Dynamic platform for magnetic resonance imaging of bioresponsive contrast agents

Abstract

Magnetic Resonance Imaging (MRI) is a powerful non-invasive imaging modality with unlimited penetration depth, conventionally used for visualization of anatomical details. In efforts to better understand our bodies, there is an increasing interest to image chemical signatures in living systems with MRI. Research efforts have worked to overcome limitations of conventional MRI approaches, such as utilizing MRI contrast agents (CA) to improve molecular sensitivity and developing fast, quantitative methods with future potential for in vivo chemical imaging.Our research has focused on the optimization of a protocol to evaluate MRI CA, including hardware, experiment design, MRI data acquisition, and analysis. Here we proposed a reliable method for imaging small volume contrast agents in preclinical MRI scanners via a Microliter Scale Concentric (MiSCo) testbed as a hardware upgrade. We also demonstrated the success of MiSCo testbed to characterize pH-responsive MRI CA and help plan for translation towards ex vivo experiments in a rat brain model. To acquire dynamic data, we have engineered a Spiral Acquisition Matching Based Algorithm (SAMBA) for fast, quantitative preclinical imaging at low field strength (3T). Although spiral acquisitions and matching based algorithms are not novel, this work demonstrated how quantitative T1 and T2 spiral sequences paired with a dictionary matching-based algorithm provided in vitro results comparable to conventional approaches in a fraction of the scanning time. In addition, the insensitivity to motion artifacts characteristic of fingerprinting-like matching-based algorithms, demonstrated by Ma et al (2013), sets the stage for future in vivo work. This proposed platform for preclinical implementation serves as a foundation to image biochemical analytes in live animals in the near future, with the ultimate objective of unlocking the potential of MRI for chemical imaging of living systems.