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Functional Imaging to Guide Network-Based TMS Treatments: Toward a Tailored Medicine Approach in Alzheimer’s Disease

A growing number of studies is using fMRI-based connectivity to guide transcranial magnetic stimulation (TMS) target identification in both normal and clinical populations. TMS has gained increasing attention as a potential therapeutic strategy also in Alzheimer’s disease (AD), but an endorsed targe...

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Autores principales: Bagattini, Chiara, Brignani, Debora, Bonnì, Sonia, Quattrini, Giulia, Gasparotti, Roberto, Pievani, Michela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8287201/
https://www.ncbi.nlm.nih.gov/pubmed/34290585
http://dx.doi.org/10.3389/fnins.2021.687493
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author Bagattini, Chiara
Brignani, Debora
Bonnì, Sonia
Quattrini, Giulia
Gasparotti, Roberto
Pievani, Michela
author_facet Bagattini, Chiara
Brignani, Debora
Bonnì, Sonia
Quattrini, Giulia
Gasparotti, Roberto
Pievani, Michela
author_sort Bagattini, Chiara
collection PubMed
description A growing number of studies is using fMRI-based connectivity to guide transcranial magnetic stimulation (TMS) target identification in both normal and clinical populations. TMS has gained increasing attention as a potential therapeutic strategy also in Alzheimer’s disease (AD), but an endorsed target localization strategy in this population is still lacking. In this proof of concept study, we prove the feasibility of a tailored TMS targeting approach for AD, which stems from a network-based perspective. Based on functional imaging, the procedure allows to extract individual optimal targets meanwhile accounting for functional variability. Single-subject resting-state fMRI was used to extract individual target coordinates of two networks primarily affected in AD, the default mode and the fronto-parietal network. The localization of these targets was compared to that of traditional group-level approaches and tested against varying degrees of TMS focality. The distance between individual fMRI-derived coordinates and traditionally defined targets was significant for a supposed TMS focality of 12 mm and in some cases up to 20 mm. Comparison with anatomical labels confirmed a lack of 1:1 correspondence between anatomical and functional targets. The proposed network-based fMRI-guided TMS approach, while accounting for inter-individual functional variability, allows to target core AD networks, and might thus represent a step toward tailored TMS interventions for AD.
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spelling pubmed-82872012021-07-20 Functional Imaging to Guide Network-Based TMS Treatments: Toward a Tailored Medicine Approach in Alzheimer’s Disease Bagattini, Chiara Brignani, Debora Bonnì, Sonia Quattrini, Giulia Gasparotti, Roberto Pievani, Michela Front Neurosci Neuroscience A growing number of studies is using fMRI-based connectivity to guide transcranial magnetic stimulation (TMS) target identification in both normal and clinical populations. TMS has gained increasing attention as a potential therapeutic strategy also in Alzheimer’s disease (AD), but an endorsed target localization strategy in this population is still lacking. In this proof of concept study, we prove the feasibility of a tailored TMS targeting approach for AD, which stems from a network-based perspective. Based on functional imaging, the procedure allows to extract individual optimal targets meanwhile accounting for functional variability. Single-subject resting-state fMRI was used to extract individual target coordinates of two networks primarily affected in AD, the default mode and the fronto-parietal network. The localization of these targets was compared to that of traditional group-level approaches and tested against varying degrees of TMS focality. The distance between individual fMRI-derived coordinates and traditionally defined targets was significant for a supposed TMS focality of 12 mm and in some cases up to 20 mm. Comparison with anatomical labels confirmed a lack of 1:1 correspondence between anatomical and functional targets. The proposed network-based fMRI-guided TMS approach, while accounting for inter-individual functional variability, allows to target core AD networks, and might thus represent a step toward tailored TMS interventions for AD. Frontiers Media S.A. 2021-07-05 /pmc/articles/PMC8287201/ /pubmed/34290585 http://dx.doi.org/10.3389/fnins.2021.687493 Text en Copyright © 2021 Bagattini, Brignani, Bonnì, Quattrini, Gasparotti and Pievani. 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
Bagattini, Chiara
Brignani, Debora
Bonnì, Sonia
Quattrini, Giulia
Gasparotti, Roberto
Pievani, Michela
Functional Imaging to Guide Network-Based TMS Treatments: Toward a Tailored Medicine Approach in Alzheimer’s Disease
title Functional Imaging to Guide Network-Based TMS Treatments: Toward a Tailored Medicine Approach in Alzheimer’s Disease
title_full Functional Imaging to Guide Network-Based TMS Treatments: Toward a Tailored Medicine Approach in Alzheimer’s Disease
title_fullStr Functional Imaging to Guide Network-Based TMS Treatments: Toward a Tailored Medicine Approach in Alzheimer’s Disease
title_full_unstemmed Functional Imaging to Guide Network-Based TMS Treatments: Toward a Tailored Medicine Approach in Alzheimer’s Disease
title_short Functional Imaging to Guide Network-Based TMS Treatments: Toward a Tailored Medicine Approach in Alzheimer’s Disease
title_sort functional imaging to guide network-based tms treatments: toward a tailored medicine approach in alzheimer’s disease
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8287201/
https://www.ncbi.nlm.nih.gov/pubmed/34290585
http://dx.doi.org/10.3389/fnins.2021.687493
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