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Angelini L, Paparella G, Bologna M. Distinguishing essential tremor from Parkinson's disease: clinical and experimental tools. Expert Rev Neurother 2024:1-16. [PMID: 39016323 DOI: 10.1080/14737175.2024.2372339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Accepted: 06/20/2024] [Indexed: 07/18/2024]
Abstract
INTRODUCTION Essential tremor (ET) and Parkinson's disease (PD) are the most common causes of tremor and the most prevalent movement disorders, with overlapping clinical features that can lead to diagnostic challenges, especially in the early stages. AREAS COVERED In the present paper, the authors review the clinical and experimental studies and emphasized the major aspects to differentiate between ET and PD, with particular attention to cardinal phenomenological features of these two conditions. Ancillary and experimental techniques, including neurophysiology, neuroimaging, fluid biomarker evaluation, and innovative methods, are also discussed for their role in differential diagnosis between ET and PD. Special attention is given to investigations and tools applicable in the early stages of the diseases, when the differential diagnosis between the two conditions is more challenging. Furthermore, the authors discuss knowledge gaps and unsolved issues in the field. EXPERT OPINION Distinguishing ET and PD is crucial for prognostic purposes and appropriate treatment. Additionally, accurate diagnosis is critical for optimizing clinical and experimental research on pathophysiology and innovative therapies. In a few years, integrated technologies could enable accurate, reliable diagnosis from early disease stages or prodromal stages in at-risk populations, but further research combining different techniques is needed.
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Affiliation(s)
| | - Giulia Paparella
- IRCCS Neuromed, Pozzilli, (IS), Italy
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | - Matteo Bologna
- IRCCS Neuromed, Pozzilli, (IS), Italy
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
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Okelberry T, Lyons KE, Pahwa R. Updates in essential tremor. Parkinsonism Relat Disord 2024; 122:106086. [PMID: 38538475 DOI: 10.1016/j.parkreldis.2024.106086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 03/02/2024] [Indexed: 05/05/2024]
Abstract
Essential tremor (ET) is one of the most common tremor disorders and can be disabling in its affect on daily activities. There have been major breakthroughs in the treatment of tremor and ET is the subject of important ongoing research. This review will present recent advancements in the epidemiology, genetics, pathophysiology, diagnosis, comorbidities, and imaging of ET. Current and future treatment options in the management of ET will also be reviewed. The need for continued innovation and scientific inquiry to address the unmet needs of persons of ET will be highlighted.
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Affiliation(s)
- Tyler Okelberry
- University of Kansas Medical Center, 3599 Rainbow Blvd, Kansas City, KS, 66160, USA.
| | - Kelly E Lyons
- University of Kansas Medical Center, 3599 Rainbow Blvd, Kansas City, KS, 66160, USA
| | - Rajesh Pahwa
- University of Kansas Medical Center, 3599 Rainbow Blvd, Kansas City, KS, 66160, USA
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Weiss V, Kokošová V, Valenta Z, Doležalová I, Baláž M, Mangia S, Michaeli S, Vojtíšek L, Nestrašil I, Herzig R, Filip P. Distance from main arteries influences microstructural and functional brain tissue characteristics. Neuroimage 2024; 285:120502. [PMID: 38103623 PMCID: PMC10804248 DOI: 10.1016/j.neuroimage.2023.120502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Revised: 12/11/2023] [Accepted: 12/13/2023] [Indexed: 12/19/2023] Open
Abstract
Given the substantial dependence of neurons on continuous supply of energy, the distribution of major cerebral arteries opens a question whether the distance from the main supply arteries constitutes a modulating factor for the microstructural and functional properties of brain tissue. To tackle this question, multimodal MRI acquisitions of 102 healthy volunteers over the full adult age span were utilised. Relaxation along a fictitious field in the rotating frame of rank n = 4 (RAFF4), adiabatic T1ρ, T2ρ, and intracellular volume fraction (fICVF) derived from diffusion-weighted imaging were implemented to quantify microstructural (cellularity, myelin density, iron concentration) tissue characteristics and degree centrality and fractional amplitude of low-frequency fluctuations to probe for functional metrics. Inverse correlation of arterial distance with robust homogeneity was detected for T1ρ, T2ρ and RAFF4 for cortical grey matter and white matter, showing substantial complex microstructural differences between brain tissue close and farther from main arterial trunks. Albeit with wider variability, functional metrics pointed to increased connectivity and neuronal activity in areas farther from main arteries. Surprisingly, multiple of these microstructural and functional distance-based gradients diminished with higher age, pointing to uniformization of brain tissue with ageing. All in all, this pilot study provides a novel insight on brain regionalisation based on artery distance, which merits further investigation to validate its biological underpinnings.
