Postural Stabilization Differences in Idiopathic Parkinson's Disease and Progressive Supranuclear Palsy during Self-Triggered Fast Forward Weight Lifting

Differential diagnosis between Parkinson's disease and atypical parkinsonism based on gait and postural instability: Artificial intelligence using an enhanced weight voting ensemble model

BACKGROUND

Parkinsonian diseases and cerebellar ataxia among movement disorders, are representative diseases which present with distinct pathological gaits. We proposed a machine learning system that can differentiate Parkinson's disease (PD), cerebellar ataxia and progressive supranuclear palsy Richardson syndrome (PSP-RS) based on postural instability and gait analysis.

METHODS

We screened 1467 gait (GAITRite) and postural instability (Pedoscan) analyses performed in Samsung Medical Center from January 2019 to December 2020. PD, probable PSP-RS, and cerebellar ataxia (i.e., probable MSA-C, hereditary ataxia, and sporadic adult-onset ataxia) were included in the study. The gated recurrent units for GaitRite and the deep neural network for Pedoscan were applied. The enhanced weight voting ensemble (EWVE) method was applied to incorporate the two modalities.

RESULTS

We included 551 PD, 38 PSP-RS, 113 cerebellar ataxia and among them, 71 were MSA-C. Pedoscan-based and Gait-based model showed high sensitivity but low specificity in differentiating atypical parkinsonism from PD. The EWVE showed significantly improved specificity and reliable performance in differentiation between PD vs. ataxia patients (AUC 0.974 ± 0.036, sensitivity 0.829 ± 0.217, specificity 0.969 ± 0.038), PD vs. MSA-C (AUC 0.975 ± 0.020, sensitivity 0.823 ± 0.162, specificity 0.932 ± 0.030) and PD vs. PSP-RS (AUC 0.963 ± 0.028, sensitivity 0.555 ± 0.157, specificity 0.936 ± 0.031).

CONCLUSION

We proposed reliable Pedoscan-based, Gait-based and EWVE model in differentiating gait disorders by integrating information from gait and postural instability. This model can provide diagnosis guidelines to primary caregivers and assist in differential diagnosis of PD from atypical parkinsonism for neurologists.

Cortical and Cerebellar Oscillatory Responses to Postural Instability in Parkinson's Disease

Introduction: Posture and balance dysfunctions critically impair activities of daily living of patients with progressing Parkinson's disease (PD). However, the neural mechanisms underlying postural instability in PD are poorly understood, and specific therapies are lacking. Previous electrophysiological studies have shown distinct cortical oscillations with a significant contribution of the cerebellum during postural control tasks in healthy individuals.

Methods: We investigated cortical and mid-cerebellar oscillatory activity via electroencephalography (EEG) during a postural control task in 10 PD patients with postural instability (PDPI+), 11 PD patients without postural instability (PDPI–), and 15 age-matched healthy control participants. Relative spectral power was analyzed in the theta (4–7 Hz) and beta (13–30 Hz) frequency bands.

Results: Time-dependent postural measurements computed by accelerometer signals showed poor performance in PDPI+ participants. EEG results revealed that theta power was profoundly lower in mid-frontal and mid-cerebellar regions during the postural control task in PDPI+, compared to PDPI– and control participants. In addition, theta power was correlated with postural control performance in PD subjects. No significant changes in beta power were observed. Additionally, oscillatory changes during the postural control task differed from the resting state.

Conclusion: This study underlines the involvement of mid-frontal and mid-cerebellar regions in postural stability during a balance task and emphasizes the important role of theta oscillations therein for postural control in PD.

Analysis of the stance phase of the gait cycle in Parkinson's disease and its potency for Parkinson's disease discrimination

In this study, using vertical ground reaction force (VGRF) data and focusing on the stance phase of the gait cycle, the effect of Parkinson's disease (PD) on gait was investigated. The used dataset consisted of 93 PD and 72 healthy individuals. Multiple comparisons correction ANOVA test and student t-test were used for statistical analyses. Results showed that a longer stance duration with a larger VGRF peak value (p < 0.05) was observed for PD patients during the stance phase. In addition, the VGRF peak value was delayed and blunted in PD cases compared with healthy individuals. These results indicated more time and effort for PD patients for posture stabilization during the stance phase. The time delay for different locations of the foot sole to contact the ground during the stance phase indicated that PD patients might use a different strategy for maintaining their body stability compared with healthy individuals. Although the VGRF time-domain pattern during the stance phase in PD was similar to healthy conditions, its local characteristics like duration and peak value differed significantly. The classification analysis based on the VGRF time-domain extracted features during the stance phase obtained PD recognition with accuracy, sensitivity and specificity of 90.82%, 88.63% and 82.56%, respectively.

