Four-dimensional Flow MRI-based Computational Fluid Dynamics Simulation for Noninvasive Portosystemic Pressure Gradient Assessment in Patients with Cirrhosis and Transjugular Intrahepatic Portosystemic Shunt.

Background Transjugular intrahepatic portosystemic shunt (TIPS) dysfunction in patients with liver cirrhosis and recurrent symptoms of portal hypertension is primarily assessed with US and confirmed with invasive catheter venography, which can be used to measure the portosystemic pressure gradient (PSPG) to identify TIPS-refractory portal hypertension. To avoid the risks and costs of invasive catheter venography, noninvasive PSPG evaluation strategies are needed. Purpose To demonstrate the feasibility of the combination of four-dimensional (4D) flow MRI with computational fluid dynamics (CFD) for noninvasive PSPG assessment in participants with cirrhosis and TIPS. Materials and Methods Abdominal 4D flow MRI was performed prospectively in participants with cirrhosis and TIPS between January 2019 and September 2020. Flow rates were measured within the TIPS and inferior vena cava (IVC). The portal vein (PV), TIPS, right hepatic vein, and IVC were segmented on MRI scans to create a CFD mesh. The PV and infrahepatic IVC were defined as inflows for 4D flow MRI-derived flow rates. The suprahepatic IVC was defined as the outflow. CFD simulations were used to noninvasively estimate PSPG as the difference between the simulated pressures in the PV and suprahepatic IVC. Invasive venographic measurements of the PSPG served as the reference standard, and Pearson correlation analysis was conducted to evaluate the relationship between noninvasive estimates and invasive measurements. Results In all 20 participants with cirrhosis (mean age, 58 years ± 9 [SD]; 11 men), 4D flow MRI-based CFD simulations enabled visualization of flow velocities and pressure distributions within the segmented vasculature and TIPS. Noninvasive estimates and invasive measures of PSPG were strongly correlated (r = 0.77; P < .001). The 4D flow MRI-based CFD simulations correctly classified the presence or absence of a post-TIPS PSPG greater than 12 mm Hg in 16 of 20 participants (80%). Conclusion The combination of 4D flow MRI and CFD was feasible for noninvasive PSPG assessment in participants with cirrhosis, portal hypertension, and TIPS. © RSNA, 2024 See also the editorial by Motosugi and Watanabe in this issue.

Effect of particle size on liver MRI R 2 * relaxometry: Monte Carlo simulation and phantom studies.

PURPOSE: To investigate the effect of particle size on liver R 2 * $$ {\mathrm{R}}_2^{\ast } $$ by Monte Carlo simulation and phantom studies at both 1.5 T and 3.0 T. METHODS: Two kinds of particles (i.e., iron sphere and fat droplet) with varying sizes were considered separately in simulation and phantom studies. MRI signals were synthesized and analyzed for predicting R 2 * $$ {\mathrm{R}}_2^{\ast } $$ , based on simulations by incorporating virtual liver model, particle distribution, magnetic field generation, and proton movement into phase accrual. In the phantom study, iron-water and fat-water phantoms were constructed, and each phantom contained 15 separate vials with combinations of five particle concentrations and three particle sizes. R 2 * $$ {\mathrm{R}}_2^{\ast } $$ measurements in the phantom were made at both 1.5 T and 3.0 T. Finally, differences in R 2 * $$ {\mathrm{R}}_2^{\ast } $$ predictions or measurements were evaluated across varying particle sizes. RESULTS: In the simulation study, strong linear and positively correlated relationships were observed between R 2 * $$ {\mathrm{R}}_2^{\ast } $$ predictions and particle concentrations across varying particle sizes and magnetic field strengths ( r ≥ 0.988 $$ r\ge 0.988 $$ ). The relationships were affected by iron sphere size ( p < 0.001 $$ p<0.001 $$ ), where smaller iron sphere size yielded higher predicted R 2 * $$ {\mathrm{R}}_2^{\ast } $$ , whereas fat droplet size had no effect on R 2 * $$ {\mathrm{R}}_2^{\ast } $$ predictions ( p ≥ 0.617 $$ p\ge 0.617 $$ ) for constant total fat concentration. Similarly, the phantom study showed that R 2 * $$ {\mathrm{R}}_2^{\ast } $$ measurements were relatively sensitive to iron sphere size ( p ≤ 0.004 $$ p\le 0.004 $$ ) unlike fat droplet size ( p ≥ 0.223 $$ p\ge 0.223 $$ ). CONCLUSION: Liver R 2 * $$ {\mathrm{R}}_2^{\ast } $$ is affected by iron sphere size, but is relatively unaffected by fat droplet size. These findings may lead to an improved understanding of the underlying mechanisms of R 2 * $$ {\mathrm{R}}_2^{\ast } $$ relaxometry in vivo, and enable improved quantitative MRI phantom design.

Confidence maps for reliable estimation of proton density fat fraction and R 2 * in the liver.

