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Prediction of rehabilitation induced motor recovery after stroke using a multi-dimensional and multi-modal approach

BACKGROUND: Stroke is a debilitating disease affecting millions of people worldwide. Despite the survival rate has significantly increased over the years, many stroke survivors are left with severe impairments impacting their quality of life. Rehabilitation programs have proved to be successful in i...

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Autores principales: Salvalaggio, Silvia, Turolla, Andrea, Andò, Martina, Barresi, Rita, Burgio, Francesca, Busan, Pierpaolo, Cortese, Anna Maria, D’Imperio, Daniela, Danesin, Laura, Ferrazzi, Giulio, Maistrello, Lorenza, Mascotto, Eleonora, Parrotta, Ilaria, Pezzetta, Rachele, Rigon, Elena, Vedovato, Anna, Zago, Sara, Zorzi, Marco, Arcara, Giorgio, Mantini, Dante, Filippini, Nicola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10352609/
https://www.ncbi.nlm.nih.gov/pubmed/37469951
http://dx.doi.org/10.3389/fnagi.2023.1205063
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author Salvalaggio, Silvia
Turolla, Andrea
Andò, Martina
Barresi, Rita
Burgio, Francesca
Busan, Pierpaolo
Cortese, Anna Maria
D’Imperio, Daniela
Danesin, Laura
Ferrazzi, Giulio
Maistrello, Lorenza
Mascotto, Eleonora
Parrotta, Ilaria
Pezzetta, Rachele
Rigon, Elena
Vedovato, Anna
Zago, Sara
Zorzi, Marco
Arcara, Giorgio
Mantini, Dante
Filippini, Nicola
author_facet Salvalaggio, Silvia
Turolla, Andrea
Andò, Martina
Barresi, Rita
Burgio, Francesca
Busan, Pierpaolo
Cortese, Anna Maria
D’Imperio, Daniela
Danesin, Laura
Ferrazzi, Giulio
Maistrello, Lorenza
Mascotto, Eleonora
Parrotta, Ilaria
Pezzetta, Rachele
Rigon, Elena
Vedovato, Anna
Zago, Sara
Zorzi, Marco
Arcara, Giorgio
Mantini, Dante
Filippini, Nicola
author_sort Salvalaggio, Silvia
collection PubMed
description BACKGROUND: Stroke is a debilitating disease affecting millions of people worldwide. Despite the survival rate has significantly increased over the years, many stroke survivors are left with severe impairments impacting their quality of life. Rehabilitation programs have proved to be successful in improving the recovery process. However, a reliable model of sensorimotor recovery and a clear identification of predictive markers of rehabilitation-induced recovery are still needed. This article introduces the cross-modality protocols designed to investigate the rehabilitation treatment’s effect in a group of stroke survivors. METHODS/DESIGN: A total of 75 stroke patients, admitted at the IRCCS San Camillo rehabilitation Hospital in Venice (Italy), will be included in this study. Here, we describe the rehabilitation programs, clinical, neuropsychological, and physiological/imaging [including electroencephalography (EEG), transcranial magnetic stimulation (TMS), and magnetic resonance imaging (MRI) techniques] protocols set up for this study. Blood collection for the characterization of predictive biological biomarkers will also be taken. Measures derived from data acquired will be used as candidate predictors of motor recovery. DISCUSSION/SUMMARY: The integration of cutting-edge physiological and imaging techniques, with clinical and cognitive assessment, dose of rehabilitation and biological variables will provide a unique opportunity to define a predictive model of recovery in stroke patients. Taken together, the data acquired in this project will help to define a model of rehabilitation induced sensorimotor recovery, with the final aim of developing personalized treatments promoting the greatest chance of recovery of the compromised functions.
