Subgenual Anterior Cingulate–Medial Orbitofrontal Functional Connectivity in Medication-Resistant Major Depression: A Neurobiological Marker for Accelerated Intermittent Theta Burst Stimulation Treatment?

Baeken, Chris; Duprat, Romain; Wu, Guo‐Rong; Raedt, Rudi De; Heeringen, Kees van

doi:10.1016/j.bpsc.2017.01.001

Cited by 53 publications

(71 citation statements)

References 63 publications

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“…And Fox et al (2012 demonstrated that the clinical effects of rTMS are linked to the functional anti-correlation between the subgenual anterior cingulate cortex (sgACC) and the stimulation spot in the left DLPFC. This anticorrelation between the sgACC and parts of the left superior medial prefrontal cortex was also suggested to have predictive value for the outcome of accelerated rTMS in a cohort of MDD patients (Baeken et al, 2014), although in another accelerated iTBS this was not found to be that straightforward (Baeken, Duprat, Wu, De Raedt, & van Heeringen, 2017a). Nevertheless, Downar et al (2014) showed in a cohort of MDD patients that the graph measure betweenness centrality can be used to distinguish responders from nonresponders to rTMS to the dorsomedial prefrontal cortex.…”

Section: Cocchi Showed Different Effects Of Continuous Versus Inhibitmentioning

confidence: 89%

“…Previously, it has been shown that rs-fMRI connectivities can be used for this purpose. This anticorrelation between the sgACC and parts of the left superior medial prefrontal cortex was also suggested to have predictive value for the outcome of accelerated rTMS in a cohort of MDD patients (Baeken et al, 2014), although in another accelerated iTBS this was not found to be that straightforward (Baeken, Duprat, Wu, De Raedt, & van Heeringen, 2017a). And Fox et al (2012 demonstrated that the clinical effects of rTMS are linked to the functional anti-correlation between the subgenual anterior cingulate cortex (sgACC) and the stimulation spot in the left DLPFC.…”

Section: Cocchi Showed Different Effects Of Continuous Versus Inhibitmentioning

confidence: 92%

“…However, for the latter application, the functional connectivity findings are not that straightforward (Baeken et al 2017a;Baeken et al, 2014) and the aiTBS treatment delivered to the left DLPFC may have different neurobiological effects on the reward system (including the caudate), based on the level of anhedonia in the depressive state (Duprat, Wu, De Raedt, & Baeken, 2017). Indeed, it remains to be determined whether the left DLPFC is the best target to stimulate.…”

Section: Graph Measures As Biomarkermentioning

confidence: 99%

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Focal application of accelerated iTBS results in global changes in graph measures

Klooster

Franklin

Besseling

et al. 2018

Human Brain Mapping

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Graph analysis was used to study the effects of accelerated intermittent theta burst stimulation (aiTBS) on the brain's network topology in medication‐resistant depressed patients. Anatomical and resting‐state functional MRI (rs‐fMRI) was recorded at baseline and after sham and verum stimulation. Depression severity was assessed using the Hamilton Depression Rating Scale (HDRS). Using various graph measures, the different effects of sham and verum aiTBS were calculated. It was also investigated whether changes in graph measures were correlated to clinical responses. Furthermore, by correlating baseline graph measures with the changes in HDRS in terms of percentage, the potential of graph measures as biomarker was studied. Although no differences were observed between the effects of verum and sham stimulation on whole‐brain graph measures and changes in graph measures did not correlate with clinical response, the baseline values of clustering coefficient and global efficiency showed to be predictive of the clinical response to verum aiTBS. Nodal effects were found throughout the whole brain. The distribution of these effects could not be linked to the strength of the functional connectivity between the stimulation site and the node. This study showed that the effects of aiTBS on graph measures distribute beyond the actual stimulation site. However, additional research into the complex interactions between different areas in the brain is necessary to understand the effects of aiTBS in more detail.

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Section: Cocchi Showed Different Effects Of Continuous Versus Inhibitmentioning

confidence: 89%

Section: Cocchi Showed Different Effects Of Continuous Versus Inhibitmentioning

confidence: 92%

Section: Graph Measures As Biomarkermentioning

confidence: 99%

See 1 more Smart Citation

Focal application of accelerated iTBS results in global changes in graph measures

Klooster

Franklin

Besseling

et al. 2018

Human Brain Mapping

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“…Neuroimaging has fundamentally advanced our understanding of the neurobiology of depression and provides the means to examine and potentially predict the regional and networkwide effects of rTMS treatment that mediate individual treatment response. The AN comprises the connections of the affective division (pregenual and subgenual cingulate cortex, SGC) of the anterior cingulate cortex (Sheline et al, 2010;Yu et al, 2011), and has been linked to abnormal emotional regulation and processing, disease severity and treatment response (Baeken, Duprat, Wu, De Raedt, & van Heeringen, 2017;Salomons et al, 2014;Sheline et al, 2010;Yu et al, 2011). The default mode network (DMN) and the affective network (AN) are now considered central to the neurobiology of depression and the therapeutic effects of rTMS (Downar & Daskalakis, 2013;Kaiser, Andrews-Hanna, Wager, & Pizzagalli, 2015;Sheline, Price, Yan, & Mintun, 2010;Tik et al, 2017).…”

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confidence: 99%

A multivariate neuroimaging biomarker of individual outcome to transcranial magnetic stimulation in depression