PURPOSE: The objective was to develop a fully automated algorithm that generates confidence maps to identify regions valid for analysis of quantitative proton density fat fraction (PDFF) and R 2 * $$ {R}_2^{\ast } $$ maps of the liver, generated with chemical shift-encoded MRI (CSE-MRI). Confidence maps are urgently needed for automated quality assurance, particularly with the emergence of automated segmentation and analysis algorithms. METHODS: Confidence maps for both PDFF and R 2 * $$ {R}_2^{\ast } $$ maps are generated based on goodness of fit, measured by normalized RMS error between measured complex signals and the CSE-MRI signal model. Based on Cramér-Rao lower bound and Monte-Carlo simulations, normalized RMS error threshold criteria were developed to identify unreliable regions in quantitative maps. Simulation, phantom, and in vivo clinical studies were included. To analyze the clinical data, a board-certified radiologist delineated regions of interest (ROIs) in each of the nine liver segments for PDFF and R 2 * $$ {R}_2^{\ast } $$ analysis in consecutive clinical CSE-MRI data sets. The percent area of ROIs in areas deemed unreliable by confidence maps was calculated to assess the impact of confidence maps on real-world clinical PDFF and R 2 * $$ {R}_2^{\ast } $$ measurements. RESULTS: Simulations and phantom studies demonstrated that the proposed algorithm successfully excluded regions with unreliable PDFF and R 2 * $$ {R}_2^{\ast } $$ measurements. ROI analysis by the radiologist revealed that 2.6% and 15% of the ROIs were placed in unreliable areas of PDFF and R 2 * $$ {R}_2^{\ast } $$ maps, as identified by confidence maps. CONCLUSION: A proposed confidence map algorithm that identifies reliable areas of PDFF and R 2 * $$ {R}_2^{\ast } $$ measurements from CSE-MRI acquisitions was successfully developed. It demonstrated technical and clinical feasibility.

Free-breathing, fat-corrected T1 mapping of the liver with stack-of-stars MRI, and joint estimation of T1, PDFF, R 2 * , and B 1 + .

PURPOSE: Quantitative T1 mapping has the potential to replace biopsy for noninvasive diagnosis and quantitative staging of chronic liver disease. Conventional T1 mapping methods are confounded by fat and B 1 + $$ {B}_1^{+} $$ inhomogeneities, resulting in unreliable T1 estimations. Furthermore, these methods trade off spatial resolution and volumetric coverage for shorter acquisitions with only a few images obtained within a breath-hold. This work proposes a novel, volumetric (3D), free-breathing T1 mapping method to account for multiple confounding factors in a single acquisition. THEORY AND METHODS: Free-breathing, confounder-corrected T1 mapping was achieved through the combination of non-Cartesian imaging, magnetization preparation, chemical shift encoding, and a variable flip angle acquisition. A subspace-constrained, locally low-rank image reconstruction algorithm was employed for image reconstruction. The accuracy of the proposed method was evaluated through numerical simulations and phantom experiments with a T1/proton density fat fraction phantom at 3.0 T. Further, the feasibility of the proposed method was investigated through contrast-enhanced imaging in healthy volunteers, also at 3.0 T. RESULTS: The method showed excellent agreement with reference measurements in phantoms across a wide range of T1 values (200 to 1000 ms, slope = 0.998 (95% confidence interval (CI) [0.963 to 1.035]), intercept = 27.1 ms (95% CI [0.4 54.6]), r2 = 0.996), and a high level of repeatability. In vivo imaging studies demonstrated moderate agreement (slope = 1.099 (95% CI [1.067 to 1.132]), intercept = -96.3 ms (95% CI [-82.1 to -110.5]), r2 = 0.981) compared to saturation recovery-based T1 maps. CONCLUSION: The proposed method produces whole-liver, confounder-corrected T1 maps through simultaneous estimation of T1, proton density fat fraction, and B 1 + $$ {B}_1^{+} $$ in a single, free-breathing acquisition and has excellent agreement with reference measurements in phantoms.

Multicenter, multivendor validation of liver quantitative susceptibility mapping in patients with iron overload at 1.5 T and 3 T.

PURPOSE: To evaluate the repeatability and reproducibility of QSM of the liver via single breath-hold chemical shift-encoded MRI at both 1.5 T and 3 T in a multicenter, multivendor study in subjects with iron overload. METHODS: This prospective study included four academic medical centers with three different MRI vendors at 1.5 T and 3 T. Subjects with known or suspected liver iron overload underwent multi-echo spoiled gradient-recalled-echo scans at each field strength. A subset received repeatability testing at either 1.5 T or 3 T. Susceptibility and R 2 * $$ {\mathrm{R}}_2^{\ast } $$ maps were reconstructed from the multi-echo images and analyzed at a single center. QSM-measured susceptibility was compared with R 2 * $$ {\mathrm{R}}_2^{\ast } $$ and a commercial R2-based liver iron concentration method across centers and field strengths using linear regression and F-tests on the intercept and slope. Field-strength reproducibility and test/retest repeatability were evaluated using Bland-Altman analysis. RESULTS: A total of 155/80 data sets (test/retest) were available at 1.5 T, and 159/70 data sets (test/retest) were available at 3 T. Calibrations across sites were reproducible, with some variability (e.g., susceptibility slope with liver iron concentration ranged from 0.102 to 0.123 g/[mg · $$ \cdotp $$ ppm] across centers at 1.5 T). Field strength reproducibility was good (concordance correlation coefficient = 0.862), and test/retest repeatability was excellent (intraclass correlation coefficient = 0.951). CONCLUSION: QSM as an imaging biomarker of liver iron overload is feasible and repeatable across centers and MR vendors. It may be complementary with R 2 * $$ {\mathrm{R}}_2^{\ast } $$ as they are obtained from the same acquisition. Although good reproducibility was observed, liver QSM may benefit from standardization of acquisition parameters. Overall, QSM is a promising method for liver iron quantification.

