Free-breathing R2∗ mapping of hepatic iron overload in children using 3D multi-echo UTE cones MRI

Free-breathing MRI techniques for fat and R2* quantification in the liver

OBJECTIVE

To review the recent advancements in free-breathing MRI techniques for proton-density fat fraction (PDFF) and R2* quantification in the liver, and discuss the current challenges and future opportunities.

MATERIALS AND METHODS

This work focused on recent developments of different MRI pulse sequences, motion management strategies, and reconstruction approaches that enable free-breathing liver PDFF and R2* quantification.

RESULTS

Different free-breathing liver PDFF and R2* quantification techniques have been evaluated in various cohorts, including healthy volunteers and patients with liver diseases, both in adults and children. Initial results demonstrate promising performance with respect to reference measurements. These techniques have a high potential impact on providing a solution to the clinical need of accurate liver fat and iron quantification in populations with limited breath-holding capacity.

DISCUSSION

As these free-breathing techniques progress toward clinical translation, studies of the linearity, bias, and repeatability of free-breathing PDFF and R2* quantification in a larger cohort are important. Scan acceleration and improved motion management also hold potential for further enhancement.

Assessment of Osteoporosis at the Lumbar Spine Using Ultrashort Echo Time Magnetization Transfer (UTE-MT) MRI

BACKGROUND

Bone collagen-matrix contributes to the mechanical properties of bone by imparting tensile strength and elasticity, which can be indirectly quantified by ultrashort echo time magnetization transfer ratio (UTE-MTR) to assess osteoporosis.

PURPOSE

To evaluate osteoporosis at the human lumbar spine using UTE-MTR.

STUDY TYPE

Prospective.

POPULATION

One hundred forty-eight-volunteers (age-range, 50-85; females, N = 90), including 81-normal bone density, 35-osteopenic, and 32-osteoporotic subjects. Ten additional healthy volunteers were recruited to study the intrasession reproducibility of the UTE-MT.

FIELD STRENGTH/SEQUENCE

3T/UTE-MT, short repetition-time adiabatic inversion recovery prepared UTE (STAIR-UTE), and iterative decomposition of water-and-fat with echo-asymmetry and least-squares estimation (IDEAL-IQ).

ASSESSMENT

Fracture risk was calculated using Fracture-Risk-Assessment-Tool (FRAX). Region-of-interests (ROIs) were delineated on the trabecular area in the maps of bone-mineral-density, UTE-MTR, collagen-bound water proton-fraction (CBWPF), and bone-marrow fat fraction (BMFF).

STATISTICAL TESTS

Linear-regression and Bland-Altman analysis were performed to assess the reproducibility of UTE-MTR measurements in the different scans. UTE-MTR and BMFF were correlated with bone-mineral-density using Pearson's regression and with FRAX scores using nonlinear regression. The abilities of UTE-MTR, CBWPF, and BMFF to discriminate between the three patient subgroups were evaluated using receiver-operator-characteristic (ROC) analysis and area-under-the-curve (AUC). Decision-curve-analysis (DCA) and clinical-impact curves were used to evaluate the value of UTE-MTR in clinical diagnosis. The DeLong test was used to compare the ROC curves. P-value <0.05 was considered statistically significant.

RESULTS

Excellent reproducibility was obtained for the UTE-MT measurements. UTE-MTR strongly correlated with bone-mineral-density (r = 0.76) and FRAX scores (r = -0.77). UTE-MTR exhibited higher AUCs (≥0.723) than BMFF, indicating its superior ability to distinguish between the three patient subgroups. The DCA and clinical-impact curves confirmed the diagnostic value of UTE-MTR. UTE-MTR and CBWPF showed similar performance in correlation with bone-mineral-density and cohort classification.

DATA CONCLUSION

UTE-MTR strongly correlates with bone-mineral-density and FRAX and shows great potential in distinguishing between normal, osteopenic, and osteoporotic subjects.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.

