Literature DB >> 31278421

Exploring cortical predictors of clinical response to electroconvulsive therapy in major depression.

Mike M Schmitgen1, Katharina M Kubera1, Malte S Depping1, Henrike M Nolte1, Dusan Hirjak2, Stefan Hofer3, Julia H Hasenkamp1, Ulrich Seidl1,4, Bram Stieltjes5, Klaus H Maier-Hein6, Fabio Sambataro7, Alexander Sartorius2, Philipp A Thomann1,8, Robert C Wolf9.   

Abstract

Electroconvulsive therapy (ECT) is a rapid and highly effective treatment option for treatment-resistant major depressive disorder (TRD). The neural mechanisms underlying such beneficial effects are poorly understood. Exploring associations between changes of brain structure and clinical response is crucial for understanding ECT mechanisms of action and relevant for the validation of potential biomarkers that can facilitate the prediction of ECT efficacy. The aim of this explorative study was to identify cortical predictors of clinical response in TRD patients treated with ECT. We longitudinally investigated 12 TRD patients before and after ECT. Twelve matched healthy controls were studied cross sectionally. Demographical, clinical, and structural magnetic resonance imaging data at 3 T and multiple cortical markers derived from surface-based morphometry (SBM) analyses were considered. Multiple regression models were computed to identify predictors of clinical response to ECT, as reflected by Hamilton Depression Rating Scale (HAMD) score changes. Symptom severity differences pre-post-ECT were predicted by models including demographic data, clinical data and SBM of frontal, cingulate, and entorhinal structures. Using all-subsets regression, a model comprising HAMD score at baseline and cortical thickness of the left rostral anterior cingulate gyrus explained most variance in the data (multiple R2 = 0.82). The data suggest that SBM provides powerful measures for identifying biomarkers for ECT response in TRD. Rostral anterior cingulate thickness and HAMD score at baseline showed the greatest predictive power of clinical response, in contrast to cortical complexity, cortical gyrification, or demographical data.

Entities:  

Keywords:  CAT12; Electroconvulsive therapy; Response prediction; Surface-based morphometry; Treatment-resistant depression

Year:  2019        PMID: 31278421     DOI: 10.1007/s00406-019-01033-w

Source DB:  PubMed          Journal:  Eur Arch Psychiatry Clin Neurosci        ISSN: 0940-1334            Impact factor:   5.270


  50 in total

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Authors:  Jussi Tohka; Alex Zijdenbos; Alan Evans
Journal:  Neuroimage       Date:  2004-09       Impact factor: 6.556

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Authors:  Joan Busner; Steven D Targum
Journal:  Psychiatry (Edgmont)       Date:  2007-07

3.  Grey matter volume increase following electroconvulsive therapy in patients with late life depression: a longitudinal MRI study.

Authors:  Filip Bouckaert; François-Laurent De Winter; Louise Emsell; Annemieke Dols; Didi Rhebergen; Martien Wampers; Stefan Sunaert; Max Stek; Pascal Sienaert; Mathieu Vandenbulcke
Journal:  J Psychiatry Neurosci       Date:  2016-03       Impact factor: 6.186

Review 4.  Structural-functional brain changes in depressed patients during and after electroconvulsive therapy.

Authors:  Antoine Yrondi; Patrice Péran; Anne Sauvaget; Laurent Schmitt; Christophe Arbus
Journal:  Acta Neuropsychiatr       Date:  2016-11-23       Impact factor: 3.403

5.  Effects of electroconvulsive therapy on brain functional activation and connectivity in depression.

Authors:  Erik B Beall; Donald A Malone; Roman M Dale; David J Muzina; Katherine A Koenig; Pallab K Bhattacharrya; Stephen E Jones; Michael D Phillips; Mark J Lowe
Journal:  J ECT       Date:  2012-12       Impact factor: 3.635

6.  Fractal dimension analysis of the cortical ribbon in mild Alzheimer's disease.

Authors:  Richard D King; Brandon Brown; Michael Hwang; Tina Jeon; Anuh T George
Journal:  Neuroimage       Date:  2010-06-25       Impact factor: 6.556