Prediction of MRI R 2 * $$ {\mathrm{R}}_2

To develop Monte Carlo simulations to predict the relationship of R 2 * $$ {\mathrm{R}}_2^{\ast } $$ with liver fat content at 1.5 T and 3.0 T. For various fat fractions (FFs) from 1% to 25%, four types of virtual liver models were developed by incorporating the size and spatial distribution of fat droplets. Magnetic fields were then generated under different fat susceptibilities at 1.5 T and 3.0 T, and proton movement was simulated for phase accrual and MRI signal synthesis. The synthesized signal was fit to single-peak and multi-peak fat signal models for R 2 * $$ {\mathrm{R}}_2^{\ast } $$ and proton density fat fraction (PDFF) predictions. In addition, the relationships between R 2 * $$ {\mathrm{R}}_2^{\ast } $$ and PDFF predictions were compared with in vivo calibrations and Bland-Altman analysis was performed to quantitatively evaluate the effects of these components (type of virtual liver model, fat susceptibility, and fat signal model) on R 2 * $$ {\mathrm{R}}_2^{\ast } $$ predictions. A virtual liver model with realistic morphology of fat droplets was demonstrated, and R 2 * $$ {\mathrm{R}}_2^{\ast } $$ and PDFF values were predicted by Monte Carlo simulations at 1.5 T and 3.0 T. R 2 * $$ {\mathrm{R}}_2^{\ast } $$ predictions were linearly correlated with PDFF, while the slope was unaffected by the type of virtual liver model and increased as fat susceptibility increased. Compared with in vivo calibrations, the multi-peak fat signal model showed superior performance to the single-peak fat signal model, which yielded an underestimation of liver fat. The R 2 * $$ {\mathrm{R}}_2^{\ast } $$ -PDFF relationships by simulations with fat susceptibility of 0.6 ppm and the multi-peak fat signal model were R 2 * = 0.490 × PDFF + 28.0 $$ {\mathrm{R}}_2^{\ast }=0.490\times \mathrm{PDFF}+28.0 $$ ( R 2 = 0.967 $$ {R}^2=0.967 $$ , p < 0.01 $$ p<0.01 $$ ) at 1.5 T and R 2 * = 0.928 × PDFF + 39.4 $$ {\mathrm{R}}_2^{\ast }=0.928\times \mathrm{PDFF}+39.4 $$ ( R 2 = 0.972 $$ {R}^2=0.972 $$ , p < 0.01 $$ p<0.01 $$ ) at 3.0 T. Monte Carlo simulations provide a new means for R 2 * $$ {\mathrm{R}}_2^{\ast } $$ -PDFF prediction, which is primarily determined by fat susceptibility, fat signal model, and magnetic field strength. Accurate R 2 * $$ {\mathrm{R}}_2^{\ast } $$ -PDFF calibration has the potential to correct the effect of fat on R 2 * $$ {\mathrm{R}}_2^{\ast } $$ quantification, and may be helpful for accurate R 2 * $$ {\mathrm{R}}_2^{\ast } $$ measurements in liver iron overload. In this study, a Monte Carlo simulation of hepatic steatosis was developed to predict the relationship between R 2 * $$ {\mathrm{R}}_2^{\ast } $$ and PDFF. Furthermore, the effects of fat droplet morphology, fat susceptibility, fat signal model, and magnetic field strength were evaluated for the R 2 * $$ {\mathrm{R}}_2^{\ast } $$ -PDFF calibration. Our results suggest that Monte Carlo simulations provide a new means for R 2 * $$ {\mathrm{R}}_2^{\ast } $$ -PDFF prediction and this means can be easily generated for various regimes, such as simulations with higher fields and different echo times, as well as correction of magnetic susceptibility measurements for liver iron quantification.

Practical Application of Multivendor MRI-Based R2* Mapping for Liver Iron Quantification at 1.5 T and 3.0 T.

BACKGROUND: Recent multicenter, multivendor MRI-based R2* vs. liver iron concentration (LIC) calibrations (i.e., MCMV calibrations) may facilitate broad clinical dissemination of R2*-based LIC quantification. However, these calibrations are based on a centralized offline R2* reconstruction, and their applicability with vendor-provided R2* maps is unclear. PURPOSE: To determine R2* ranges of agreement between the centralized and three MRI vendors' R2* reconstructions. STUDY TYPE: Prospective. SUBJECTS: Two hundred and seven subjects (mean age 37.6 ± 19.6 years; 117 male) with known or suspected iron overload from four academic medical centers. FIELD STRENGTH/SEQUENCE: Standardized multiecho spoiled gradient echo sequence at 1.5 T and 3.0 T for R2* mapping and a multiple spin-echo sequence at 1.5 T for LIC quantification. MRI vendors: GE Healthcare, Philips Healthcare, and Siemens Healthineers. ASSESSMENT: R2* maps were generated using both the centralized and vendor reconstructions, and ranges of agreement were determined. R2*-LIC linear calibrations were determined for each site, field strength, and reconstruction and compared with the MCMV calibrations. STATISTICAL TESTS: Bland-Altman analysis to determine ranges of agreement. Linear regression, analysis of covariance F tests, and Tukey's multiple comparison testing to assess reproducibility of calibrations across sites and vendors. A P value <0.05 was considered significant. RESULTS: The upper limits of R2* ranges of agreement were approximately 500, 375, and 330 s-1 for GE, Philips, and Siemens reconstructions, respectively, at 1.5 T and approximately 700 and 800 s-1 for GE and Philips, respectively, at 3.0 T. Within the R2* ranges of agreement, vendor R2*-LIC calibrations demonstrated high reproducibility (no significant differences between slopes or intercepts; P ≥ 0.06) and agreed with the MCMV calibrations (overlapping 95% confidence intervals). DATA CONCLUSION: Based on the determined upper limits, R2* measurements obtained from vendor-provided R2* maps may be reliably and practically used to quantify LIC less than approximately 8-13 mg/g using the MCMV calibrations and similar acquisition parameters as this study. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 3.

