Empirical validation of gradient field models for an accurate ADC measured on clinical 3T MR systems in body oncologic applications.

PURPOSE: To empirically corroborate vendor-provided gradient nonlinearity (GNL) characteristics and demonstrate efficient GNL bias correction for human brain apparent diffusion coefficient (ADC) across 3T MR systems and spatial locations. METHODS: Spatial distortion vector fields (DVF) were mapped in 3D using a surface fiducial array phantom for individual gradient channels on three 3T MR platforms from different vendors. Measured DVF were converted into empirical 3D GNL tensors and compared with their theoretical counterparts derived from vendor-provided spherical harmonic (SPH) coefficients. To illustrate spatial impact of GNL on ADC, diffusion weighted imaging using three orthogonal gradient directions was performed on a volunteer brain positioned at isocenter (as a reference) and offset superiorly by 10-17 cm (>10% predicted GNL bias). The SPH tensor-based GNL correction was applied to individual DWI gradient directions, and derived ADC was compared with low-bias reference for human brain white matter (WM) ROIs. RESULTS: Empiric and predicted GNL errors were comparable for all three studied 3T MR systems, with <1.0% differences in the median and width of spatial histograms for individual GNL tensor elements. Median (±width) of ADC (10-3mm2/s) histograms measured at isocenter in WM reference ROIs from three MR systems were: 0.73 ± 0.11, 0.71 ± 0.14, 0.74 ± 0.17, and at off-isocenters (before versus after GNL correction) were respectively 0.63 ± 0.14 versus 0.72 ± 0.11, 0.53 ± 0.16 versus 0.74 ± 0.18, and 0.65 ± 0.16 versus 0.76 ± 0.18. CONCLUSION: The phantom-based spatial distortion measurements validated vendor-provided gradient fields, and accurate WM ADC was recovered regardless of spatial locations and clinical MR platforms using system-specific tensor-based GNL correction for routine DWI.

A phantom based laser marking workflow to visually assess geometric image distortion in magnetic resonance guided radiotherapy.

Magnetic resonance (MR)-only workflows require quality assurance due to potential dosimetric impacts of using geometry distorted MR images in radiotherapy planning. MR-visible silicone-based fiducials were arranged in regular 3D structures to cover extended imaging volumes. The scanner's patient marking workflow with a 2-axes movable laser bridge allowed to visually check geometric distortions of each MR reconstructed fiducial against its true position in 3D space. A measurement resolution and uncertainty of the order of 0.5 mm in sagittal and coronal, and 1 mm in transversal direction was found. The proposed workflow required 1 min of evaluation time per fiducial position, and a 9 min 3D MR volume acquisition.

Retrospective Correction of ADC for Gradient Nonlinearity Errors in Multicenter Breast DWI Trials: ACRIN6698 Multiplatform Feasibility Study.

The presented analysis of multisite, multiplatform clinical oncology trial data sought to enhance quantitative utility of the apparent diffusion coefficient (ADC) metric, derived from diffusion-weighted magnetic resonance imaging, by reducing technical interplatform variability owing to systematic gradient nonlinearity (GNL). This study tested the feasibility and effectiveness of a retrospective GNL correction (GNC) implementation for quantitative quality control phantom data, as well as in a representative subset of 60 subjects from the ACRIN 6698 breast cancer therapy response trial who were scanned on 6 different gradient systems. The GNL ADC correction based on a previously developed formalism was applied to trace-DWI using system-specific gradient-channel fields derived from vendor-provided spherical harmonic tables. For quantitative DWI phantom images acquired in typical breast imaging positions, the GNC improved interplatform accuracy from a median of 6% down to 0.5% and reproducibility of 11% down to 2.5%. Across studied trial subjects, GNC increased low ADC (<1 µm2/ms) tumor volume by 16% and histogram percentiles by 5%-8%, uniformly shifting percentile-dependent ADC thresholds by ∼0.06 µm2/ms. This feasibility study lays the grounds for retrospective GNC implementation in multiplatform clinical imaging trials to improve accuracy and reproducibility of ADC metrics used for breast cancer treatment response prediction.

Prediction of peripheral nerve stimulation thresholds of MRI gradient coils using coupled electromagnetic and neurodynamic simulations.

PURPOSE: As gradient performance increases, peripheral nerve stimulation (PNS) is becoming a significant constraint for fast MRI. Despite its impact, PNS is not directly included in the coil design process. Instead, the PNS characteristics of a gradient are assessed on healthy subjects after prototype construction. We attempt to develop a tool to inform coil design by predicting the PNS thresholds and activation locations in the human body using electromagnetic field simulations coupled to a neurodynamic model. We validate the approach by comparing simulated and experimentally determined thresholds for 3 gradient coils. METHODS: We first compute the electric field induced by the switching fields within a detailed electromagnetic body model, which includes a detailed atlas of peripheral nerves. We then calculate potential changes along the nerves and evaluate their response using a neurodynamic model. Both a male and female body model are used to study 2 body gradients and 1 head gradient. RESULTS: There was good agreement between the average simulated thresholds of the male and female models with the experimental average (normalized root-mean-square error: <10% and <5% in most cases). The simulation could also interrogate thresholds above those accessible by the experimental setup and allowed identification of the site of stimulation. CONCLUSIONS: Our simulation framework allows accurate prediction of gradient coil PNS thresholds and provides detailed information on location and "next nerve" thresholds that are not available experimentally. As such, we hope that PNS simulations can have a potential role in the design phase of high performance MRI gradient coils.