A practical framework for large-scale neuroimaging data collection in clinically diverse populations: experience from the Stanford Brain Stimulation Lab

Novel neuroimaging technologies and data science techniques have allowed for large-scale applications of neuroimaging acquisition in clinical research, particularly within the fields of interventional psychiatry, neuropsychiatry, and precision medicine. These developments have enhanced our understanding of psychiatric and neurological disorders and highlight the need for optimized protocols that support scalable, high-quality neuroimaging data acquisition. This paper aims to describe a protocol for systematic MRI data collection in clinical trials, including details for subject recruitment, meticulous equipment calibration, rigorous real-time quality control of imaging data, standardized documentation (SOP, hardware and software logs), consent workflows, and personnel training. While existing MRI review papers largely focus on analytical methods, safety protocols, and results of large consortium efforts, few publications detail specific operational protocols of MRI data collection that allow for consistent, high-impact neuroimaging research including participant recruitment, staff training, and practical scanning considerations. The operational protocols presented here are designed to facilitate reproducible, high-quality neuroimaging acquisition across clinically diverse populations, with a particular focus on functional MRI. Importantly, many of the recommendations described are grounded in practical experience rather than prescriptive guidelines alone. They represent lessons learned through years of iterative refinement, troubleshooting, and trial-and-error while conducting thousands of MRI scans in clinical research settings. By sharing these operational insights, we hope to provide researchers with practical strategies that can reduce common challenges and accelerate the development of robust neuroimaging workflows.