Apparent Variation in Measurement Size of Colorectal Cancer Metastases to the Liver on Dual Contrast MRI.

PURPOSE: The aim of this study was to formally investigate the apparent variation in lesion size of hepatic metastatic lesions from colorectal cancer on hepatobiliary phase (HBP) and dual contrast images of magnetic resonance imaging performed with both hepatobiliary and extracellular contrast agents. METHODS: Patients with known colorectal carcinoma who had undergone dual contrast liver magnetic resonance imaging were identified in our institutional database. Metastatic lesions were measured semiautomatically on both HBP and dual contrast images with a custom software tool that automatically identifies the lesion edge and thereby the lesion diameter. Lesion measurements from both sets of images were compared with a Student t test and Bland-Altman analysis. Lesions were also measured on both HBP and dual contrast images by 2 fellowship-trained abdominal radiologists. Measurements from the software and radiologists were compared with a Student t test and Bland-Altman analysis; interreader agreement was evaluated with the intraclass correlation coefficient. RESULTS: A total of 70 liver lesions in 39 patients was identified. Software-based measurements were significantly larger on HBP than dual contrast images ( P < 0.001), with a mean lesion size of 10.9 ± 4.2 mm for HBP and 10.5 ± 4.2 mm for dual contrast measurements. Radiologist-based measurements showed a similar trend, with HBP measurements being significantly larger than dual contrast measurements ( P < 0.001). Bland-Altman analysis indicated a mean bias ± 2 SD of +0.4 ± 1.6 mm for software-based measurements and +0.9 ± 2.9 mm and +0.7 ± 2.1 mm for readers 1 and 2, respectively. The intraclass correlation coefficient for interreader agreement was 0.9. CONCLUSIONS: Both software-based and radiologist-based measurements of colorectal cancer liver metastases are significantly larger on HBP than dual contrast images. Based on these findings, we recommend that longitudinal assessment be performed consistently on either HBP or dual contrast phases to avoid introduction of avoidable variability.

Skeletal Muscle Adiposity and Lung Function Trajectory in the Severe Asthma Research Program.

Rationale: Extrapulmonary manifestations of asthma, including fatty infiltration in tissues, may reflect systemic inflammation and influence lung function and disease severity. Objectives: To determine if skeletal muscle adiposity predicts lung function trajectory in asthma. Methods: Adult SARP III (Severe Asthma Research Program III) participants with baseline computed tomography imaging and longitudinal postbronchodilator FEV1% predicted (median follow-up 5 years [1,132 person-years]) were evaluated. The mean of left and right paraspinous muscle density (PSMD) at the 12th thoracic vertebral body was calculated (Hounsfield units [HU]). Lower PSMD reflects higher muscle adiposity. We derived PSMD reference ranges from healthy control subjects without asthma. A linear multivariable mixed-effects model was constructed to evaluate associations of baseline PSMD and lung function trajectory stratified by sex. Measurements and Main Results: Participants included 219 with asthma (67% women; mean [SD] body mass index, 32.3 [8.8] kg/m2) and 37 control subjects (51% women; mean [SD] body mass index, 26.3 [4.7] kg/m2). Participants with asthma had lower adjusted PSMD than control subjects (42.2 vs. 55.8 HU; P < 0.001). In adjusted models, PSMD predicted lung function trajectory in women with asthma (ß = -0.47 Δ slope per 10-HU decrease; P = 0.03) but not men (ß = 0.11 Δ slope per 10-HU decrease; P = 0.77). The highest PSMD tertile predicted a 2.9% improvement whereas the lowest tertile predicted a 1.8% decline in FEV1% predicted among women with asthma over 5 years. Conclusions: Participants with asthma have lower PSMD, reflecting greater muscle fat infiltration. Baseline PSMD predicted lung function decline among women with asthma but not men. These data support an important role of metabolic dysfunction in lung function decline.

Quantification of Liver Iron Overload with MRI: Review and Guidelines from the ESGAR and SAR.

Accumulation of excess iron in the body, or systemic iron overload, results from a variety of causes. The concentration of iron in the liver is linearly related to the total body iron stores and, for this reason, quantification of liver iron concentration (LIC) is widely regarded as the best surrogate to assess total body iron. Historically assessed using biopsy, there is a clear need for noninvasive quantitative imaging biomarkers of LIC. MRI is highly sensitive to the presence of tissue iron and has been increasingly adopted as a noninvasive alternative to biopsy for detection, severity grading, and treatment monitoring in patients with known or suspected iron overload. Multiple MRI strategies have been developed in the past 2 decades, based on both gradient-echo and spin-echo imaging, including signal intensity ratio and relaxometry strategies. However, there is a general lack of consensus regarding the appropriate use of these methods. The overall goal of this article is to summarize the current state of the art in the clinical use of MRI to quantify liver iron content and to assess the overall level of evidence of these various methods. Based on this summary, expert consensus panel recommendations on best practices for MRI-based quantification of liver iron are provided.

