Multisite multivendor validation of a quantitative MRI and CT compatible fat phantom.

PURPOSE: Chemical shift-encoded magnetic resonance imaging enables accurate quantification of liver fat content though estimation of proton density fat-fraction (PDFF). Computed tomography (CT) is capable of quantifying fat, based on decreased attenuation with increased fat concentration. Current quantitative fat phantoms do not accurately mimic the CT number of human liver. The purpose of this work was to develop and validate an optimized phantom that simultaneously mimics the MRI and CT signals of fatty liver. METHODS: An agar-based phantom containing 12 vials doped with iodinated contrast, and with a granular range of fat fractions was designed and constructed within a novel CT and MR compatible spherical housing design. A four-site, three-vendor validation study was performed. MRI (1.5T and 3T) and CT images were obtained using each vendor's PDFF and CT reconstruction, respectively. An ROI centered in each vial was placed to measure MRI-PDFF (%) and CT number (HU). Mixed-effects model, linear regression, and Bland-Altman analysis were used for statistical analysis. RESULTS: MRI-PDFF agreed closely with nominal PDFF values across both field strengths and all MRI vendors. A linear relationship (slope = -0.54 ± 0.01%/HU, intercept = 37.15 ± 0.03%) with an R2 of 0.999 was observed between MRI-PDFF and CT number, replicating established in vivo signal behavior. Excellent test-retest repeatability across vendors (MRI: mean = -0.04%, 95% limits of agreement = [-0.24%, 0.16%]; CT: mean = 0.16 HU, 95% limits of agreement = [-0.15HU, 0.47HU]) and good reproducibility using GE scanners (MRI: mean = -0.21%, 95% limits of agreement = [-1.47%, 1.06%]; CT: mean = -0.18HU, 95% limits of agreement = [-1.96HU, 1.6HU]) were demonstrated. CONCLUSIONS: The proposed fat phantom successfully mimicked quantitative liver signal for both MRI and CT. The proposed fat phantom in this study may facilitate broader application and harmonization of liver fat quantification techniques using MRI and CT across institutions, vendors and imaging platforms.

Linearity and Bias of Proton Density Fat Fraction as a Quantitative Imaging Biomarker: A Multicenter, Multiplatform, Multivendor Phantom Study.

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 of CSE MRI to estimate PDFF. Purpose To assess the accuracy of CSE MRI methods for estimating PDFF by determining the linearity and range of bias observed in a phantom. Materials and Methods In this prospective study, a commercial phantom with 12 vials of known PDFF values were shipped across nine U.S. centers. The phantom underwent 160 independent MRI examinations on 27 1.5-T and 3.0-T systems from three vendors. Two three-dimensional CSE MRI protocols with minimal T1 bias were included: vendor and standardized. Each vendor's confounder-corrected complex or hybrid magnitude-complex based reconstruction algorithm was used to generate PDFF maps in both protocols. The Siemens reconstruction required a configuration change to correct for water-fat swaps in the phantom. The MRI PDFF values were compared with the known PDFF values by using linear regression with mixed-effects modeling. The 95% CIs were calculated for the regression slope (ie, proportional bias) and intercept (ie, constant bias) and compared with the null hypothesis (slope = 1, intercept = 0). Results Pooled regression slope for estimated PDFF values versus phantom-derived reference PDFF values was 0.97 (95% CI: 0.96, 0.98) in the biologically relevant 0%-47.5% PDFF range. The corresponding pooled intercept was -0.27% (95% CI: -0.50%, -0.05%). Across vendors, slope ranges were 0.86-1.02 (vendor protocols) and 0.97-1.0 (standardized protocol) at 1.5 T and 0.91-1.01 (vendor protocols) and 0.87-1.01 (standardized protocol) at 3.0 T. The intercept ranges (absolute PDFF percentage) were -0.65% to 0.18% (vendor protocols) and -0.69% to -0.17% (standardized protocol) at 1.5 T and -0.48% to 0.10% (vendor protocols) and -0.78% to -0.21% (standardized protocol) at 3.0 T. Conclusion Proton density fat fraction estimation derived from three-dimensional chemical shift-encoded MRI in a commercial phantom was accurate across vendors, imaging centers, and field strengths, with use of the vendors' product acquisition and reconstruction software. © RSNA, 2021 See also the editorial by Dyke in this issue.

Multisite, multivendor validation of the accuracy and reproducibility of proton-density fat-fraction quantification at 1.5T and 3T using a fat-water phantom.

