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

Pang, Yuxi; Malyarenko, Dariya I.; Amouzandeh, Ghoncheh; Barberi, Enzo A.; Cole, Michael; Endt, Axel vom; Peeters, Johannes M.; Tan, Ek Tsoon; Chenevert, Thomas L.

doi:10.1016/j.ejmp.2021.05.030

Cited by 7 publications

(14 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Once built for a specific gradient system, the corrector maps can be applied retrospectively to the prior DWI scans of an arbitrary object and geometry [7,13]. Analogous to commonly used correction of geometric distortion, the prospective correction of GNL-induced DW bias can also be implemented on-scanner using a gradient system design and DWI scan geometry information [2,14].…”

Section: Discussionmentioning

confidence: 99%

“…When DWI is employed in a multi-center study on multiple platforms, additional variability will confound ADC measurements due to different system-specific spatial GNL patterns [9][10][11][12]. To establish reliable diagnostic thresholds, efforts are underway to correct for this systematic variability either retrospectively via centralized data analysis [11,13] or prospectively, on systems equipped with vendor implementation of GNL bias correction [7,14].…”

Section: Introductionmentioning

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 2 more Smart Citations

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

et al. 2022

Self Cite

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: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…We did not investigate the effect of different equation forms or different fitting algorithms, which could affect the results [ 6 , 10 – 12 ]. Additionally, the intersystem reproducibility of the results may be an issue, as diffusion-weighted imaging (DWI) parameters are known to be dependent on the manufacturer/model of the scanner, sequence implementation, and gradient nonlinearity (GNL) [ 22 – 24 ].…”

Section: Discussionmentioning

confidence: 99%

Perfusion‐Diffusion Ratio: A New IVIM Approach in Differentiating Solid Benign and Malignant Primary Lesions of the Liver

Podgórska

Pasicz

Skrzyński

et al. 2022

BioMed Research International

View full text Add to dashboard Cite

Introduction. In order to improve the efficacy of intravoxel incoherent motion (IVIM) parameters in characterising specific tissues, a new concept is introduced: the perfusion–diffusion ratio (PDR), which expresses the relationship between the signal S b decline rate as a result of IVIM and the rate of signal S b decline due to diffusion. The aim of this study was to investigate this novel approach in the differentiation of solid primary liver lesions. Material and Methods. Eighty-three patients referred for liver MRI between August 2017 and January 2020 with a suspected liver tumour were prospectively examined with the standard liver MRI protocol extended by DWI-IVIM sequence. Patients with no liver lesions, haemangiomas, or metastases were excluded. The final study population consisted of 34 patients with primary solid liver masses, 9 with FNH, 4 with regenerative nodules, 10 with HCC, and 11 with CCC. The PDR coefficient was introduced, defined as the ratio of the rate of signal S b decrease due to the IVIM effect to the rate of signal S b decrease due to the diffusion process, for b = 0 . Results. No significant differences were found between benign and malignant lesions in the case of IVIM parameters ( f , D , or D ∗ ) and ADC. Significant differences were observed only for PDR, with lower values for malignant lesions ( p = 0.03 ). The ROC analysis yielded an AUC value for PDR equal to 0.74, with a cut-off value of 5.06, sensitivity of 81%, specificity of 77%, and accuracy of 79%. Conclusion. PDR proved to be more effective than IVIM parameters and ADC in the differentiation of solid benign and malignant primary liver lesions.

show abstract

“…Furthermore, the conditions of measurement of the Apparent Diffusion Coefficient (ADC) that are most critical are identified. The second by Pang Y. et al [6] describes the empirical validation of a vendor-provided gradient model dedicated to the correction of the ADC measured on a 3T system. Empiric and predicted errors due to gradient non-linearities are shown to be similar for all the considered 3T systems.…”

Section: System Characterizationmentioning

confidence: 99%

New developments in MRI: System characterization, technical advances and radiotherapy applications

Mazzoni¹,

Bock

Levesque

et al. 2021

Physica Medica

View full text Add to dashboard Cite

show abstract

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

Cited by 7 publications

References 30 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

Perfusion‐Diffusion Ratio: A New IVIM Approach in Differentiating Solid Benign and Malignant Primary Lesions of the Liver

New developments in MRI: System characterization, technical advances and radiotherapy applications

Contact Info

Product

Resources

About