Multicenter Reproducibility of Liver Iron Quantification with 1.5-T and 3.0-T MRI.

Background MRI is a standard of care tool to measure liver iron concentration (LIC). Compared with regulatory-approved R2 MRI, R2* MRI has superior speed and is available in most MRI scanners; however, the cross-vendor reproducibility of R2*-based LIC estimation remains unknown. Purpose To evaluate the reproducibility of LIC via single-breath-hold R2* MRI at both 1.5 T and 3.0 T with use of a multicenter, multivendor study. Materials and Methods Four academic medical centers using MRI scanners from three different vendors (three 1.5-T scanners, one 2.89-T scanner, and two 3.0-T scanners) participated in this prospective cross-sectional study. Participants with known or suspected liver iron overload were recruited to undergo multiecho gradient-echo MRI for R2* mapping at 1.5 T and 3.0 T (2.89 T or 3.0 T) on the same day. R2* maps were reconstructed from the multiecho images and analyzed at a single center. Reference LIC measurements were obtained with a commercial R2 MRI method performed using standardized 1.5-T spin-echo imaging. R2*-versus-LIC calibrations were generated across centers and field strengths using linear regression and compared using F tests. Receiver operating characteristic (ROC) curve analysis was used to determine the diagnostic performance of R2* MRI in the detection of clinically relevant LIC thresholds. Results A total of 207 participants (mean age, 38 years ± 20 [SD]; 117 male participants) were evaluated between March 2015 and September 2019. A linear relationship was confirmed between R2* and LIC. All calibrations within the same field strength were highly reproducible, showing no evidence of statistically significant center-specific differences (P > .43 across all comparisons). Calibrations for 1.5 T and 3.0 T were generated, as follows: for 1.5 T, LIC (in milligrams per gram [dry weight]) = -0.16 + 2.603 × 10-2 R2* (in seconds-1); for 2.89 T, LIC (in milligrams per gram) = -0.03 + 1.400 × 10-2 R2* (in seconds-1); for 3.0 T, LIC (in milligrams per gram) = -0.03 + 1.349 × 10-2 R2* (in seconds-1). Liver R2* had high diagnostic performance in the detection of clinically relevant LIC thresholds (area under the ROC curve, >0.98). Conclusion R2* MRI enabled accurate and reproducible quantification of liver iron overload over clinically relevant ranges of liver iron concentration (LIC). The data generated in this study provide the necessary calibrations for broad clinical dissemination of R2*-based LIC quantification. ClinicalTrials.gov registration no.: NCT02025543 © RSNA, 2022 Online supplemental material is available for this article.

Confounder-corrected T1 mapping in the liver through simultaneous estimation of T1 , PDFF, R 2 * , and B 1 + in a single breath-hold acquisition.

PURPOSE: Quantitative volumetric T1 mapping in the liver has the potential to aid in the detection, diagnosis, and quantification of liver fibrosis, inflammation, and spatially resolved liver function. However, accurate measurement of hepatic T1 is confounded by the presence of fat and inhomogeneous B 1 + $$ {B}_1^{+} $$ excitation. Furthermore, scan time constraints related to respiratory motion require tradeoffs of reduced volumetric coverage and/or increased acquisition time. This work presents a novel 3D acquisition and estimation method for confounder-corrected T1 measurement over the entire liver within a single breath-hold through simultaneous estimation of T1 , fat and B 1 + $$ {B}_1^{+} $$ . THEORY AND METHODS: The proposed method combines chemical shift encoded MRI and variable flip angle MRI with a B 1 + $$ {B}_1^{+} $$ mapping technique to enable confounder-corrected T1 mapping. The method was evaluated theoretically and demonstrated in both phantom and in vivo acquisitions at 1.5 and 3.0T. At 1.5T, the method was evaluated both pre- and post- contrast enhancement in healthy volunteers. RESULTS: The proposed method demonstrated excellent linear agreement with reference inversion-recovery spin-echo based T1 in phantom acquisitions at both 1.5 and 3.0T, with minimal bias (5.2 and 45 ms, respectively) over T1 ranging from 200-1200 ms. In vivo results were in general agreement with reference saturation-recovery based 2D T1 maps (SMART1 Map, GE Healthcare). CONCLUSION: The proposed 3D T1 mapping method accounts for fat and B 1 + $$ {B}_1^{+} $$ confounders through simultaneous estimation of T1 , B 1 + $$ {B}_1^{+} $$ , PDFF and R 2 * $$ {R}_2^{\ast } $$ . It demonstrates strong linear agreement with reference T1 measurements, with low bias and high precision, and can achieve full liver coverage in a single breath-hold.

Validation of liver quantitative susceptibility mapping across imaging parameters at 1.5 T and 3.0 T using SQUID susceptometry as reference.

