closed-loop-neurostimulation-for-biomarker-driven-personalized

Closed-Loop Neurostimulation for Biomarker-Driven, Personalized Treatment of Major Depressive Disorder

Deep brain stimulation involves the administration of electrical stimulation to targeted brain regions for therapeutic benefit. In the context of major ...

University of California, San Francisco

Psoriasis is the most common chronic inflammatory condition involving the T helper cell system. Population studies have demonstrated that patients with psoriasis and/or psoriatic arthritis have an increased risk of developing vascular risk factors, including diabetes, hypertension, and obesity, and increased risk of adverse vascular events, including myocardial infarction and stroke. Population studies have generally investigated the individual contributions of psoriasis and psoriatic arthritis to development of vascular risk factors; fewer studies have investigated the additive contribution of comorbid inflammatory disorders. We present a case of a woman with psoriasis, psoriatic arthritis, and comorbid vascular risk factors.

Catastrophic stroke burden in a patient with uncontrolled psoriasis and psoriatic arthritis: a case report.

Status epilepticus (SE) is a neurologic emergency requiring immediate time-sensitive treatment to minimize neuronal injury and systemic complications. Minimizing time to administration of first- and second-line therapy is necessary to optimize the chances of successful seizure termination in generalized convulsive SE (GCSE). The approach to refractory and superrefractory GCSE is less well defined. Multiple agents with differing complementary actions that facilitate seizure termination are recommended. Nonconvulsive SE (NCSE) has a wide range of presentations and approaches to treatment. Continuous electroencephalography is critical to the management of both GCSE and NCSE, while its use for patients without seizure continues to expand.

Management of Status Epilepticus and Indications for Inpatient Electroencephalography Monitoring.

Responsive neurostimulation is a promising treatment for drug-resistant focal epilepsy; however, clinical outcomes are highly variable across individuals. The therapeutic mechanism of responsive neurostimulation likely involves modulatory effects on brain networks; however, with no known biomarkers that predict clinical response, patient selection remains empiric. This study aimed to determine whether functional brain connectivity measured non-invasively prior to device implantation predicts clinical response to responsive neurostimulation therapy. Resting-state magnetoencephalography was obtained in 31 participants with subsequent responsive neurostimulation device implantation between 15 August 2014 and 1 October 2020. Functional connectivity was computed across multiple spatial scales (global, hemispheric, and lobar) using pre-implantation magnetoencephalography and normalized to maps of healthy controls. Normalized functional connectivity was investigated as a predictor of clinical response, defined as percent change in self-reported seizure frequency in the most recent year of clinic visits relative to pre-responsive neurostimulation baseline. Area under the receiver operating characteristic curve quantified the performance of functional connectivity in predicting responders (≥50% reduction in seizure frequency) and non-responders (<50%). Leave-one-out cross-validation was furthermore performed to characterize model performance. The relationship between seizure frequency reduction and frequency-specific functional connectivity was further assessed as a continuous measure. Across participants, stimulation was enabled for a median duration of 52.2 (interquartile range, 27.0-62.3) months. Demographics, seizure characteristics, and responsive neurostimulation lead configurations were matched across 22 responders and 9 non-responders. Global functional connectivity in the alpha and beta bands were lower in non-responders as compared with responders (alpha, p < 0.001; beta, p < 0.001). The classification of responsive neurostimulation outcome was improved by combining feature inputs; the best model incorporated four features (i.e. mean and dispersion of alpha and beta bands) and yielded an area under the receiver operating characteristic curve of 0.970 (0.919-1.00). The leave-one-out cross-validation analysis of this four-feature model yielded a sensitivity of 86.3%, specificity of 77.8%, positive predictive value of 90.5%, and negative predictive value of 70%. Global functional connectivity in alpha band correlated with seizure frequency reduction (alpha,  = 0.010). Global functional connectivity predicted responder status more strongly, as compared with hemispheric predictors. Lobar functional connectivity was not a predictor. These findings suggest that non-invasive functional connectivity may be a candidate personalized biomarker that has the potential to predict responsive neurostimulation effectiveness and to identify patients most likely to benefit from responsive neurostimulation therapy. Follow-up large-cohort, prospective studies are required to validate this biomarker. These findings furthermore support an emerging view that the therapeutic mechanism of responsive neurostimulation involves network-level effects in the brain.

Network connectivity predicts effectiveness of responsive neurostimulation in focal epilepsy.

Epileptiform discharges triggered with direct electrical stimulation for treatment-resistant depression: Factors that modulate risk and treatment considerations.

Humans routinely shift their sleepiness and wakefulness levels in response to emotional factors. The diversity of emotional factors that modulates sleep-wake levels suggests that the ascending arousal network may be intimately linked with networks that mediate mood. Indeed, while animal studies have identified select limbic structures that play a role in sleep-wake regulation, the breadth of corticolimbic structures that directly modulates arousal in humans remains unknown.

Joline M. Fan

Weill Institute for Neurosciences,
Department of Neurology

University of California, San Francisco

Closed-Loop Neurostimulation for Biomarker-Driven, Personalized Treatment of Major Depressive Disorder

Joline M. Fan

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Weill Institute for Neurosciences,Department of Neurology

University of California, San Francisco

Closed-Loop Neurostimulation for Biomarker-Driven, Personalized Treatment of Major Depressive Disorder

Weill Institute for Neurosciences,
Department of Neurology