PURPOSE: To evaluate the accuracy and reproducibility of quantitative chemical shift-encoded (CSE) MRI to quantify proton-density fat-fraction (PDFF) in a fat-water phantom across sites, vendors, field strengths, and protocols. METHODS: Six sites (Philips, Siemens, and GE Healthcare) participated in this study. A phantom containing multiple vials with various oil/water suspensions (PDFF:0%-100%) was built, shipped to each site, and scanned at 1.5T and 3T using two CSE protocols per field strength. Confounder-corrected PDFF maps were reconstructed using a common algorithm. To assess accuracy, PDFF bias and linear regression with the known PDFF were calculated. To assess reproducibility, measurements were compared across sites, vendors, field strengths, and protocols using analysis of covariance (ANCOVA), Bland-Altman analysis, and the intraclass correlation coefficient (ICC). RESULTS: PDFF measurements revealed an overall absolute bias (across sites, field strengths, and protocols) of 0.22% (95% confidence interval, 0.07%-0.38%) and R2 > 0.995 relative to the known PDFF at each site, field strength, and protocol, with a slope between 0.96 and 1.02 and an intercept between -0.56% and 1.13%. ANCOVA did not reveal effects of field strength (P = 0.36) or protocol (P = 0.19). There was a significant effect of vendor (F = 25.13, P = 1.07 × 10-10 ) with a bias of -0.37% (Philips) and -1.22% (Siemens) relative to GE Healthcare. The overall ICC was 0.999. CONCLUSION: CSE-based fat quantification is accurate and reproducible across sites, vendors, field strengths, and protocols. Magn Reson Med 77:1516-1524, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Assessment of pulmonary artery stiffness using velocity-encoding magnetic resonance imaging: evaluation of techniques.

The loss of pulmonary artery (PA) compliance has significant pathophysiological effect on the right ventricle. Noninvasive and reliable assessment of PA wall stiffness would be an essential determiner of right heart load and a clinically useful factor to assess cardiovascular risk. Two MRI techniques have been proposed for assessing PA stiffness by measuring pulse wave velocity (PWV): transit time (TT) and flow area (QA). However, no data are available that compares the two techniques and evaluates their performance, especially over a wide range of PWV values or at 3.0-T, which is the purpose of the present study. Thirty-three patients with different heart conditions were imaged using optimized high-temporal resolution and high-spatial resolution velocity-encoding MRI sequences. Statistical analysis was conducted to study intermethod, interobserver and intraobserver variabilities. The PWV measurements using TT and QA techniques showed good agreement (P>0.1). The Bland-Altman analysis showed negligible differences between the two methods (mean±S.D.=0.11±0.35 m/s, correlation coefficient r=0.94). The repeated measurements showed low interobserver and intraobserver variabilities, although the S.D. of the differences was larger in the QA technique. The mean±S.D. of the TT/QA measurement differences were -0.05±0.2/0.0±0.36 m/s and 0.02±0.26/0.02±0.39 m/s for the interobserver and intraobserver differences, respectively. In conclusion, each technique has its own advantages and disadvantages. The two techniques result in similar measurements, although the QA method is more subjective due to its dependency on operator intervention.

Measuring aortic pulse wave velocity using high-field cardiovascular magnetic resonance: comparison of techniques.

BACKGROUND: The assessment of arterial stiffness is increasingly used for evaluating patients with different cardiovascular diseases as the mechanical properties of major arteries are often altered. Aortic stiffness can be noninvasively estimated by measuring pulse wave velocity (PWV). Several methods have been proposed for measuring PWV using velocity-encoded cardiovascular magnetic resonance (CMR), including transit-time (TT), flow-area (QA), and cross-correlation (XC) methods. However, assessment and comparison of these techniques at high field strength has not yet been performed. In this work, the TT, QA, and XC techniques were clinically tested at 3 Tesla and compared to each other. METHODS: Fifty cardiovascular patients and six volunteers were scanned to acquire the necessary images. The six volunteer scans were performed twice to test inter-scan reproducibility. Patient images were analyzed using the TT, XC, and QA methods to determine PWV. Two observers analyzed the images to determine inter-observer and intra-observer variabilities. The PWV measurements by the three methods were compared to each other to test inter-method variability. To illustrate the importance of PWV using CMR, the degree of aortic stiffness was assessed using PWV and related to LV dysfunction in five patients with diastolic heart failure patients and five matched volunteers. RESULTS: The inter-observer and intra-observer variability results showed no bias between the different techniques. The TT and XC results were more reproducible than the QA; the mean (SD) inter-observer/intra-observer PWV differences were -0.12(1.3)/-0.04(0.4) for TT, 0.2(1.3)/0.09(0.9) for XC, and 0.6(1.6)/0.2(1.4) m/s for QA methods, respectively. The correlation coefficients (r) for the inter-observer/intra-observer comparisons were 0.94/0.99, 0.88/0.94, and 0.83/0.92 for the TT, XC, and QA methods, respectively. The inter-scan reproducibility results showed low variability between the repeated scans (mean (SD) PWV difference = -0.02(0.4) m/s and r = 0.96). The inter-method variability results showed strong correlation between the TT and XC measurements, but less correlation with QA: r = 0.95, 0.87, and 0.89, and mean (SD) PWV differences = -0.12(1.0), 0.8(1.7), and 0.65(1.6) m/s for TT-XC, TT-QA, and XC-QA, respectively. Finally, in the group of diastolic heart failure patient, PWV was significantly higher (6.3 +/- 1.9 m/s) than in volunteers (3.5 +/- 1.4 m/s), and the degree of LV diastolic dysfunction showed good correlation with aortic PWV. CONCLUSIONS: In conclusion, while each of the studied methods has its own advantages and disadvantages, at high field strength, the TT and XC methods result in closer and more reproducible aortic PWV measurements, and the associated image processing requires less user interaction, than in the QA method. The choice of the analysis technique depends on the vessel segment geometry and available image quality.