PURPOSE: To validate QSM-based biomagnetic liver susceptometry (BLS) to measure liver iron overload at 1.5 T and 3.0 T using superconducting quantum interference devices (SQUID)-based BLS as reference. METHODS: Subjects with known or suspected iron overload were recruited for QSM-BLS at 1.5 T and 3.0 T using eight different protocols. SQUID-BLS was also obtained in each subject to provide susceptibility reference. A recent QSM method based on data-adaptive regularization was used to obtain susceptibility and R 2 * $$ {\mathrm{R}}_2^{\ast } $$ maps. Measurements of susceptibility and R 2 * $$ {\mathrm{R}}_2^{\ast } $$ were obtained in the right liver lobe. Linear mixed-effects analysis was used to estimate the contribution of specific acquisition parameters to QSM-BLS. Linear regression and Bland-Altman analyses were used to assess the relationship between QSM-BLS and SQUID-BLS/ R 2 * $$ {\mathrm{R}}_2^{\ast } $$ . RESULTS: Susceptibility maps showed high subjective quality for each acquisition protocol across different iron levels. High linear correlation was observed between QSM-BLS and SQUID-BLS at 1.5 T (r2 range, [0.82, 0.84]) and 3.0 T (r2 range, [0.77, 0.85]) across different acquisition protocols. QSM-BLS and R 2 * $$ {\mathrm{R}}_2^{\ast } $$ were highly correlated at both field strengths (r2 range at 1.5 T, [0.94, 0.99]; 3.0 T, [0.93, 0.99]). High correlation (r2  = 0.99) between 1.5 T and 3.0 T QSM-BLS, with narrow reproducibility coefficients (range, [0.13, 0.21] ppm) were observed for each protocol. CONCLUSION: This work evaluated the feasibility and performance of liver QSM-BLS across iron levels and acquisition protocols at 1.5 T and 3.0 T. High correlation and reproducibility were observed between QSM-BLS and SQUID-BLS across protocols and field strengths. In summary, QSM-BLS may enable reliable and reproducible quantification of liver iron concentration.

Data adaptive regularization with reference tissue constraints for liver quantitative susceptibility mapping.

PURPOSE: To improve repeatability and reproducibility across acquisition parameters and reduce bias in quantitative susceptibility mapping (QSM) of the liver, through development of an optimized regularized reconstruction algorithm for abdominal QSM. METHODS: An optimized approach to estimation of magnetic susceptibility distribution is formulated as a constrained reconstruction problem that incorporates estimates of the input data reliability and anatomical priors available from chemical shift-encoded imaging. The proposed data-adaptive method was evaluated with respect to bias, repeatability, and reproducibility in a patient population with a wide range of liver iron concentration (LIC). The proposed method was compared to the previously proposed and validated approach in liver QSM for two multi-echo spoiled gradient-recalled echo protocols with different acquisition parameters at 3T. Linear regression was used for evaluation of QSM methods against a reference FDA-approved R 2 $$ {R}_2 $$ -based LIC measure and R 2 ∗ $$ {R}_2^{\ast } $$ measurements; repeatability/reproducibility were assessed by Bland-Altman analysis. RESULTS: The data-adaptive method produced susceptibility maps with higher subjective quality due to reduced shading artifacts. For both acquisition protocols, higher linear correlation with both R 2 $$ {R}_2 $$ - and R 2 ∗ $$ {R}_2^{\ast } $$ -based measurements were observed for the data-adaptive method ( r 2 = 0 . 74 / 0 . 69 $$ {r}^2=0.74/0.69 $$ for R 2 $$ {R}_2 $$ , 0 . 97 / 0 . 95 $$ 0.97/0.95 $$ for R 2 ∗ $$ {R}_2^{\ast } $$ ) than the standard method ( r 2 = 0 . 60 / 0 . 66 $$ {r}^2=0.60/0.66 $$ and 0 . 79 / 0 . 88 $$ 0.79/0.88 $$ ). For both protocols, the data-adaptive method enabled better test-retest repeatability (repeatability coefficients 0.19/0.30 ppm for the data-adaptive method, 0.38/0.47 ppm for the standard method) and reproducibility across protocols (reproducibility coefficient 0.28 vs. 0.53ppm) than the standard method. CONCLUSIONS: The proposed data-adaptive QSM algorithm may enable quantification of LIC with improved repeatability/reproducibility across different acquisition parameters as 3T.

Fat mitigation strategies to improve image quality of radial 4D flow MRI in obese subjects.

PURPOSE: This study addresses the challenges in obtaining abdominal 4D flow MRI of obese patients. We aimed to evaluate spectral saturation and inner volume excitation as methods to mitigating artifacts originating from adipose signals, with the goal of enhancing image quality and improving quantification. METHODS: Radial 4D flow MRI acquisitions with fat mitigation (inner volume excitation [IVE] and intermittent fat saturation [FS]) were compared to a standard slab selective excitation (SSE) in a test-retest study of 15 obese participants. IVE selectively excited a cylindrical region of interest, avoiding contamination from peripheral adipose tissue, while FS globally suppressed fat based on spectral selection. Acquisitions were evaluated qualitatively based on expert ratings and quantitatively based on conservation of mass, test-retest repeatability, and a divergence free quality metric. Errors were evaluated statistically using the absolute and relative errors, regression, and Bland-Altman analysis. RESULTS: IVE demonstrated superior performance quantitatively in the conservation of mass analysis in the portal vein, with higher correlation and lower bias in regression analysis. IVE also produced flow fields with the lowest divergence error and was rated best in overall image quality, delineating small vessels, and producing the least streaking artifacts. Evaluation results did not differ significantly between FS and SSE. Test-retest reproducibility was similarly high for all sequences, with data suggesting biological variations dominate the technical variability. CONCLUSION: IVE improved hemodynamic assessment of radial 4D flow MRI in the abdomen of obese participants while FS did not lead to significant improvements in image quality or flow metrics.

