A simple geometric analysis method for measuring and mitigating RF induced currents on Deep Brain Stimulation leads...

The purpose of this work is to present a new method that can be used to estimate and mitigate RF induced currents on Deep Brain Stimulation (DBS) leads. Here, we demonstrate the effect of RF induced current mitigation on both RF heating and image quality for a variety of brain MRI sequences at 3 T. We acquired pre-scan images around a DBS lead (in-situ and ex-vivo) using conventional Gradient Echo Sequence (GRE) accelerated by parallel imaging (i.e GRAPPA) and quantified the magnitude and phase of RF induced current using the relative location of the B1+ null with respect to the lead position. We estimated the RF induced current on a DBS lead implanted in a gel phantom as well as in a cadaver head study for a variety of RF excitation patterns. We also measured the increase in tip temperature using fiber-optic probes for both phantom and cadaver studies. Using the magnitude and phase information of the current induced separately by two transmit channels of the body coil, we calculated an implant friendly (IF) excitation. Using the IF excitation, we acquired T1, T2 weighted Turbo Spin Echo (TSE), T2 weighted SPACE-Dark Fluid, and Ultra Short Echo Time (UTE) sequences around the lead. Our induced current estimation demonstrated linear relationship between the magnitude of the induced current and the square root SAR at the tip of the lead as measured in phantom studies. The "IF excitation pattern" calculated after the pre-scan mitigated RF artifacts and increased the image quality around the lead. In addition, it reduced the tip temperature significantly in both phantom and cadaver studies compared to a conventional quadrature excitation while keeping equivalent overall image quality. We present a relatively fast method that can be used to calculate implant friendly excitation, reducing image artifacts as well as the temperature around the DBS electrodes. When combined with a variety of MR sequences, the proposed method can improve the image quality and patient safety in clinical imaging scenarios.