Mapping gradient nonlinearity and miscalibration using diffusion‐weighted MR images of a uniform isotropic phantom

Barnett, Alan S.; İrfanoğlu, M. Okan; Landman, Bennett A.; Rogers, Baxter P.; Pierpaoli, Carlo

doi:10.1002/mrm.28890

Cited by 10 publications

(17 citation statements)

References 33 publications

(55 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Consistent with previous observations [10,12,17,19], uncorrected DW nonuniformity led to substantial errors both in absolute ADC values at offset locations and technical cross-system variability. One poorly performing gradient system that exhibited excessive measurement errors was not used for clinical trials but was included in this study for completeness.…”

Section: Discussionsupporting

confidence: 90%

“…The cross-channel gradient contributions along sampled locations were inherently small due to spatial GNL symmetry [1,15], preventing reliable measurements. Other work using alternative phantoms and extensive 3D GNL mapping methods [14,17] have confirmed high consistency with the gradient model designs over moderate FOV. The current study workflow was chosen for an effective evaluation of temporal stability and relative static contribution of GNL and non-GNL bias sources over large FOV typical of body DWI.…”

Section: Discussionmentioning

confidence: 63%

“…The ice-water provided universal reference ADC standard for evaluation of cross-system reproducibility, independent of the scanner room temperature. To complement previous phantom studies of the spatial ADC bias [10,12,17,19], this work included long-term longitudinal measurements to test the static character of the GNL relative to temporal variability and non-GNL bias sources over a large FOV typical for a range of body ADC applications [5,6,8]. The GNL models were provided by the MR vendors, the participants of the AIP.…”

Section: Discussionmentioning

confidence: 99%

“…The most practical correction of GNL-induced b-value bias would be to use scannerspecific gradient design information [1][2][3] in analogy to the current mitigation of geometric image distortions [15,16]. This approach relies on the assumption of high consistency between the static gradient system model and the observed biases, e.g., recently shown for several gradient systems over moderate (cranial) FOV [14,17]. 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].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Long-Term Stability of Gradient Characteristics Warrants Model-Based Correction of Diffusion Weighting Bias

et al. 2022

View full text Add to dashboard Cite

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 B0 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 B0 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 (RMSDREF), measurement and model (RMSDEXP), and temporal measurement variations (RMSDTMP). Average RMSDREF was 4.9 ± 3.2 (%RL) and –14.8 ± 3.8 (%SI), and threefold larger than RMSDEXP. RMSDTMP 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 RMSDEXP = 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.

show abstract

Section: Discussionsupporting

confidence: 90%

Section: Discussionmentioning

confidence: 63%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Long-Term Stability of Gradient Characteristics Warrants Model-Based Correction of Diffusion Weighting Bias

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Multiple studies of bias/repeatability/reproducibility of ADC on clinical MRIs using DWI phantoms are available [ 22 , 23 , 24 , 25 , 26 ]. Spatial nonuniformity of ADC as a function of x–y offset, as well as z-location on clinical scanners, has been studied using specialized phantoms and procedures [ 43 , 44 , 45 , 46 ] within FOVs much larger than typical for preclinical scanners. In our study, we limited ADC nonuniformity measurements to small offsets (±25 mm) relevant for mouse DWI along the bore axis (z-direction), since this typically is the most nonuniform direction on clinical scanners, as predicted by horizontal bore gradient coil design specifications [ 42 , 43 , 44 , 45 ].…”

Section: Discussionmentioning

confidence: 99%

Evaluation of Apparent Diffusion Coefficient Repeatability and Reproducibility for Preclinical MRIs Using Standardized Procedures and a Diffusion-Weighted Imaging Phantom

