1
|
Matejicka P, Kajan S, Goga J, Straka I, Balaz M, Janovic S, Minar M, Valkovic P, Hajduk M, Kosutzka Z. Bradykinesia in dystonic hand tremor: kinematic analysis and clinical rating. Front Hum Neurosci 2024; 18:1395827. [PMID: 38938290 PMCID: PMC11208697 DOI: 10.3389/fnhum.2024.1395827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Accepted: 05/21/2024] [Indexed: 06/29/2024] Open
Abstract
Introduction Bradykinesia is an essential diagnostic criterion for Parkinson's disease (PD) but is frequently observed in many non-parkinsonian movement disorders, complicating differential diagnosis, particularly in disorders featuring tremors. The presence of bradykinetic features in the subset of dystonic tremors (DT), either "pure" dystonic tremors or tremors associated with dystonia, remains currently unexplored. The aim of the current study was to evaluate upper limb bradykinesia in DT patients, comparing them with healthy controls (HC) and patients with PD by observing repetitive finger tapping (FT). Methods The protocol consisted of two main parts. Initially, the kinematic recording of repetitive FT was performed using optical hand tracking system (Leap Motion Controller). The values of amplitude, amplitude decrement, frequency, frequency decrement, speed, acceleration and number of halts of FT were calculated. Subsequently, three independent movement disorder specialists from different movement disorders centres, blinded to the diagnosis, rated the presence of FT bradykinesia based on video recordings. Results Thirty-six subjects participated in the study (12 DT, 12 HC and 12 early-stage PD). Kinematic analysis revealed no significant difference in the selected parameters of FT bradykinesia between DT patients and HC. In comparisons between DT and PD patients, PD patients exhibited bigger amplitude decrement and slower FT performance. In the blinded clinical assessment, bradykinesia was rated, on average, as being present in 41.6% of DT patients, 27.7% of HC, and 91.7% of PD patients. While overall inter-rater agreement was moderate, weak agreement was noted within the DT group. Discussion Clinical ratings indicated signs of bradykinesia in almost half of DT patients. The objective kinematic analysis confirmed comparable parameters between DT and HC individuals, with more pronounced abnormalities in PD across various kinematic parameters. Interpretation of bradykinesia signs in tremor patients with DT should be approached cautiously and objective motion analysis might complement the diagnostic process and serve as a decision support system in the choice of clinical entities.
Collapse
Affiliation(s)
- Peter Matejicka
- 2nd Department of Neurology, Faculty of Medicine, Comenius University, Bratislava, Slovakia
| | - Slavomir Kajan
- Institute of Robotics and Cybernetics, Faculty of Electrical Engineering and Informatics, Slovak University of Technology in Bratislava, Bratislava, Slovakia
| | - Jozef Goga
- Institute of Robotics and Cybernetics, Faculty of Electrical Engineering and Informatics, Slovak University of Technology in Bratislava, Bratislava, Slovakia
| | - Igor Straka
- 2nd Department of Neurology, Faculty of Medicine, Comenius University, Bratislava, Slovakia
| | - Marek Balaz
- 1st Department of Neurology, St. Anne’s University Hospital, Masaryk University, Brno, Czechia
- Central European Institute of Technology (CEITEC), Brno, Czechia
| | - Simon Janovic
- 2nd Department of Neurology, Faculty of Medicine, Comenius University, Bratislava, Slovakia
| | - Michal Minar
- 2nd Department of Neurology, Faculty of Medicine, Comenius University, Bratislava, Slovakia
| | - Peter Valkovic
- 2nd Department of Neurology, Faculty of Medicine, Comenius University, Bratislava, Slovakia
- Institute of Normal and Pathological Physiology, Center of Experimental Medicine, Slovak Academy of Sciences (SAS), Bratislava, Slovakia
| | - Michal Hajduk
- Department of Psychology, Faculty of Arts, Comenius University, Bratislava, Slovakia
- Centre for Psychiatric Disorders Research, Science Park, Comenius University in Bratislava, Bratislava, Slovakia
- Department of Psychiatry, Faculty of Medicine, Comenius University, Bratislava, Slovakia
| | - Zuzana Kosutzka
- 2nd Department of Neurology, Faculty of Medicine, Comenius University, Bratislava, Slovakia
| |
Collapse
|
2
|
Normative vs. patient-specific brain connectivity in deep brain stimulation. Neuroimage 2020; 224:117307. [PMID: 32861787 DOI: 10.1016/j.neuroimage.2020.117307] [Citation(s) in RCA: 64] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2020] [Revised: 08/17/2020] [Accepted: 08/22/2020] [Indexed: 11/22/2022] Open
Abstract