Simulation of a virtual liver iron overload model and R2 * estimation using multispectral fat-water models for GRE and UTE acquisitions at 1.5 T and 3 T

R2 *-MRI has emerged as a noninvasive alternative to liver biopsy for assessment of hepatic iron content (HIC). Multispectral fat-water R2 * modeling techniques such as the nonlinear least squares (NLSQ) fitting and autoregressive moving average (ARMA) models have been proposed for the accurate assessment of iron overload by also considering fat, which can otherwise confound R2 *-based HIC measurements in conditions of coexisting iron overload and steatosis. However, the R2 * estimation by these multispectral models has not been systematically investigated for various acquisition methods in iron overload only conditions and across the full clinically relevant range of HICs (0-40 mg Fe/g dry liver weight). The purpose of this study is to evaluate the R2 * accuracy and precision of multispectral models for various multiecho gradient echo (GRE) and ultrashort echo time (UTE) imaging acquisitions by constructing virtual iron overload models based on true histology and synthesizing MRI signals via Monte Carlo simulations at 1.5 T and 3 T, and comparing their results with monoexponential model and published in vivo R2 *-HIC calibrations. The signals were synthesized with TE1  = 1.0 ms for GRE and TE1  = 0.1 ms for UTE acquisition for varying echo spacing, ΔTE (0.1, 0.5, 1, 2 ms), and maximum echo time, TEmax (2, 4, 6, 10 ms). An iron-doped phantom study is also conducted to validate the simulation results in experimental GRE (TE1  = 1.2 ms, ΔTE  = 0.72 ms, TEmax  = 6.24 ms) and UTE (TE1  = 0.1 ms, ΔTE  = 0.5 ms, TEmax  = 6.1 ms) acquisitions. For GRE acquisitions, the multispectral ARMA and NLSQ models produced higher slopes (0.032-0.035) compared with the monoexponential model and published in vivo R2 *-HIC calibrations (0.025-0.028). However, for UTE acquisition for shorter echo spacing (≤0.5 ms) and longer maximum echo time, TEmax (≥6 ms), the multispectral and monoexponential signal models produced similar R2 *-HIC slopes (1.5 T, 0.028-0.032; 3 T, 0.014-0.016) and precision values (coefficient of variation < 25%) across the full clinical spectrum of HICs at both 1.5 T and 3 T. The phantom analysis also showed that all signal models demonstrated a significant improvement in R2 * estimation for UTE acquisition compared with GRE, confirming our simulation findings. Future work should investigate the performance of multispectral fat-water models by simulating liver models in coexisting conditions of iron overload and steatosis for accurate R2 * and fat quantification.

Free-breathing high isotropic resolution quantitative susceptibility mapping (QSM) of liver using 3D multi-echo UTE cones acquisition and respiratory motion-resolved image reconstruction

PURPOSE

To enable free-breathing and high isotropic resolution liver quantitative susceptibility mapping (QSM) using 3D multi-echo UTE cones acquisition and respiratory motion-resolved image reconstruction.

METHODS

Using 3D multi-echo UTE cones MRI, a respiratory motion was estimated from the k-space center of the imaging data. After sorting the k-space data with estimated motion, respiratory motion state-resolved reconstruction was performed for multi-echo data followed by nonlinear least-squares fitting for proton density fat fraction (PDFF),R 2 * $$ {\mathrm{R}}_2^{\ast } $$ , and fat-corrected B0 field maps. PDFF and B0 field maps were subsequently used for QSM reconstruction. The proposed method was compared with motion-averaged (gridding) reconstruction and conventional 3D multi-echo Cartesian MRI in moving gadolinium phantom and in vivo studies. Region of interest (ROI)-based linear regression analysis was performed on these methods to investigate correlations between gadolinium concentration and QSM in the phantom study and betweenR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and QSM in in vivo study.