Cash

Cocchi

Anderson

et al. 2019

Human Brain Mapping

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The neurobiology of major depressive disorder (MDD) remains incompletely understood, and many individuals fail to respond to standard treatments. Repetitive transcranial magnetic stimulation (rTMS) of the dorsolateral prefrontal cortex (DLPFC) has emerged as a promising antidepressant therapy. However, the heterogeneity of response underscores a pressing need for biomarkers of treatment outcome. We acquired resting state functional magnetic resonance imaging (rsfMRI) data in 47 MDD individuals prior to 5–8 weeks of rTMS treatment targeted using the F3 beam approach and in 29 healthy comparison subjects. The caudate, prefrontal cortex, and thalamus showed significantly lower blood oxygenation level‐dependent (BOLD) signal power in MDD individuals at baseline. Critically, individuals who responded best to treatment were associated with lower pre‐treatment BOLD power in these regions. Additionally, functional connectivity (FC) in the default mode and affective networks was associated with treatment response. We leveraged these findings to train support vector machines (SVMs) to predict individual treatment responses, based on learned patterns of baseline FC, BOLD signal power and clinical features. Treatment response (responder vs. nonresponder) was predicted with 85–95% accuracy. Reduction in symptoms was predicted to within a mean error of ±16% (r = .68, p < .001). These preliminary findings suggest that therapeutic outcome to DLPFC‐rTMS could be predicted at a clinically meaningful level using only a small number of core neurobiological features of MDD, warranting prospective testing to ascertain generalizability. This provides a novel, transparent and physiologically plausible multivariate approach for classification of individual response to what has become the most commonly employed rTMS treatment worldwide. This study utilizes data from a larger clinical study (Australian New Zealand Clinical Trials Registry: Investigating Predictors of Response to Transcranial Magnetic Stimulation for the Treatment of Depression; ACTRN12610001071011; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=336262).

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“…TMS, a noninvasive alternative, removes the need for device implantation whatsoever and may be a preferred in less severely treatment-resistant patients who are at greater risk for surgical complications. TMS can also be used as a presurgical probe for determination of potential efficacy of an implanted device (23) and aggressive rTMS protocols may be a method for selecting potential responders based off of mechanistic intermediate targets (24). Nevertheless, all of these neuromodulation treatments suffer from the response latency seen with DBS.…”

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confidence: 99%

It takes time to tune

Bentzley

Pannu

Badran

et al. 2017

Annals of Translational Medicine

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In a recent issue of JAMA Psychiatry, Bergfeld et al., report the results of an investigator-initiated trial of bilateral deep brain stimulation (DBS) of the ventral anterior limb of the internal capsule (vALIC) for treatment of treatmentresistant depression (TRD) (1). The results of this trial indicate that DBS of vALIC produces an antidepressant response that slowly accumulates over the course of a year and rapidly dissipates when stimulation is discontinued. This is encouraging and brings hope to patients with a debilitating depression who have exhausted most currently available treatment options. Indeed, the patients selected for this trial were particularly refractory, having failed electroconvulsive therapy (ECT) as well as numerous pharmacotherapeutic approaches, including two selective serotonin reuptake inhibitors, tricyclic antidepressants, monoamine oxidase inhibitors, and lithium augmentation. Despite reports of recently failed industry-sponsored trials of DBS for treatment of TRD (2,3), the medical field has an obligation to continue to investigate potential treatments for this group of severely afflicted patients. Although the results of this trial inspire some hope for an effective treatment for TRD, this hope comes with a caveat of caution driven by two recently failed trials (2,3) as well as several unique aspects of this trial that raise questions of how to move the field of invasive neuromodulation for TRD forward.Perhaps the most striking aspect of this study is the clinical trial design (4). Aside from one notable exception (5), the process of discovering the optimal settings for a new invasive neuromodulation approach in a psychiatric condition can take months to years to mature (3). This latency is likely due to the still cryptogenic mechanism of action of DBS as well as its guess-and-check approach to programing (6). There is no immediate symptom-based feedback parameter currently available for TRD as exists for movement disorders (7), that can be used to determine if the programming changes are likely to be beneficial; thus, each new set of DBS parameters must be tested for several days to weeks before its effect can be determined. In our own experience with determining the optimal programming parameters for treating TRD with epidural prefrontal cortical stimulators (EpCS), a similar implantable technology to DBS stimulators, this onerous and methodical process took years to discover the appropriate stimulation settings that ultimately resulted in remission in 80% of patients (8,9). In the absence of an immediate symptom-based feedback parameter, a randomized clinical trial requires a yearlong (or longer) period during which the comparison between active and sham parallel groups is made. Alternatively, a yearlong open-label lead-in period transitioning to a short sham-controlled cross-over phase, was employed by Bergfeld et al., a design similar to that used in a trial of DBS for treatment of obsessive-compulsive disorder (10). There are several advantages to this later approach. It is m...

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Subgenual Anterior Cingulate–Medial Orbitofrontal Functional Connectivity in Medication-Resistant Major Depression: A Neurobiological Marker for Accelerated Intermittent Theta Burst Stimulation Treatment?

Cited by 53 publications

References 63 publications

Focal application of accelerated iTBS results in global changes in graph measures

Focal application of accelerated iTBS results in global changes in graph measures

A multivariate neuroimaging biomarker of individual outcome to transcranial magnetic stimulation in depression

It takes time to tune

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