7.  Resting-state connectivity biomarkers define neurophysiological subtypes of depression.

Authors:  Andrew T Drysdale; Logan Grosenick; Jonathan Downar; Katharine Dunlop; Farrokh Mansouri; Yue Meng; Robert N Fetcho; Benjamin Zebley; Desmond J Oathes; Amit Etkin; Alan F Schatzberg; Keith Sudheimer; Jennifer Keller; Helen S Mayberg; Faith M Gunning; George S Alexopoulos; Michael D Fox; Alvaro Pascual-Leone; Henning U Voss; B J Casey; Marc J Dubin; Conor Liston
Journal:  Nat Med       Date:  2016-12-05       Impact factor: 53.440

8.  Speed of response and remission in major depressive disorder with acute electroconvulsive therapy (ECT): a Consortium for Research in ECT (CORE) report.

Authors:  Mustafa M Husain; A John Rush; Max Fink; Rebecca Knapp; Georgios Petrides; Teresa Rummans; Melanie M Biggs; Kevin O'Connor; Keith Rasmussen; Marc Litle; Wenle Zhao; Hilary J Bernstein; Glenn Smith; Martina Mueller; Shawn M McClintock; Samuel H Bailine; Charles H Kellner
Journal:  J Clin Psychiatry       Date:  2004-04       Impact factor: 4.384

9.  Dynamic Development of Regional Cortical Thickness and Surface Area in Early Childhood.

Authors:  Amanda E Lyall; Feng Shi; Xiujuan Geng; Sandra Woolson; Gang Li; Li Wang; Robert M Hamer; Dinggang Shen; John H Gilmore
Journal:  Cereb Cortex       Date:  2014-03-02       Impact factor: 5.357

10.  Electroconvulsive therapy response in major depressive disorder: a pilot functional network connectivity resting state FMRI investigation.

Authors:  Christopher C Abbott; Nicholas T Lemke; Shruti Gopal; Robert J Thoma; Juan Bustillo; Vince D Calhoun; Jessica A Turner
Journal:  Front Psychiatry       Date:  2013-03-01       Impact factor: 4.157

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  5 in total

Review 1.  Parsing the Network Mechanisms of Electroconvulsive Therapy.

Authors:  Amber M Leaver; Randall Espinoza; Benjamin Wade; Katherine L Narr
Journal:  Biol Psychiatry       Date:  2021-11-26       Impact factor: 12.810

2.  Accounting for symptom heterogeneity can improve neuroimaging models of antidepressant response after electroconvulsive therapy.

Authors:  Benjamin S C Wade; Gerhard Hellemann; Randall T Espinoza; Roger P Woods; Shantanu H Joshi; Ronny Redlich; Udo Dannlowski; Anders Jorgensen; Christopher C Abbott; Leif Oltedal; Katherine L Narr
Journal:  Hum Brain Mapp       Date:  2021-08-13       Impact factor: 5.038

Review 3.  Cortical complexity estimation using fractal dimension: A systematic review of the literature on clinical and nonclinical samples.

Authors:  Valentina Meregalli; Francesco Alberti; Christopher R Madan; Paolo Meneguzzo; Alessandro Miola; Nicolò Trevisan; Fabio Sambataro; Angela Favaro; Enrico Collantoni
Journal:  Eur J Neurosci       Date:  2022-03-09       Impact factor: 3.698

4.  Cortical Thickness Predicts Response Following 2 Weeks of SSRI Regimen in First-Episode, Drug-Naive Major Depressive Disorder: An MRI Study.

Authors:  Peiyi Wu; Aixia Zhang; Ning Sun; Lei Lei; Penghong Liu; Yikun Wang; Hejun Li; Chunxia Yang; Kerang Zhang
Journal:  Front Psychiatry       Date:  2022-02-22       Impact factor: 4.157

Review 5.  The Neurobiological Effects of Electroconvulsive Therapy Studied Through Magnetic Resonance: What Have We Learned, and Where Do We Go?

Authors:  Olga Therese Ousdal; Giulio E Brancati; Ute Kessler; Vera Erchinger; Anders M Dale; Christopher Abbott; Leif Oltedal
Journal:  Biol Psychiatry       Date:  2021-05-31       Impact factor: 13.382

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