Brain connectivity profiles seeding from deep brain stimulation (DBS) electrodes have emerged as informative tools to estimate outcome variability across DBS patients. Given the limitations of acquiring and processing patient-specific diffusion-weighted imaging data, a number of studies have employed normative atlases of the human connectome. To date, it remains unclear whether patient-specific connectivity information would strengthen the accuracy of such analyses. Here, we compared similarities and differences between patient-specific, disease-matched and normative structural connectivity data and their ability to predict clinical improvement. Data from 33 patients suffering from Parkinson's Disease who underwent surgery at three different centers were retrospectively collected. Stimulation-dependent connectivity profiles seeding from active contacts were estimated using three modalities, namely patient-specific diffusion-MRI data, age- and disease-matched or normative group connectome data (acquired in healthy young subjects). Based on these profiles, models of optimal connectivity were calculated and used to estimate clinical improvement in out of sample data. All three modalities resulted in highly similar optimal connectivity profiles that could largely reproduce findings from prior research based on this present novel multi-center cohort. In a data-driven approach that estimated optimal whole-brain connectivity profiles, out-of-sample predictions of clinical improvements were calculated. Using either patient-specific connectivity (R = 0.43 at p = 0.001), an age- and disease-matched group connectome (R = 0.25, p = 0.048) and a normative connectome based on healthy/young subjects (R = 0.31 at p = 0.028), significant predictions could be made. Our results of patient-specific connectivity and normative connectomes lead to similar main conclusions about which brain areas are associated with clinical improvement. Still, although results were not significantly different, they hint at the fact that patient-specific connectivity may bear the potential of explaining slightly more variance than group connectomes. Furthermore, use of normative connectomes involves datasets with high signal-to-noise acquired on specialized MRI hardware, while clinical datasets as the ones used here may not exactly match their quality. Our findings support the role of DBS electrode connectivity profiles as a promising method to investigate DBS effects and to potentially guide DBS programming.
Collapse
|
3
|
Sabo A, Mehdizadeh S, Ng KD, Iaboni A, Taati B. Assessment of Parkinsonian gait in older adults with dementia via human pose tracking in video data. J Neuroeng Rehabil 2020; 17:97. [PMID: 32664973 PMCID: PMC7362631 DOI: 10.1186/s12984-020-00728-9] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 07/06/2020] [Indexed: 01/01/2023] Open
Abstract
Background Parkinsonism is common in people with dementia, and is associated with neurodegenerative and vascular changes in the brain, or with exposure to antipsychotic or other dopamine antagonist medications. The detection of parkinsonian changes to gait may provide an opportunity to intervene and address reversible causes. In this study, we investigate the use of a vision-based system as an unobtrusive means to assess severity of parkinsonism in gait. Methods Videos of walking bouts of natural gait were collected in a specialized dementia unit using a Microsoft Kinect sensor and onboard color camera, and were processed to extract sixteen 3D and eight 2D gait features. Univariate regression to gait quality, as rated on the Unified Parkinson’s Disease Rating Scale (UPDRS) and Simpson-Angus Scale (SAS), was used to identify gait features significantly correlated to these clinical scores for inclusion in multivariate models. Multivariate ordinal logistic regression was subsequently performed and the relative contribution of each gait feature for regression to UPDRS-gait and SAS-gait scores was assessed. Results Four hundred one walking bouts from 14 older adults with dementia were included in the analysis. Multivariate ordinal logistic regression models incorporating selected 2D or 3D gait features attained similar accuracies: the UPDRS-gait regression models achieved accuracies of 61.4 and 62.1% for 2D and 3D features, respectively. Similarly, the SAS-gait models achieved accuracies of 47.4 and 48.5% with 2D or 3D gait features, respectively. Conclusions Gait features extracted from both 2D and 3D videos are correlated to UPDRS-gait and SAS-gait scores of parkinsonism severity in gait. Vision-based systems have the potential to be used as tools for longitudinal monitoring of parkinsonism in residential settings.