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spelling pubmed-103526092023-07-19 Prediction of rehabilitation induced motor recovery after stroke using a multi-dimensional and multi-modal approach Salvalaggio, Silvia Turolla, Andrea Andò, Martina Barresi, Rita Burgio, Francesca Busan, Pierpaolo Cortese, Anna Maria D’Imperio, Daniela Danesin, Laura Ferrazzi, Giulio Maistrello, Lorenza Mascotto, Eleonora Parrotta, Ilaria Pezzetta, Rachele Rigon, Elena Vedovato, Anna Zago, Sara Zorzi, Marco Arcara, Giorgio Mantini, Dante Filippini, Nicola Front Aging Neurosci Neuroscience BACKGROUND: Stroke is a debilitating disease affecting millions of people worldwide. Despite the survival rate has significantly increased over the years, many stroke survivors are left with severe impairments impacting their quality of life. Rehabilitation programs have proved to be successful in improving the recovery process. However, a reliable model of sensorimotor recovery and a clear identification of predictive markers of rehabilitation-induced recovery are still needed. This article introduces the cross-modality protocols designed to investigate the rehabilitation treatment’s effect in a group of stroke survivors. METHODS/DESIGN: A total of 75 stroke patients, admitted at the IRCCS San Camillo rehabilitation Hospital in Venice (Italy), will be included in this study. Here, we describe the rehabilitation programs, clinical, neuropsychological, and physiological/imaging [including electroencephalography (EEG), transcranial magnetic stimulation (TMS), and magnetic resonance imaging (MRI) techniques] protocols set up for this study. Blood collection for the characterization of predictive biological biomarkers will also be taken. Measures derived from data acquired will be used as candidate predictors of motor recovery. DISCUSSION/SUMMARY: The integration of cutting-edge physiological and imaging techniques, with clinical and cognitive assessment, dose of rehabilitation and biological variables will provide a unique opportunity to define a predictive model of recovery in stroke patients. Taken together, the data acquired in this project will help to define a model of rehabilitation induced sensorimotor recovery, with the final aim of developing personalized treatments promoting the greatest chance of recovery of the compromised functions. Frontiers Media S.A. 2023-07-04 /pmc/articles/PMC10352609/ /pubmed/37469951 http://dx.doi.org/10.3389/fnagi.2023.1205063 Text en Copyright © 2023 Salvalaggio, Turolla, Andò, Barresi, Burgio, Busan, Cortese, D’Imperio, Danesin, Ferrazzi, Maistrello, Mascotto, Parrotta, Pezzetta, Rigon, Vedovato, Zago, Zorzi, Arcara, Mantini and Filippini. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Salvalaggio, Silvia
Turolla, Andrea
Andò, Martina
Barresi, Rita
Burgio, Francesca
Busan, Pierpaolo
Cortese, Anna Maria
D’Imperio, Daniela
Danesin, Laura
Ferrazzi, Giulio
Maistrello, Lorenza
Mascotto, Eleonora
Parrotta, Ilaria
Pezzetta, Rachele
Rigon, Elena
Vedovato, Anna
Zago, Sara
Zorzi, Marco
Arcara, Giorgio
Mantini, Dante
Filippini, Nicola
Prediction of rehabilitation induced motor recovery after stroke using a multi-dimensional and multi-modal approach
title Prediction of rehabilitation induced motor recovery after stroke using a multi-dimensional and multi-modal approach
title_full Prediction of rehabilitation induced motor recovery after stroke using a multi-dimensional and multi-modal approach
title_fullStr Prediction of rehabilitation induced motor recovery after stroke using a multi-dimensional and multi-modal approach
title_full_unstemmed Prediction of rehabilitation induced motor recovery after stroke using a multi-dimensional and multi-modal approach
title_short Prediction of rehabilitation induced motor recovery after stroke using a multi-dimensional and multi-modal approach
title_sort prediction of rehabilitation induced motor recovery after stroke using a multi-dimensional and multi-modal approach
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10352609/
https://www.ncbi.nlm.nih.gov/pubmed/37469951
http://dx.doi.org/10.3389/fnagi.2023.1205063
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