Investigation of neuroimaging assessments and current flow modeling as target engagement and predictor biomarkers of convulsive therapies

• Grant number: 22/03266-0
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Effective date (Start): May 01, 2022
• Effective date (End): April 30, 2025
• Field of knowledge: Health Sciences - Medicine - Psychiatry
• Principal Investigator: Andre Russowsky Brunoni
• Grantee: Pedro Henrique Rodrigues da Silva
• Host Institution: Hospital Universitário (HU). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated research grant: 19/06009-6 - Non-implantable neuromodulation therapies: a perspective for the depressed brain, AP.TEM
• Associated scholarship(s): 23/13893-5 - Disentangling the functional neurobiological effects of electroconvulsive therapy in major depression disorder: a resting-state functional MRI study, BE.EP.PD

Abstract

Depressed patients have volumetric reductions of the hippocampus, amygdala, prefrontal, Anterior Cingulate Cortices (ACC), and basal ganglia. Moreover, a metabolic decrease in dorsolateral prefrontal cortex (DLPFC) associated with increased activity in the cingulate cortex and limbic regions is observed. The white matter involved in implicit emotional regulation and reward processing neural circuits include the corpus callosum, anterior cingulum, uncinate fascicle, and superior longitudinal fascicle. Regarding functional connectivity, the Default-Mode Network (DMN) is the most studied network in depression, in which hyperactivity is generally observed, usually centered in the ACC, which has been critically involved in depression pathophysiology. Convulsive therapies can induce brain structural changes, particularly bilateral hippocampal volumetric enlargement. However, whether such changes persist in the long-term has not been sufficiently explored. Volumetric enlargement of the amygdala, anterior cingulate cortex, and basal nuclei have also been described. Such changes may predict a positive response to ECT. Moreover, increases in fractional anisotropy and decreased mean diffusivity in white matter of the frontal and temporal lobes have been observed. These changes indicate increasing white matter integrity (ie, greater structural connectivity). Regarding functional brain parameters, a study showed that the regional neural activity of the subcallosal cingulate cortex was a predictor of ECT response, and also functional resting state connectivity between the DLPFC and the default mode network. In addition, a novel modality to assess the effects of neuromodulatory interventions, electrical field modeling of brain circuits based on individualized Magnetic Resonance Imaging (MRI), showed that this parameter can predict structural brain changes. Despite these initial findings, there is limited understanding of neural circuitry underlying treatment-associated antidepressant and cognitive effects of convulsive therapies. MRI images can be used to measure phenotypic variations in specific brain circuits that are a unique representation of the interaction between genes and environment and are associated with specific behavioral changes. However, most studies analyzing these biomarkers in ECT studies used only one MRI modality. The use of a combination of several MRI parameters sensitive to complementary tissue characteristics (multimodal MRI) may support the construction of more accurate endophenotypes, that, together with clinical features, will aid in identifying ECT responders, which could consequently allow to increase treatment effectiveness and reduce adverse effects. In addition, by comparing the effects of Electroconvulsive Therapy (ECT) with Magnetic Seizure Therapy (MST), we hope to better elucidate the function of brain changes observed in previous studies, such as hippocampal volumetric changes and their relation to the clinical outcomes of ECT. To this end, we will perform MRI scans at baseline and endpoint in a randomized clinical trial comparing the efficacy of bilateral ECT vs. MST in 100 treatment-resistant depressed patients. (AU)