Pulmonary MRA During Pregnancy: Early Experience With Ferumoxytol.

BACKGROUND: Ferumoxytol, an intravenous iron supplement, is commonly used to treat anemia in pregnancy. Ferumoxytol-enhanced magnetic resonance angiography (Fe-MRA) is a viable off-label alternative to gadolinium-enhanced MRA for assessment of pulmonary embolism (PE) in pregnancy. PURPOSE: To describe our clinical experience with Fe-MRA in pregnant women with suspected PE. STUDY TYPE: Retrospective, observational, cohort. POPULATION: A total of 98 Fe-MRA exams (consecutive sample) performed in 94 pregnant women. FIELD STRENGTH/SEQUENCE: A 1.5 T and 3.0 T, 3D T1-weighted MRA. ASSESSMENT: After IRB approval including a waiver of informed consent, electronic health records were reviewed retrospectively for all Fe-MRA exams performed at our institution in pregnant between January, 2017 and March, 2022. The Fe-MRA protocol included 3D-MRA for assessment of pulmonary arteries, and T1-weighted imaging for ancillary findings. Fe-MRA exam duration was measured from image time stamps. Fe-MRA exams were reviewed by three cardiovascular imagers using a 4-point Likert scale for image quality and confidence for PE diagnosis (score 4 = best, 1 = worst), and tabulation of ancillary findings. STATISTICAL TESTS: Continuous data are presented as mean ± standard deviation. The overall image quality and confidence score is given as the mean of three readers. RESULTS: The 98 Fe-MRA exams were performed in 94 pregnant women (age 30 ± 6, range 19-48 years, gestational week 23 ± 10, range 3-38 weeks), with four undergoing two Fe-MRA exams during their pregnancy. Median Fe-MRA exam durration was 8 minutes (interquantile range 6 minutes). Overall image quality score was 3.3 ± 0.9. Confidence score for diagnosing PE was 3.5 ± 0.8. One subject was positive for PE (1/94, 1%); 42 of the 94 (45%) subjects Fe-MRA had ancillary findings including hydronephrosis or pneumonia. CONCLUSION: Ferumoxytol enhanced MRA is a radiation- and gadolinium-free alternative for diagnosis of PE during pregancy. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 5.

Automated MR Image Prescription of the Liver Using Deep Learning: Development, Evaluation, and Prospective Implementation.

BACKGROUND: There is an unmet need for fully automated image prescription of the liver to enable efficient, reproducible MRI. PURPOSE: To develop and evaluate artificial intelligence (AI)-based liver image prescription. STUDY TYPE: Prospective. POPULATION: A total of 570 female/469 male patients (age: 56 ± 17 years) with 72%/8%/20% assigned randomly for training/validation/testing; two female/four male healthy volunteers (age: 31 ± 6 years). FIELD STRENGTH/SEQUENCE: 1.5 T, 3.0 T; spin echo, gradient echo, bSSFP. ASSESSMENT: A total of 1039 three-plane localizer acquisitions (26,929 slices) from consecutive clinical liver MRI examinations were retrieved retrospectively and annotated by six radiologists. The localizer images and manual annotations were used to train an object-detection convolutional neural network (YOLOv3) to detect multiple object classes (liver, torso, and arms) across localizer image orientations and to output corresponding 2D bounding boxes. Whole-liver image prescription in standard orientations was obtained based on these bounding boxes. 2D detection performance was evaluated on test datasets by calculating intersection over union (IoU) between manual and automated labeling. 3D prescription accuracy was calculated by measuring the boundary mismatch in each dimension and percentage of manual volume covered by AI prescription. The automated prescription was implemented on a 3 T MR system and evaluated prospectively on healthy volunteers. STATISTICAL TESTS: Paired t-tests (threshold = 0.05) were conducted to evaluate significance of performance difference between trained networks. RESULTS: In 208 testing datasets, the proposed method with full network had excellent agreement with manual annotations, with median IoU > 0.91 (interquartile range < 0.09) across all seven classes. The automated 3D prescription was accurate, with shifts <2.3 cm in superior/inferior dimension for 3D axial prescription for 99.5% of test datasets, comparable to radiologists' interreader reproducibility. The full network had significantly superior performance than the tiny network for 3D axial prescription in patients. Automated prescription performed well across single-shot fast spin-echo, gradient-echo, and balanced steady-state free-precession sequences in the prospective study. DATA CONCLUSION: AI-based automated liver image prescription demonstrated promising performance across the patients, pathologies, and field strengths studied. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 1.

Radiologic-pathologic correlation of lesions in resected liver specimens with an ex vivo MRI-compatible localization device.

