Correction of Gradient Nonlinearity Bias in Quantitative Diffusion Parameters of Renal Tissue with Intra Voxel Incoherent Motion.

Dariya I Malyarenko,Marko K Ivancevic,Brian D Ross,Julien Senegas,Thomas L Chenevert,Yuxi Pang

doi:10.18383/j.tom.2015.00160

Abstract

Spatially nonuniform diffusion weighting bias as a result of gradient nonlinearity (GNL) causes substantial errors in apparent diffusion coefficient (ADC) maps for anatomical regions imaged distant from the magnet isocenter. Our previously described approach effectively removed spatial ADC bias from 3 orthogonal diffusion-weighted imaging (DWI) measurements for monoexponential media of arbitrary anisotropy. This work evaluates correction feasibility and performance for quantitative diffusion parameters of the 2-component intravoxel incoherent motion (IVIM) model for well-perfused and nearly isotropic renal tissue. Sagittal kidney DWI scans of a volunteer were performed on a clinical 3T magnetic resonance imaging scanner near isocenter and offset superiorly. Spatially nonuniform diffusion weighting caused by GNL resulted both in shifting and broadening of perfusion-suppressed ADC histograms for off-center DWI relative to unbiased measurements close to the isocenter. Direction-average diffusion weighting bias correctors were computed based on the known gradient design provided by the vendor. The computed bias maps were empirically confirmed by coronal DWI measurements for an isotropic gel-flood phantom. Both phantom and renal tissue ADC bias for off-center measurements was effectively removed by applying precomputed 3D correction maps. Comparable ADC accuracy was achieved for corrections of both b maps and DWI intensities in the presence of IVIM perfusion. No significant bias impact was observed for the IVIM perfusion fraction.

Highlights

Recent multicenter oncology trials have evaluated quantitative diffusion-weighted imaging (DWI) as a radiological marker of tumor malignancy and response to therapy [1,2,3]
Within a relatively large regions of interest (ROIs) (220 ϫ 240 mm2), such nonuniformity resulted in artificial broadening of the apparent diffusion coefficient (ADC) histogram that was accompanied by a shift of the mean ADC value (Figure 1B)
The observed ADC bias (Figure 1A), normalized to the isocenter reference value, agreed with the predicted by gradient nonlinearity (GNL) model for the scanner, with ROI pixel-by-pixel difference falling within 3%

Summary

Introduction

Recent multicenter oncology trials have evaluated quantitative diffusion-weighted imaging (DWI) as a radiological marker of tumor malignancy and response to therapy [1,2,3]. In clinical applications outside of the brain, tissues with low fractional anisotropy are typically assessed by combining 3 orthogonal DWI acquisitions as a function of diffusion gradient weighting, quantified by a b-value to provide a mean diffusivity measure of the tissue. The default measure of mean diffusivity in current clinical trials is the apparent diffusion coefficient (ADC), which assumes monoexponential signal decay with increasing b-values [4, 9,10,11]. For IVIM, the typically derived metrics include perfusion-suppressed ADC values and perfusion fraction. Characterization and minimization of technical errors in diffusion metrics is imperative for standardizing DWI measurements so that meaningful and consistent clinical trial results can be obtained to further establish the diagnostic and clinical response value of DWI-derived biomarkers [14, 15]

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Conclusion