Abstract
The study aims to test the long-term stability of gradient characteristics for model-based correction of diffusion weighting (DW) bias in an apparent diffusion coefficient (ADC) for multisite imaging trials. Single spin echo (SSE) DWI of a long-tube ice-water phantom was acquired quarterly on six MR scanners over two years for individual diffusion gradient channels, along with mapping, as a function of right-left (RL) and superior-inferior (SI) offsets from the isocenter. Additional double spin-echo (DSE) DWI was performed on two systems. The offset dependences of derived ADC were fit to 4th-order polynomials. Chronic shim gradients were measured from spatial derivatives of maps along the tube direction. Gradient nonlinearity (GNL) was modeled using vendor-provided gradient field descriptions. Deviations were quantified by root-mean-square differences (RMSD), normalized to reference ice-water ADC, between the model and reference (), measurement and model (), and temporal measurement variations (). Average was 4.9 ± 3.2 (%RL) and –14.8 ± 3.8 (%SI), and threefold larger than . was close to measurement errors (~3%). GNL-induced bias across gradient systems varied up to 20%, while deviation from the model accounted at most for 6.5%, and temporal variation for less than 3% of ADC reproducibility error. Higher SSE = 7.5–11% was reduced to 2.5–4.8% by DSE, consistent with the eddy current origin. Measured chronic shim gradients below 0.1 mT/m had a minor contribution to ADC bias. The demonstrated long-term stability of spatial ADC profiles and consistency with system GNL models justifies retrospective and prospective DW bias correction based on system gradient design models. Residual errors due to eddy currents and shim gradients should be corrected independent of GNL.
Highlights
In clinical MR diffusion weighed imaging (DWI), gradient nonlinearity (GNL) leads to spatially varying diffusion weighting [1] that causes predictable systematic errors or biases in derived metrics, such as an apparent diffusion coefficient (ADC) [2,3], a promising quantitative biomarker for cancer therapy response and diagnosis [4,5,6]
ADC is calculated based on a mono-exponential decay model for a DWI signal with increasing diffusion weighting quantified by the b-value
Gradient channel-specific ADC deviations from the reference value were largely consistent with the static GNL model that well exceeded temporal variations for all scanners
Summary
In clinical MR diffusion weighed imaging (DWI), gradient nonlinearity (GNL) leads to spatially varying diffusion weighting [1] that causes predictable systematic errors or biases in derived metrics, such as an apparent diffusion coefficient (ADC) [2,3], a promising quantitative biomarker for cancer therapy response and diagnosis [4,5,6]. To confirm feasibility of model-based GNL correction for both retrospective and prospective applications over arbitrary FOV in a multi-center, multi-scanner setting, our team has designed long-term DWI quality control studies using a quantitative ice-water diffusion phantom [18]. This phantom was scanned quarterly over two years on multiple representative clinical gradient platforms within typical body DWI FOV [5,6,8]. The described studies were performed in collaboration with three key MRI vendors, the participants of an academic industrial partnership (AIP)
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
