Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/105843
Title: Precision non-implantable neuromodulation therapies: a perspective for the depressed brain
Authors: Borrione, Lucas
Bellini, Helena
Razza, Lais Boralli
Ávila, Ana G. 
Baeken, Chris
Brem, Anna-Katharine
Busatto, Geraldo
Carvalho, Andre F.
Chekroud, Adam
Daskalakis, Zafiris J.
Deng, Zhi-De
Downar, Jonathan
Gattaz, Wagner
Loo, Colleen
Lotufo, Paulo A
Martin, Maria da Graça M.
McClintock, Shawn M.
O'Shea, Jacinta
Padberg, Frank
Passos, Ives C.
Salum, Giovanni A.
Vanderhasselt, Marie-Anne
Fraguas, Renerio
Benseñor, Isabela
Valiengo, Leandro
Brunoni, Andre R.
Keywords: Major depressive disorder; transcranial magnetic stimulation; transcranial direct current stimulation; electroconvulsive therapy; precision medicine
Issue Date: Aug-2020
Publisher: Associacao Brasileira de Psiquiatria
Serial title, monograph or event: Brazilian Journal of Psychiatry
Volume: 42
Issue: 4
Abstract: Current first-line treatments for major depressive disorder (MDD) include pharmacotherapy and cognitive-behavioral therapy. However, one-third of depressed patients do not achieve remission after multiple medication trials, and psychotherapy can be costly and time-consuming. Although non-implantable neuromodulation (NIN) techniques such as transcranial magnetic stimulation, transcranial direct current stimulation, electroconvulsive therapy, and magnetic seizure therapy are gaining momentum for treating MDD, the efficacy of non-convulsive techniques is still modest, whereas use of convulsive modalities is limited by their cognitive side effects. In this context, we propose that NIN techniques could benefit from a precision-oriented approach. In this review, we discuss the challenges and opportunities in implementing such a framework, focusing on enhancing NIN effects via a combination of individualized cognitive interventions, using closed-loop approaches, identifying multimodal biomarkers, using computer electric field modeling to guide targeting and quantify dosage, and using machine learning algorithms to integrate data collected at multiple biological levels and identify clinical responders. Though promising, this framework is currently limited, as previous studies have employed small samples and did not sufficiently explore pathophysiological mechanisms associated with NIN response and side effects. Moreover, cost-effectiveness analyses have not been performed. Nevertheless, further advancements in clinical trials of NIN could shift the field toward a more "precision-oriented" practice.
URI: https://hdl.handle.net/10316/105843
ISSN: 1809-452X
1516-4446
DOI: 10.1590/1516-4446-2019-0741
Rights: openAccess
Appears in Collections:I&D CINEICC - Artigos em Revistas Internacionais

Show full item record

SCOPUSTM   
Citations

21
checked on Apr 29, 2024

WEB OF SCIENCETM
Citations

17
checked on Apr 2, 2024

Page view(s)

33
checked on Apr 23, 2024

Download(s)

17
checked on Apr 23, 2024

Google ScholarTM

Check

Altmetric

Altmetric


This item is licensed under a Creative Commons License Creative Commons