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Affiliation(s)
- Viktor Weiss
- First Department of Neurology, Faculty of Medicine, Masaryk University and University Hospital of St. Anne, Brno, Czech Republic; Department of Neurology, Charles University Faculty of Medicine, Hradec Králové, Czech Republic
| | - Viktória Kokošová
- First Department of Neurology, Faculty of Medicine, Masaryk University and University Hospital of St. Anne, Brno, Czech Republic; Department of Neurology, Faculty of Medicine, Masaryk University and University Hospital Brno, Brno, Czech Republic
| | - Zdeněk Valenta
- Department of Statistical Modelling, Institute of Computer Science of the Czech Academy of Sciences, Prague, Czech Republic
| | - Irena Doležalová
- First Department of Neurology, Faculty of Medicine, Masaryk University and University Hospital of St. Anne, Brno, Czech Republic
| | - Marek Baláž
- First Department of Neurology, Faculty of Medicine, Masaryk University and University Hospital of St. Anne, Brno, Czech Republic
| | - Silvia Mangia
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, United States of America
| | - Shalom Michaeli
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, United States of America
| | - Lubomír Vojtíšek
- Central European Institute of Technology (CEITEC) Masaryk University, Neuroscience Centre, Brno, Czech Republic
| | - Igor Nestrašil
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, United States of America
| | - Roman Herzig
- Department of Neurology, Charles University Faculty of Medicine, Hradec Králové, Czech Republic; Department of Neurology, Comprehensive Stroke Center, University Hospital Hradec Králové, Czech Republic
| | - Pavel Filip
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, United States of America; Department of Neurology, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic.
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Angelini L, Terranova R, Lazzeri G, van den Berg KRE, Dirkx MF, Paparella G. The role of laboratory investigations in the classification of tremors. Neurol Sci 2023; 44:4183-4192. [PMID: 37814130 PMCID: PMC10641063 DOI: 10.1007/s10072-023-07108-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 09/28/2023] [Indexed: 10/11/2023]
Abstract
INTRODUCTION Tremor is the most common movement disorder. Although clinical examination plays a significant role in evaluating patients with tremor, laboratory tests are useful to classify tremors according to the recent two-axis approach proposed by the International Parkinson and Movement Disorders Society. METHODS In the present review, we will discuss the usefulness and applicability of the various diagnostic methods in classifying and diagnosing tremors. We will evaluate a number of techniques, including laboratory and genetic tests, neurophysiology, and neuroimaging. The role of newly introduced innovative tremor assessment methods will also be discussed. RESULTS Neurophysiology plays a crucial role in tremor definition and classification, and it can be useful for the identification of specific tremor syndromes. Laboratory and genetic tests and neuroimaging may be of paramount importance in identifying specific etiologies. Highly promising innovative technologies are being developed for both clinical and research purposes. CONCLUSIONS Overall, laboratory investigations may support clinicians in the diagnostic process of tremor. Also, combining data from different techniques can help improve understanding of the pathophysiological bases underlying tremors and guide therapeutic management.