RESULTS

Cones with motion-resolved reconstruction showed sharper image quality compared to motion-averaged reconstruction with a substantial reduction of motion artifacts in both moving phantom and in vivo studies. For ROI-based linear regression analysis of the phantom study, susceptibility values from cones with motion-resolved reconstruction (QSM ppm $$ {\mathrm{QSM}}_{\mathrm{ppm}} $$  = 0.31 × gadolinium mM + $$ \times {\mathrm{gadolinium}}_{\mathrm{mM}}+ $$ 0.05,R 2 $$ {R}^2 $$  = 0.999) and Cartesian without motion (QSM ppm $$ {\mathrm{QSM}}_{\mathrm{ppm}} $$  = 0.32× gadolinium mM + $$ \times {\mathrm{gadolinium}}_{\mathrm{mM}}+ $$ 0.04,R 2 $$ {R}^2 $$  = 1.000) showed linear relationships with gadolinium concentrations and showed good agreement with each other. For in vivo, motion-resolved reconstruction showed higher goodness of fit (QSM ppm $$ {\mathrm{QSM}}_{\mathrm{ppm}} $$  = 0.00261 × R 2 s - 1 * - $$ \times {\mathrm{R}}_{2_{{\mathrm{s}}^{-1}}}^{\ast }- $$ 0.524,R 2 $$ {R}^2 $$  = 0.977) compared to motion-averaged reconstruction (QSM ppm $$ {\mathrm{QSM}}_{\mathrm{ppm}} $$ = 0.0021 × R 2 s - 1 * - $$ \times {\mathrm{R}}_{2_{{\mathrm{s}}^{-1}}}^{\ast }- $$ 0.572,R 2 $$ {R}^2 $$ = 0.723) in ROI-based linear regression analysis betweenR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and QSM.

CONCLUSION

Feasibility of free-breathing liver QSM was demonstrated with motion-resolved 3D multi-echo UTE cones MRI, achieving high isotropic resolution currently unachievable in conventional Cartesian MRI.

Quantitative MRI of diffuse liver diseases: techniques and tissue-mimicking phantoms

Quantitative magnetic resonance imaging (MRI) techniques are emerging as non-invasive alternatives to biopsy for assessment of diffuse liver diseases of iron overload, steatosis and fibrosis. For testing and validating the accuracy of these techniques, phantoms are often used as stand-ins to human tissue to mimic diffuse liver pathologies. However, currently, there is no standardization in the preparation of MRI-based liver phantoms for mimicking iron overload, steatosis, fibrosis or a combination of these pathologies as various sizes and types of materials are used to mimic the same liver disease. Liver phantoms that mimic specific MR features of diffuse liver diseases observed in vivo are important for testing and calibrating new MRI techniques and for evaluating signal models to accurately quantify these features. In this study, we review the liver morphology associated with these diffuse diseases, discuss the quantitative MR techniques for assessing these liver pathologies, and comprehensively examine published liver phantom studies and discuss their benefits and limitations.

Radiomics nomograms based on R2* mapping and clinical biomarkers for staging of liver fibrosis in patients with chronic hepatitis B: a single-center retrospective study

OBJECTIVES

To investigate the value of R2* mapping-based radiomics nomograms in staging liver fibrosis in patients with chronic hepatitis B.

METHODS

Between January 2020 and December 2020, 151 patients with chronic hepatitis B were randomly divided into training (n = 103) and validation (n = 48) cohorts. From January to February 2021, 58 patients were included in a test cohort. Radiomics features were selected using the interclass correlation coefficient and least absolute shrinkage and selection operator method. Three radiomics nomograms, combining the radiomics score (Radscore) derived from R2* mapping and clinical variables, were used for staging significant and advanced fibrosis, and cirrhosis. Performance of the model was evaluated using the AUC. The utility and clinical benefits were evaluated using the continuous net reclassification index (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA).

RESULTS

The Radscore calculated by 12 radiomics features and independent factors (laminin and platelet) of advanced fibrosis were used to construct the radiomics nomograms. In the test cohort, the AUCs of the radiomics nomograms for staging significant fibrosis, advanced fibrosis, and cirrhosis were 0.738 (95% confidence interval [CI]: 0.604-0.872), 0.879 (95% CI: 0.779-0.98), and 0.952 (95% CI: 0.878-1), respectively. NRI, IDI, and DCA confirmed that radiomics nomograms demonstrated varying degrees of clinical benefit and improvement for advanced fibrosis and cirrhosis, but not for significant fibrosis.

CONCLUSIONS

Radiomics nomograms combined with R2* mapping-based Radscore, laminin, and platelet have value in staging advanced fibrosis and cirrhosis but limited value for staging significant fibrosis.

KEY POINTS

• Laminin and platelets were independent predictors of advanced fibrosis. • Radiomics analysis based on R2* mapping was beneficial for evaluating advanced fibrosis and cirrhosis. • It was difficult to distinguish significant fibrosis using a radiomics nomogram, which is possibly due to the complex pathological microenvironment of chronic liver diseases.