Laboratory based assessment of gait and balance impairment in patients with progressive supranuclear palsy

BACKGROUND

Gait and balance abnormalities are a significant source of morbidity and mortality in progressive supranuclear palsy (PSP). Gait impairment in PSP is primarily assessed clinically on exam or with the use of rating scales. Three dimensional video based gait and balance analysis performed in a laboratory setting is a highly accurate method of motion analysis (Wren et al., 2020), however limited data is available in patients with PSP.

RESEARCH QUESTION

In this study we assess the objective features of postural control, kinematics, kinetic and temporal-spatial gait metrics in PSP, using three-dimensional video motion analysis in a laboratory setting compared to normal controls.

METHODS

Three-dimensional motion was captured using a 10-camera motion capture system, 41 body markers and ground embedded force plates in 16 patients with PSP patients and compared to motorically normal controls.

RESULTS

Spatiotemporal, kinematic, and kinetic gait measures effectively differentiated patients with PSP from controls. Patients had slower gait velocity, lower cadence, increased double support time and abnormal antero-posterior sway. Joint kinematics and kinetics were reduced and showed less variation among patients with PSP compared to controls which is suggestive of bradykinesia. Objective gait measures of abnormality correlated with clinical disease severity. Postural sway metrics distinguished PSP from controls and captured gait imbalance.

SIGNIFICANCE

Objective measures of gait and balance abnormalities in patients with PSP provide an outcome measure that can be potentially used for early disease detection, in clinical trials and to validate portable motion capture devices in the future.

Neuroimaging correlates of gait abnormalities in progressive supranuclear palsy

Progressive supranuclear palsy is a neurodegenerative disorder characterized primarily by tau inclusions and neurodegeneration in the midbrain, basal ganglia, thalamus, premotor and frontal cortex. Neurodegenerative change in progressive supranuclear palsy has been assessed using MRI. Degeneration of white matter tracts is evident with diffusion tensor imaging and PET methods have been used to assess brain metabolism or presence of tau protein deposits. Patients with progressive supranuclear palsy present with a variety of clinical syndromes; however early onset of gait impairments and postural instability are common features. In this study we assessed the relationship between multimodal imaging biomarkers (i.e., MRI atrophy, white matter tracts degeneration, flortaucipir-PET uptake) and laboratory-based measures of gait and balance abnormalities in a cohort of nineteen patients with progressive supranuclear palsy, using univariate and multivariate statistical analyses. The PSP rating scale and its gait midline sub-score were strongly correlated to gait abnormalities but not to postural imbalance. Principal component analysis on gait variables identified velocity, stride length, gait stability ratio, length of gait phases and dynamic stability as the main contributors to the first component, which was associated with diffusion tensor imaging measures in the posterior thalamic radiation, external capsule, superior cerebellar peduncle, superior fronto-occipital fasciculus, body and splenium of the corpus callosum and sagittal stratum, with MRI volumes in frontal and precentral regions and with flortaucipir-PET uptake in the precentral gyrus. The main contributor to the second principal component was cadence, which was higher in patients presenting more abnormalities on mean diffusivity: this unexpected finding might be related to compensatory gait strategies adopted in progressive supranuclear palsy. Postural imbalance was the main contributor to the third principal component, which was related to flortaucipir-PET uptake in the left paracentral lobule and supplementary motor area and white matter disruption in the superior cerebellar peduncle, putamen, pontine crossing tract and corticospinal tract. A partial least square model identified flortaucipir-PET uptake in midbrain, basal ganglia and thalamus as the main correlate of speed and dynamic component of gait in progressive supranuclear palsy. Although causality cannot be established in this analysis, our study sheds light on neurodegeneration of brain regions and white matter tracts that underlies gait and balance impairment in progressive supranuclear palsy.