Collapse
Affiliation(s)
- Andrea Sabo
- KITE, Toronto Rehabilitation Institute, University Health Network, 550 University Avenue, Toronto, ON, M5G 2A2, Canada.,Institute of Biomaterials and Biomedical Engineering, University of Toronto, 164 College Street. Room 407, Toronto, ON, M2S 3G9, Canada
| | - Sina Mehdizadeh
- KITE, Toronto Rehabilitation Institute, University Health Network, 550 University Avenue, Toronto, ON, M5G 2A2, Canada
| | - Kimberley-Dale Ng
- KITE, Toronto Rehabilitation Institute, University Health Network, 550 University Avenue, Toronto, ON, M5G 2A2, Canada.,Institute of Biomaterials and Biomedical Engineering, University of Toronto, 164 College Street. Room 407, Toronto, ON, M2S 3G9, Canada
| | - Andrea Iaboni
- KITE, Toronto Rehabilitation Institute, University Health Network, 550 University Avenue, Toronto, ON, M5G 2A2, Canada.,Department of Psychiatry, University of Toronto, 250 College Street, 8th floor, Toronto, ON, M5T 1R8, Canada.,Centre for Mental Health, University Health Network, 33 Russell Street, Toronto, ON, M5S 2S1, Canada
| | - Babak Taati
- KITE, Toronto Rehabilitation Institute, University Health Network, 550 University Avenue, Toronto, ON, M5G 2A2, Canada. .,Institute of Biomaterials and Biomedical Engineering, University of Toronto, 164 College Street. Room 407, Toronto, ON, M2S 3G9, Canada. .,Department of Computer Science, University of Toronto, 10 King's College Road, Room 3302, Toronto, ON, M5S 3G4, Canada.
| |
Collapse
|
4
|
Changes in Phonation and Their Relations with Progress of Parkinson’s Disease. APPLIED SCIENCES-BASEL 2018. [DOI: 10.3390/app8122339] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Hypokinetic dysarthria, which is associated with Parkinson’s disease (PD), affects several speech dimensions, including phonation. Although the scientific community has dealt with a quantitative analysis of phonation in PD patients, a complex research revealing probable relations between phonatory features and progress of PD is missing. Therefore, the aim of this study is to explore these relations and model them mathematically to be able to estimate progress of PD during a two-year follow-up. We enrolled 51 PD patients who were assessed by three commonly used clinical scales. In addition, we quantified eight possible phonatory disorders in five vowels. To identify the relationship between baseline phonatory features and changes in clinical scores, we performed a partial correlation analysis. Finally, we trained XGBoost models to predict the changes in clinical scores during a two-year follow-up. For two years, the patients’ voices became more aperiodic with increased microperturbations of frequency and amplitude. Next, the XGBoost models were able to predict changes in clinical scores with an error in range 11–26%. Although we identified some significant correlations between changes in phonatory features and clinical scores, they are less interpretable. This study suggests that it is possible to predict the progress of PD based on the acoustic analysis of phonation. Moreover, it recommends utilizing the sustained vowel /i/ instead of /a/.
Collapse
|