopa challenge tests. The proposed model was able to explain how kinematic movements are associated with each FOG severity level that were highly consistent with the features, in which movement disorders specialists are trained to identify as characteristics of freezing. Overall, we demonstrate that deep learning models' capability to capture complex movement patterns in kinematic data can automatically and objectively score FOG with high accuracy. These models have the potential to discover novel kinematic biomarkers for FOG that can be used for hypothesis generation and potentially as clinical trial outcome measures.
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Project description:Freezing of gait (FOG) is a poorly understood heterogeneous gait disorder seen in patients with parkinsonism which contributes to significant morbidity and social isolation. FOG is currently measured with scales that are typically performed by movement disorders specialists (ie. MDS-UPDRS), or through patient completed questionnaires (N-FOG-Q) both of which are inadequate in addressing the heterogeneous nature of the disorder and are unsuitable for use in clinical trials The purpose of this study was to devise a method to measure FOG objectively, hence improving our ability to identify it and accurately evaluate new therapies. We trained interpretable deep learning models with multi-task learning to simultaneously score FOG (cross-validated F1 score 97.6%), identify medication state (OFF vs. ON levodopa; cross-validated F1 score 96.8%), and measure total PD severity (MDS-UPDRS-III score prediction error ≤ 2.7 points) using kinematic data of a well-characterized sample of N=57 patients during levodopa challenge tests. The proposed model was able to identify kinematic features associated with each FOG severity level that were highly consistent with the features that movement disorders specialists are trained to identify as characteristic of freezing. In this work, we demonstrate that deep learning models' capability to capture complex movement patterns in kinematic data can automatically and objectively score FOG with high accuracy. These models have the potential to discover novel kinematic biomarkers for FOG that can be used for hypothesis generation and potentially as clinical trial outcome measures.
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Project description:Gait impairments in persons with multiple sclerosis (pwMS) leading to decreased ambulation and reduced walking endurance remain poorly understood. Our objective was to assess gait asymmetry (GA) and bilateral coordination of gait (BCG), among pwMS during the six-minute walk test (6MWT), and determine their association with disease severity. We recruited 92 pwMS (age: 46.6 ± 7.9; 83% females) with a range of clinical disability, who completed the 6MWT wearing gait analysis system. GA was assessed by comparing left and right swing times, and BCG was assessed by the phase coordination index (PCI). Several functional and subjective gait assessments were performed. Results show that gait is more asymmetric and less coordinated as the disease progresses (p < 0.0001). Participants with mild MS showed significantly better BCG as reflected by lower PCI values in comparison to the other two MS severity groups (severe: p = 0.001, moderate: p = 0.02). GA and PCI also deteriorated significantly each minute during the 6MWT (p < 0.0001). GA and PCI (i.e., BCG) show weaker associations with clinical MS status than associations observed between functional and subjective gait assessments and MS status. Similar to other neurological cohorts, GA and PCI may be important parameters to assess and target in interventions among pwMS.
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Project description:Though gait asymmetry is used as a metric of functional recovery in clinical rehabilitation, there is no consensus on an ideal method for its evaluation. Various methods have been proposed to analyze single bilateral signals but are limited in scope, as they can often use only positive signals or discrete values extracted from time-scale data as input. By defining five symmetry axioms, a framework for benchmarking existing methods was established and a new method was described here for the first time: the weighted universal symmetry index (wUSI), which overcomes limitations of other methods. Both existing methods and the wUSI were mathematically compared to each other and in respect to their ability to fulfill the proposed symmetry axioms. Eligible methods that fulfilled these axioms were then applied using both discrete and continuous approaches to ground reaction force (GRF) data collected from healthy gait, both with and without artificially induced asymmetry using a single instrumented elbow crutch. The wUSI with a continuous approach was the only symmetry method capable of identifying GRF asymmetry differences in different walking conditions in all three planes of motion. When used with a continuous approach, the wUSI method was able to detect asymmetries while avoiding artificial inflation, a common problem reported in other methods. In conclusion, the wUSI is proposed as a universal method to quantify three-dimensional GRF asymmetries, which may also be expanded to other biomechanical signals.
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