et al. 2023

View full text Add to dashboard Cite

Relevant to co-clinical trials, the goal of this work was to assess repeatability, reproducibility, and bias of the apparent diffusion coefficient (ADC) for preclinical MRIs using standardized procedures for comparison to performance of clinical MRIs. A temperature-controlled phantom provided an absolute reference standard to measure spatial uniformity of these performance metrics. Seven institutions participated in the study, wherein diffusion-weighted imaging (DWI) data were acquired over multiple days on 10 preclinical scanners, from 3 vendors, at 6 field strengths. Centralized versus site-based analysis was compared to illustrate incremental variance due to processing workflow. At magnet isocenter, short-term (intra-exam) and long-term (multiday) repeatability were excellent at within-system coefficient of variance, wCV [±CI] = 0.73% [0.54%, 1.12%] and 1.26% [0.94%, 1.89%], respectively. The cross-system reproducibility coefficient, RDC [±CI] = 0.188 [0.129, 0.343] µm2/ms, corresponded to 17% [12%, 31%] relative to the reference standard. Absolute bias at isocenter was low (within 4%) for 8 of 10 systems, whereas two high-bias (>10%) scanners were primary contributors to the relatively high RDC. Significant additional variance (>2%) due to site-specific analysis was observed for 2 of 10 systems. Base-level technical bias, repeatability, reproducibility, and spatial uniformity patterns were consistent with human MRIs (scaled for bore size). Well-calibrated preclinical MRI systems are capable of highly repeatable and reproducible ADC measurements.

show abstract

Diffusion‐Weighted Imaging of the Abdomen: Correction for Gradient Nonlinearity Bias in Apparent Diffusion Coefficient

Wang

Yang

et al. 2022

Magnetic Resonance Imaging

View full text Add to dashboard Cite

Background Gradient nonlinearity (GNL) introduces spatial nonuniformity bias in apparent diffusion coefficient (ADC) measurements, especially at large offsets from the magnet isocenter. Purpose To investigate the effects of GNL in abdominal ADC measurements and to develop an ADC bias correction procedure. Study Type Retrospective. Phantom/Population Two homemade ultrapure water phantoms/25 patients with histologically confirmed pancreatic ductal adenocarcinoma (PDAC). Field Strength/Sequence A 3.0 T/diffusion‐weighted imaging (DWI) with single‐shot echo‐planar imaging sequence. Assessment ADC bias was computed in the three orthogonal directions at different offset locations. The spatial‐dependent correctors of ADC bias were generated from the ADCs of phantom 1. The ADCs were estimated before and after corrections for the phantom 1 with both the proposed approach and the theoretical GNL correction method. For the patients, ADCs were measured in abdominal tissues including left and right liver lobes, PDAC, spleen, bilateral kidneys, and bilateral paraspinal muscles. Statistical Test Friedman tests and Wilcoxon tests. Results The ADC bias measured by phantom 1 was 9.7% and 12.6% higher in the right–left and anterior–posterior directions and 9.2% lower in the superior–inferior direction at the 150 mm offsets from the magnetic isocenter. The corrected vs. the uncorrected ADCs measurements (median: 2.20 × 10−3 mm2/sec for both the proposed method and the theoretical GNL method vs. 2.31 × 10−3 mm2/sec, respectively) and their relative ADC errors (0.014, 0.016, and 0.054, respectively) were lower in the phantom 1. The relative ADC errors substantially decreased after correction in the phantom 2 (median: 0.048 and −0.008, respectively). The ADCs of all the abdominal tissues were lower after correction except for the left liver lobes (P = 0.13). Data Conclusion GNL bias in abdominal ADC can be measured by a DWI phantom. The proposed correction procedure was successfully applied for the bias correction in abdominal ADC. Evidence Level 3. Technical Efficacy Stage 1.

show abstract

Mapping gradient nonlinearity and miscalibration using diffusion‐weighted MR images of a uniform isotropic phantom

Abstract: This is an open access article under the terms of the Creat ive Commo ns Attri butio n-NonCo mmerc ial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Cited by 10 publications

References 33 publications

Long-Term Stability of Gradient Characteristics Warrants Model-Based Correction of Diffusion Weighting Bias

Long-Term Stability of Gradient Characteristics Warrants Model-Based Correction of Diffusion Weighting Bias

Evaluation of Apparent Diffusion Coefficient Repeatability and Reproducibility for Preclinical MRIs Using Standardized Procedures and a Diffusion-Weighted Imaging Phantom

Diffusion‐Weighted Imaging of the Abdomen: Correction for Gradient Nonlinearity Bias in Apparent Diffusion Coefficient

Contact Info

Product

Resources

About