Abstract Clinicians rely on neuroimaging to visualize life-changing diseases affecting the brain. Current techniques struggle in areas important for neuroimaging such as quantifying cerebrovascular disease, detecting diseases of inflammation, and monitoring newly developed cell-based therapies. This is due to fundamental technical limitations in MRI, CT, and nuclear medicine. For example, CT perfusion imaging suffers from intrinsically poor signal-to-noise ratio (SNR), which translates to low image resolution and poor quantification that prevents identification of smaller strokes and vasospasms. A new clinical modality that provides fundamentally new information would present new opportunities for medicine. Magnetic Particle Imaging (MPI) is an emerging tracer imaging technology that excels at detecting functional measures such as perfusion. The MPI technique directly images superparamagnetic iron oxide (SPIO) tracers by measuring their time-varying magnetization in response to safe, low-frequency magnetic fields. MPI images are direct views of tracer distribution with no signal arising from tissue, no perturbations from materials such as air, and image intensity that is directly linear with tracer concentration. This ?hot-spot? contrast provides spatial localization and quantification without ambiguity. In clinical neuroimaging, MPI can be used for real-time quantitative perfusion imaging, measurement of cerebrovascular reserve, and assessing vessel lumen diameters. MPI excels at measuring dynamic contrast enhancement and enhanced permeability and retention in tumors, and MPI's properties are near-ideal for cell tracking. In Phase I we explored multiple clinical magnet designs, estimated system cost, developed a manufacturing plan, and manufactured a small-scale preclinical system. In Phase II, we propose building the first human MPI imager. We will build the main magnet, characterize its magnetic performance, integrate all necessary support systems (shielding, RF transmit and receive, magnet control systems, etc.), characterizing the imager with phantoms, and finally evaluate with animal cadavers.