OBJECTIVE: Liver lesion characterization is limited by the lack of an established gold standard for precise correlation of radiologic characteristics with their histologic features. The objective of this study was to demonstrate the feasibility of using an ex vivo MRI-compatible sectioning device for radiologic-pathologic co-localization of lesions in resected liver specimens. METHODS: In this prospective feasibility study, adults undergoing curative partial hepatectomy from February 2018 to January 2019 were enrolled. Gadoxetic acid was administered intraoperatively prior to hepatic vascular inflow ligation. Liver specimens were stabilized in an MRI-compatible acrylic lesion localization device (27 × 14 × 14 cm3) featuring slicing channels and a silicone gel 3D matrix. High-resolution 3D T1-weighted fast spoiled gradient echo and 3D T2-weighted fast-spin-echo images were acquired using a single channel quadrature head coil. Radiologic lesion coordinates guided pathologic sectioning. A final histopathologic diagnosis was prepared for all lesions. The proportion of successfully co-localized lesions was determined. RESULTS: A total of 57 lesions were identified radiologically and sectioned in liver specimens from 10 participants with liver metastases (n = 8), primary biliary mucinous cystic neoplasm (n = 1), and hepatic adenomatosis (n = 1). Of these, 38 lesions (67%) were < 1 cm. Overall, 52/57 (91%) of radiologically identified lesions were identified pathologically using the device. Of these, 5 lesions (10%) were not initially identified on gross examination but were confirmed histologically using MRI-guided localization. One lesion was identified grossly but not on MRI. CONCLUSIONS: We successfully demonstrated the feasibility of a clinical method for image-guided co-localization and histological characterization of liver lesions using an ex vivo MRI-compatible sectioning device. KEY POINTS: • The ex vivo MRI-compatible sectioning device provides a reliable method for radiologic-pathologic correlation of small (< 1 cm) liver lesions in human liver specimens. • The sectioning method can be feasibly implemented within a clinical practice setting and used in future efforts to study liver lesion characterization. • Intraoperative administration of gadoxetic acid results in enhancement in ex vivo MRI images of liver specimens hours later with excellent image quality.

Validation of 4D flow cardiovascular magnetic resonance in TIPS stent grafts using a 3D-printed flow phantom.

BACKGROUND: Four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) is feasible for portal blood flow evaluation after placement of transjugular intrahepatic portosystemic shunts (TIPS) in patients with liver cirrhosis. However, clinical acceptance of 4D flow CMR in TIPS patients is limited due to the lack of validation studies. The purpose of this study was to validate 4D flow CMR-derived measurements in TIPS stent grafts using a three-dimensional (3D)-printed flow phantom. METHODS: A translucent flow phantom of the portal vasculature was 3D-printed. The phantom consisted of the superior mesenteric vein and the splenic vein draining into the portal vein, the TIPS-tract, and the hepatic vein. A TIPS stent graft (Gore® Viatorr®) was positioned within the TIPS-tract. Superior mesenteric vein and splenic vein served as inlets for blood-mimicking fluid. 4D flow CMR acquisitions were performed at 3T at preset flow rates of 0.8 to 2.8 l/min using velocity encoding of both 1.0 and 2.0 m/s. Flow rates and velocities were measured at predefined levels in the portal vasculature and within the stent graft. Accuracy of 4D flow CMR was assessed through linear regression with reference measurements obtained by flow sensors and two-dimensional (2D) phase contrast (PC) CMR. Intra- and interobserver agreement were assessed through Bland-Altman analyses. RESULTS: At a velocity encoding of 2.0 m/s, 4D flow CMR-derived flow rates and velocities showed an excellent correlation with preset flow rates and 2D PC CMR-derived flow velocities at all vascular levels and within the stent graft (all r ≥ 0.958, p ≤ 0.003). At a velocity encoding of 1.0 m/s, aliasing artifacts were present within the stent graft at flow rates ≥ 2.0 l/min. 4D flow CMR-derived measurements revealed high intra- and interobserver agreement. CONCLUSIONS: The in vitro accuracy and precision of 4D flow CMR is unaffected by the presence of TIPS stent grafts, suggesting that 4D flow CMR may be used to monitor TIPS patency in patients with liver cirrhosis.

Update on Gadolinium Based Contrast Agent Safety, From the AJR Special Series on Contrast Media.

Since its introduction 35 years ago, gadolinium-enhanced MRI has fundamentally changed medical practice. While extraordinarily safe, gadolinium-based contrast agents (GBCAs) may have side effects. Four distinct safety considerations include: acute allergic-like reactions, nephrogenic systemic fibrosis (NSF), gadolinium deposition, and symptoms associated with gadolinium exposure. Acute reactions after GBCA administration are uncommon-far less than with iodinated contrast agents-and, while rare, serious reactions can occur. NSF is a rare, but serious, scleroderma-like condition occurring in patients with kidney failure after exposure to American College of Radiology (ACR) Group 1 GBCAs. Group 2 and 3 GBCAs are considered lower risk, and, through their use, NSF has largely been eliminated. Unrelated to NSF, retention of trace amounts of gadolinium in the brain and other organs has been recognized for over a decade. Deposition occurs with all agents, although linear agents appear to deposit more than macrocyclic agents. Importantly, to date, no data demonstrate any adverse biologic or clinical effects from gadolinium deposition, even with normal kidney function. This article summarizes the latest safety evidence of commercially available GBCAs with a focus on new agents, discusses updates to the ACR NSF GBCA safety classification, and describes approaches for strengthening the evidence needed for regulatory decisions.