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Affiliation(s)
- Luca Angelini
- Department of Human Neurosciences, Sapienza University of Rome, Viale Dell'Università 30, 00185, Rome, Italy.
| | - Roberta Terranova
- Department of Medical, Surgical Sciences and Advanced Technologies "GF Ingrassia," University of Catania, Catania, Italy
| | - Giulia Lazzeri
- IRCCS Ca' Granda Ospedale Maggiore Policlinico, Neurology Unit, Milan, Italy
| | - Kevin R E van den Berg
- Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Neurology, Center of Expertise for Parkinson and Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Michiel F Dirkx
- Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Neurology, Center of Expertise for Parkinson and Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Giulia Paparella
- Department of Human Neurosciences, Sapienza University of Rome, Viale Dell'Università 30, 00185, Rome, Italy
- IRCCS Neuromed, Pozzilli (IS), Italy
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Wang X, Huang P, Haacke EM, Liu Y, Zhang Y, Jin Z, Li Y, Xu Q, Liu P, Chen S, He N, Yan F. Locus coeruleus and substantia nigra neuromelanin magnetic resonance imaging differentiates Parkinson's disease and essential tremor. Neuroimage Clin 2023; 38:103420. [PMID: 37141646 PMCID: PMC10176060 DOI: 10.1016/j.nicl.2023.103420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 04/04/2023] [Accepted: 04/23/2023] [Indexed: 05/06/2023]
Abstract
BACKGROUND Differential diagnosis of essential tremor (ET) and Parkinson's disease (PD) can still be a challenge in clinical practice. These two tremor disorders may have different pathogenesis related to the substantia nigra (SN) and locus coeruleus (LC). Characterizing neuromelanin (NM) in these structures may help improve the differential diagnosis. METHODS Forty-three subjects with tremor-dominant PD (PDTD), 31 subjects with ET, and 30 age- and sex-matched healthy controls were included. All subjects were scanned with NM magnetic resonance imaging (NM-MRI). NM volume and contrast measures for the SN and contrast for the LC were evaluated. Logistic regression was used to calculate predicted probabilities by using the combination of SN and LC NM measures. The discriminative power of the NM measures in detecting subjects with PDTD from ET was assessed with a receiver operative characteristic curve, and the area under the curve (AUC) was calculated. RESULTS The NM contrast-to-noise ratio (CNR) of the LC, the NM volume, and CNR of the SN on the right and left sides were significantly lower in PDTD subjects than in ET subjects or healthy controls (all P < 0.05). Furthermore, when combining the best model constructed from the NM measures, the AUC reached 0.92 in differentiating PDTD from ET. CONCLUSION The NM volume and contrast measures of the SN and contrast for the LC provided a new perspective on the differential diagnosis of PDTD and ET, and the investigation of the underlying pathophysiology.
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Affiliation(s)
- Xinhui Wang
- From the Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China
| | - Pei Huang
- From the Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China
| | - Ewart Mark Haacke
- From the Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China; Department of Biomedical Engineering, Wayne State University, 3990 John R, Detroit, MI, USA; Department of Radiology, Wayne State University, 3990 John R, Detroit, MI, USA; Department of Neurology, Wayne State University, 3990 John R, Detroit, MI, USA
| | - Yu Liu
- From the Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China
| | - Youmin Zhang
- From the Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China
| | - Zhijia Jin
- From the Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China
| | - Yan Li
- From the Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China
| | - Qiuyun Xu
- Department of Biomedical Engineering, Wayne State University, 3990 John R, Detroit, MI, USA
| | - Peng Liu
- From the Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China
| | - Shengdi Chen
- From the Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China.
| | - Naying He
- From the Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China.
| | - Fuhua Yan
- From the Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin Er Road, Shanghai 200025, China.
