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.
