Proton density fat fraction estimated by using chemical shift–encoded MRI in a commercial phantom was accurate across vendors, imaging centers, and two magnetic field strengths, with use of two com... Background Proton density fat fraction (PDFF) estimated by using chemical shift–encoded (CSE) MRI is an accepted imaging biomarker of hepatic steatosis. This work aims to promote standardized use o...

Purpose: Characterize system‐specific bias across common magnetic resonance imaging (MRI) platforms for quantitative diffusion measurements in multicenter trials.Methods: Diffusion weighted imaging (DWI) was performed on an ice‐water phantom along the superior–inferior (SI) and right–left (RL) orientations spanning ±150 mm. The same scanning protocol was implemented on 14 MRI systems at seven imaging centers. The bias was estimated as a deviation of measured from known apparent diffusion coefficient (ADC) along individual DWI directions. The relative contributions of gradient nonlinearity, shim errors, imaging gradients, and eddy currents were assessed independently. The observed bias errors were compared with numerical models.Results: The measured systematic ADC errors scaled quadratically with offset from isocenter, and ranged between −55% (SI) and 25% (RL). Nonlinearity bias was dependent on system design and diffusion gradient direction. Consistent with numerical models, minor ADC errors (±5%) due to shim, imaging and eddy currents were mitigated by double echo DWI and image coregistration of individual gradient directions.Conclusion: The analysis confirms gradient nonlinearity as a major source of spatial DW bias and variability in off‐center ADC measurements across MRI platforms, with minor contributions from shim, imaging gradients and eddy currents. The developed protocol enables empiric description of systematic bias in multicenter quantitative DWI studies. Magn Reson Med 75:1312–1323, 2016.

An approach for measuring mean apparent diffusion coefficient that used two b values is sufficient for improving diagnostic performance of breast MRI and reducing the biopsy rate by up to 22.4% wit... Background The Eastern Cooperative Oncology Group and American College of Radiology Imaging Network Cancer Research Group A6702 multicenter trial helped confirm the potential of diffusion-weighted ...

The aim of this study was to establish the repeatability measures of quantitative Gaussian and non-Gaussian diffusion metrics using diffusion-weighted imaging (DWI) data from phantoms and patients with head-and-neck and papillary thyroid cancers. The Quantitative Imaging Biomarker Alliance (QIBA) DWI phantom and a novel isotropic diffusion kurtosis imaging phantom were scanned at 3 different sites, on 1.5T and 3T magnetic resonance imaging systems, using standardized multiple b-value DWI acquisition protocol. In the clinical component of this study, a total of 60 multiple b-value DWI data sets were analyzed for test–retest, obtained from 14 patients (9 head-and-neck squamous cell carcinoma and 5 papillary thyroid cancers). Repeatability of quantitative DWI measurements was assessed by within-subject coefficient of variation (wCV%) and Bland–Altman analysis. In isotropic diffusion kurtosis imaging phantom vial with 2% ceteryl alcohol and behentrimonium chloride solution, the mean apparent diffusion (Dapp × 10−3 mm2/s) and kurtosis (Kapp, unitless) coefficient values were 1.02 and 1.68 respectively, capturing in vivo tumor cellularity and tissue microstructure. For the same vial, Dapp and Kapp mean wCVs (%) were ≤1.41% and ≤0.43% for 1.5T and 3T across 3 sites. For pretreatment head-and-neck squamous cell carcinoma, apparent diffusion coefficient, D, D*, K, and f mean wCVs (%) were 2.38%, 3.55%, 3.88%, 8.0%, and 9.92%, respectively; wCVs exhibited a higher trend for papillary thyroid cancers. Knowledge of technical precision and bias of quantitative imaging metrics enables investigators to properly design and power clinical trials and better discern between measurement variability versus biological change.