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Filip P, Kokošová V, Valenta Z, Baláž M, Mangia S, Michaeli S, Vojtíšek L. Utility of quantitative MRI metrics in brain ageing research. Front Aging Neurosci 2023; 15:1099499. [PMID: 36967815 PMCID: PMC10034010 DOI: 10.3389/fnagi.2023.1099499] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 02/06/2023] [Indexed: 03/11/2023] Open
Abstract
The advent of new, advanced quantitative MRI metrics allows for in vivo evaluation of multiple biological processes highly relevant for ageing. The presented study combines several MRI parameters hypothesised to detect distinct biological characteristics as myelin density, cellularity, cellular membrane integrity and iron concentration. 116 healthy volunteers, continuously distributed over the whole adult age span, underwent a multi-modal MRI protocol acquisition. Scatterplots of individual MRI metrics revealed that certain MRI protocols offer much higher sensitivity to early adulthood changes while plateauing in higher age (e.g., global functional connectivity in cerebral cortex or orientation dispersion index in white matter), while other MRI metrics provided reverse ability—stable levels in young adulthood with sharp changes with rising age (e.g., T1ρ and T2ρ). Nonetheless, despite the previously published validations of specificity towards microstructural biology based on cytoarchitectonic maps in healthy population or alterations in certain pathologies, several metrics previously hypothesised to be selective to common measures failed to show similar scatterplot distributions, pointing to further confounding factors directly related to age. Furthermore, other metrics, previously shown to detect different biological characteristics, exhibited substantial intercorrelations, be it due to the nature of the MRI protocol itself or co-dependence of relevant biological microstructural processes. All in all, the presented study provides a unique basis for the design and choice of relevant MRI parameters depending on the age group of interest. Furthermore, it calls for caution in simplistic biological inferences in ageing based on one simple MRI metric, even though previously validated under other conditions. Complex multi-modal approaches combining several metrics to extract the shared subcomponent will be necessary to achieve the desired goal of histological MRI.
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Affiliation(s)
- Pavel Filip
- Department of Neurology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czechia
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, United States
- *Correspondence: Pavel Filip,
| | - Viktória Kokošová
- Department of Neurology, Faculty of Medicine, Masaryk University and University Hospital Brno, Brno, Czechia
- First Department of Neurology, Faculty of Medicine, University Hospital of St. Anne, Masaryk University, Brno, Czechia
| | - Zdeněk Valenta
- Department of Statistical Modelling, Institute of Computer Science of the Czech Academy of Sciences, Prague, Czechia
| | - Marek Baláž
- First Department of Neurology, Faculty of Medicine, University Hospital of St. Anne, Masaryk University, Brno, Czechia
| | - Silvia Mangia
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, United States
| | - Shalom Michaeli
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, United States
| | - Lubomír Vojtíšek
- Neuroscience Centre, Central European Institute of Technology (CEITEC), Masaryk University, Brno, Czechia
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Filip P, Burdová K, Valenta Z, Jech R, Kokošová V, Baláž M, Mangia S, Michaeli S, Bareš M, Vojtíšek L. Tremor associated with similar structural networks in Parkinson's disease and essential tremor. Parkinsonism Relat Disord 2021; 95:28-34. [PMID: 34979362 DOI: 10.1016/j.parkreldis.2021.12.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2021] [Revised: 12/01/2021] [Accepted: 12/20/2021] [Indexed: 11/24/2022]
Abstract
INTRODUCTION Despite substantial clinical and pathophysiological differences, the characteristics of tremor in Parkinson's disease (PD) and essential tremor (ET) patients bear certain similarities. The presented study delineates tremor-related structural networks in these two disorders. METHODS 42 non-advanced PD patients (18 tremor-dominant, 24 without substantial tremor), 17 ET, and 45 healthy controls underwent high-angular resolution diffusion-weighted imaging acquisition to reconstruct their structural motor connectomes as a proxy of the anatomical interconnections between motor network regions, implementing state-of-the-art globally optimised probabilistic tractography. RESULTS When compared to healthy controls, ET patients exhibited higher structural connectivity in the cerebello-thalamo-cortical network. Interestingly, the comparison of tremor-dominant PD patients and PD patients without tremor yielded very similar results - higher structural connectivity in tremor-dominant PD sharing multiple nodes with the tremor network detected in ET, despite the generally lower structural connectivity between basal ganglia and frontal cortex in the whole PD group when compared to healthy controls. CONCLUSION The higher structural connectivity of the cerebello-thalamo-cortical network seems to be the dominant tremor driver in both PD and ET. While it appears to be the only tremor-related network in ET, its combination with large scale hypoconnectivity in the frontal cortico-subcortical network in PD may explain different clinical features of tremor in these two disorders.
