Mitigation of peripheral nerve stimulation (PNS) in MRI

Massachusetts General Hospital, Boston MA

Investigators

Linked publications & trials

Abstract

Project Summary/Abstract Peripheral nerve stimulation (PNS) is the stimulation of motor and sensory nerves in the body by electric fields induced by the rapid switching of MRI gradient coils. Until recently PNS was considered an unavoidable effect of the MRI imaging process. This is problematic for clinical MRI because PNS dramatically restricts the parameter space of common imaging sequences (TR, TE, ESP etc…) thus resulting in degraded image quality and inefficient acquisition times. PNS is especially constraining for fast ‘turbo’ sequences that have become ubiquitous in clinics, such as stead-state free precession (cardiac), diffusion weighted imaging (neuro), turbo spin echo (cardiac/neuro/pelvis/knee) and fluid attenuated inversion recovery (cardiac/neuro/pelvis/knee), just to name a few. In the previous funding cycle, we developed, validated and disseminated electromagnetic and neurophysiological modeling tools allowing to predict PNS thresholds in absolute unit (mT/m). We then proposed PNS mitigation methods yielding gradient coils with intrinsically low PNS propensity. Despite these successes, there are several barriers to clinical translation of our gradient designs. A first challenge is the generation of coils that perform well for all body habitus (we currently consider only two body models) and all imaging landmarks (we currently consider one landmark per optimization). Another challenge is that of accurate real-time PNS monitoring as the patient is being scanned. Indeed, the state-of-the-art PNS monitor, SAFE, does not model the variation of PNS response across different landmarks, nor E-field interactions across gradient axes that occurs in oblique MRI acquisitions. As a result, using SAFE for PNS monitoring does not allow using the full performance capabilities of our PNS-optimized systems, and in general is poorly adapted to PNS control in all high-performance systems. In this renewal, we design gradient coils with robust PNS performance across all body habitus, imaging landmarks and develop accurate PNS monitor models that allow using the full performance capabilities of high-performance gradient systems, including our PNS-optimized designs. In the last Aim, we build gradient coil prototypes to validate our PNS predictions in healthy subjects. A key deliverable of this project is the dissemination of gradient design and monitoring tools that fully address PNS in MRI and can be readily translated to industry and clinics. We work closely with academic, industry (Siemens, GE) and regulatory partners (IEC, FDA) throughout the project to ensure translation.