Zero and First-Order Phase Shift Correction for Field Map Estimation with Dual-Echo GRE Using Bipolar Gradients

A simple phase error correction technique used for field map estimation with a generally available dual-echo gradient-echo (GRE) sequence is presented. Magnetic field inhomogeneity maps estimated using two separate GRE volume acquisitions at different echo times are prone to dynamic motion errors between acquisitions. By using the dual-echo sequence, the data are collected during two back-to-back readout gradients in opposite polarity after a single radio frequency pulse, and interecho motion artifacts and alignment errors in field map estimation can be factored out. Residual phase error from the asymmetric readout pulses is modeled as an affine term in the readout direction. Results from phantom and human data suggest that the first-order phase correction term stays constant over time and, hence, can be applied to different data acquired with the same protocol over time. The zero-order phase correction term may change with time and is estimated empirically for different scans.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85843/1/Fessler31.pd

Simulation guided design of the MRcollar: a MR compatible applicator for deep heating in the head and neck region

Purpose: To develop a head and neck hyperthermia phased array system compatible with a 1.5 T magnetic resonance (MR) scanner for noninvasive thermometry. Methods: We designed a dielectric-parabolic-reflector antenna (DiPRA) based on a printed reflector backed dipole antenna and studied its predicted and measured performance in a flat configuration (30 mm thick water bolus and muscle equivalent layer). Thereafter, we designed a phased array applicator model (‘MRcollar’) consisting of 12 DiPRA modules placed on a radius of 180 mm. Theoretical heating performance of the MRcollar model was benchmarked against the current clinical applicator (HYPERcollar3D) using specific (3D) head and neck models of 28 treated patients. Lastly, we assessed the influence of the DiPRA modules on MR scanning quality. Results: The predicted and measured reflection coefficients (S11) of the DiPRA module are below −20 dB. The maximum specific absorption rate (SAR) in the area under the antenna was 47% higher than for the antenna without encasing. Compared to the HYPERcollar3D, the MRcollar design incorporates 31% less demineralized water (−2.5 L), improves the predicted TC25 (target volume enclosed by 25% iso-SAR contour) by 4.1% and TC50 by 8.5%, while the target-to-hotspot quotient (THQ) is minimally affected (−1.6%). MR experiments showed that the DiPRA modules do not affect MR transmit/receive performance. Conclusion: Our results suggest that head and neck hyperthermia delivery quality with the MRcollar can be maintained, while facilitating simultaneous noninvasive MR thermometry for treatment monitoring and control

Concurrent Correction of Geometric Distortion and Motion Using the Map-Slice-to-Volume Method in Echo-Planar Imaging

The accuracy of measuring voxel intensity changes between stimulus and rest images in fMRI echo-planar imaging (EPI) data is severely degraded in the presence of head motion. In addition, EPI is sensitive to susceptibility-induced geometric distortions. Head motion causes image shifts and associated field map changes that induce different geometric distortion at different time points. Conventionally, geometric distortion is “corrected” with a static field map independently of image registration. That approach ignores all field map changes induced by head motion. This work evaluates the improved motion correction capability of mapping slice to volume with concurrent iterative field corrected reconstruction using updated field maps derived from an initial static field map that has been spatially transformed and resampled. It accounts for motion-induced field map changes for translational and in-plane rotation motion. The results from simulated EPI time series data, in which motion, image intensity and activation ground truths are available, show improved accuracy in image registration, field corrected image reconstruction and activation detection.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86009/1/Fessler24.pd