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Affiliation(s)
- Pavel Filip
- Department of Neurology, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic; Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, USA.
| | - Kristína Burdová
- Department of Neurology, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic
| | - Zdeněk Valenta
- Department of Statistical Modelling, Institute of Computer Science of the Czech Academy of Sciences, Prague, Czech Republic
| | - Robert Jech
- Department of Neurology, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic
| | - Viktória Kokošová
- Department of Neurology, Faculty of Medicine, Masaryk University and University Hospital Brno, Brno, Czech Republic
| | - Marek Baláž
- First Department of Neurology, Faculty of Medicine, Masaryk University and University Hospital of St. Anne, Brno, Czech Republic
| | - Silvia Mangia
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, USA
| | - Shalom Michaeli
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, USA
| | - Martin Bareš
- First Department of Neurology, Faculty of Medicine, Masaryk University and University Hospital of St. Anne, Brno, Czech Republic; Department of Neurology, School of Medicine, University of Minnesota, Minneapolis, MN, USA
| | - Lubomír Vojtíšek
- Central European Institute of Technology (CEITEC), Masaryk University, Neuroscience Centre, Brno, Czech Republic
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Lopez-de-Ipina K, Solé-Casals J, Sánchez-Méndez JI, Romero-Garcia R, Fernandez E, Requejo C, Poologaindran A, Faúndez-Zanuy M, Martí-Massó JF, Bergareche A, Suckling J. Analysis of Fine Motor Skills in Essential Tremor: Combining Neuroimaging and Handwriting Biomarkers for Early Management. Front Hum Neurosci 2021; 15:648573. [PMID: 34168544 PMCID: PMC8219239 DOI: 10.3389/fnhum.2021.648573] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Accepted: 04/19/2021] [Indexed: 12/22/2022] Open
Abstract
Essential tremor (ET) is a highly prevalent neurological disorder characterized by action-induced tremors involving the hand, voice, head, and/or face. Importantly, hand tremor is present in nearly all forms of ET, resulting in impaired fine motor skills and diminished quality of life. To advance early diagnostic approaches for ET, automated handwriting tasks and magnetic resonance imaging (MRI) offer an opportunity to develop early essential clinical biomarkers. In this study, we present a novel approach for the early clinical diagnosis and monitoring of ET based on integrating handwriting and neuroimaging analysis. We demonstrate how the analysis of fine motor skills, as measured by an automated Archimedes' spiral task, is correlated with neuroimaging biomarkers for ET. Together, we present a novel modeling approach that can serve as a complementary and promising support tool for the clinical diagnosis of ET and a large range of tremors.
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Affiliation(s)
- Karmele Lopez-de-Ipina
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
- EleKin Research Group, Department of System Engineering and Automation, University of the Basque Country UPV/EHU, Donostia-San Sebastian, Spain
| | - Jordi Solé-Casals
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
- Data and Signal Processing Research Group, University of Vic-Central University of Catalonia, Barcelona, Spain
| | - José Ignacio Sánchez-Méndez
- EleKin Research Group, Department of System Engineering and Automation, University of the Basque Country UPV/EHU, Donostia-San Sebastian, Spain
| | | | - Elsa Fernandez
- EleKin Research Group, Department of System Engineering and Automation, University of the Basque Country UPV/EHU, Donostia-San Sebastian, Spain
| | - Catalina Requejo
- Cajal Institute, Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain
| | - Anujan Poologaindran
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
- The Alan Turing Institute, British Library, London, United Kingdom
| | | | - José Félix Martí-Massó
- Neurodegenerative Disorders Area, Biodonostia Health Research Institute, Donostia-San Sebastian, Spain
- Movement Disorders Unit, Department of Neurology, Donostia University Hospital, Donostia-San Sebastian, Spain
- Biomedical Research Networking Centre Consortium for the Area of Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Alberto Bergareche
- Neurodegenerative Disorders Area, Biodonostia Health Research Institute, Donostia-San Sebastian, Spain
- Movement Disorders Unit, Department of Neurology, Donostia University Hospital, Donostia-San Sebastian, Spain
- Biomedical Research Networking Centre Consortium for the Area of Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - John Suckling
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
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