PREDICT-ACC: Prediction of REsponse to Depression Interventions (Accelerated rTMS) Using Clinical and TD-fNIRS Measurements
Kernel
Summary
This observational, longitudinal, multi-cohort study aims to evaluate functional brain activity in adults undergoing treatment for Major Depressive Disorder (MDD) at participating clinical sites. A separate cohort of healthy adults will be enrolled as a control group. All data collected in this study are for research purposes only and will not influence clinical decision-making or treatment plans. This study will use TD-fNIRS to measure hemodynamic brain responses at rest and/or during tasks in patients receiving accelerated transcranial magnetic stimulation (TMS). Imaging will occur at multiple timepoints (pre-treatment, post-treatment, and follow-ups). Healthy control participants will complete similar measurements at one visit, with the option for a follow-up visit. The primary objectives are to assess feasibility, characterize brain activity patterns, and explore potential biomarkers associated with treatment response.
Eligibility
- Age range
- 18–75 years
- Sex
- All
- Healthy volunteers
- Yes
Inclusion Criteria for: Accelerated TMS cohort * Adults aged 18-75 at the time of enrollment * Primary diagnosis of MDD as defined by the DSM-5 * Determined by the clinic to be eligible for accelerated rTMS treatment and agrees to receive accelerated rTMS treatment * Agrees to start accelerated rTMS treatment in conjunction with study participation to capture baseline measurements * Has not received rTMS treatment in the past 1 month * Has not received SPRAVATO treatment in the past 1 month * Can speak and understand English * Ability to provide informed consent Healthy controls cohort * A…
Interventions
- OtherfNIRS measurement
Kernel Flow is a non-invasive neuroimaging device that uses time-domain functional near-infrared spectroscopy (TD-fNIRS) to measure changes in cortical hemodynamics associated with brain activity.
Locations (2)
- KernelLos Angeles, California
- Acacia ClinicsSunnyvale, California