Ultra-short echo time images quantify high liver iron

Assessing the accuracy of CMRtools software for diagnosing liver iron overload in thalassemia patients: influencing factors and optimisation strategies

Background

CMRtools is a software package that can be used to measure T2* values to diagnose liver iron overload, however, its accuracy in terms is affected by multiple factors, including goodness-of-fit (R2 value), the number of echo time (TE) images, and the liver iron concentration (LIC). To investigate the effects of the R2 value, the number of TE images, and the LIC on the accuracy of CMRtools software for measuring T2* values to diagnose liver iron overload (LIO).

Materials and methods

CMRtools software was used to measure liver T2* values among 108 thalassemia patients via the truncation method, and the R2 values, the number of TE images, and T2* values were recorded. These values were subsequently converted into liver iron concentration (LICT) values. The LICF (derived from MRI-R2/FerriScan) was used as a reference, and the diagnostic accordance rate (DAR) was compared between R2 value subgroups, between TE image number subgroups, and between LIC subgroups.

Results

The greater the R2 value was, the greater the standardized DAR (SDAR) was (p < 0.05). The SDAR are not identical between each TE image number subgroup (p > 0.05). However, the relationship between TE image number subgroups and SDAR was analysed using Spearman's correlation, and it was found to be positively correlated (rs  = 0.729, p = 0.017). The SDAR are not identical between each LIC subgroup (p > 0.05), furthermore, the relationship between LIC subgroup and SDAR was found irrelevant (p = 0.747).

Conclusion

The accuracy of CMRtools software for diagnosing LIO in patients with thalassemia can be improved by artificially controlling the number of TE images to be fitted and selecting higher R2 values.

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.

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.

High-resolution 3D ultra-short echo time MRI with Rosette k-space pattern for brain iron content mapping

BACKGROUND

The iron concentration increases during normal brain development and is identified as a risk factor for many neurodegenerative diseases, it is vital to monitor iron content in the brain non-invasively.

PURPOSE

This study aimed to quantify in vivo brain iron concentration with a 3D rosette-based ultra-short echo time (UTE) magnetic resonance imaging (MRI) sequence.

METHODS

A cylindrical phantom containing nine vials of different iron concentrations (iron (II) chloride) from 0.5 millimoles to 50 millimoles and six healthy subjects were scanned using 3D high-resolution (0.94 ×0.94 ×0.94 mm3) rosette UTE sequence at an echo time (TE) of 20 μs.

RESULTS

Iron-related hyperintense signals (i.e., positive contrast) were detected based on the phantom scan, and were used to establish an association between iron concentration and signal intensity. The signal intensities from in vivo scans were then converted to iron concentrations based on the association. The deep brain structures, such as the substantia nigra, putamen, and globus pallidus, were highlighted after the conversion, which indicated potential iron accumulations.

CONCLUSION

This study suggested that T1-weighted signal intensity could be used for brain iron mapping.

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.

Ultra-short T2 components imaging of the whole brain using 3D dual-echo UTE MRI with rosette k-space pattern

PURPOSE

This study aimed to develop a new 3D dual-echo rosette k-space trajectory, specifically designed for UTE MRI applications. The imaging of the ultra-short transverse relaxation time (uT₂ ) of brain was acquired to test the performance of the proposed UTE sequence.

THEORY AND METHODS

The rosette trajectory was developed based on rotations of a "petal-like" pattern in the k_x -k_y plane, with oscillated extensions in the k_z -direction for 3D coverage. Five healthy volunteers underwent 10 dual-echo 3D rosette UTE scans with various TEs. Dual-exponential complex model fitting was performed on the magnitude data to separate uT₂ signals, with the output of uT₂ fraction, uT₂ value, and long-T₂ value.

RESULTS

The 3D rosette dual-echo UTE sequence showed better performance than a 3D radial UTE acquisition. More significant signal intensity decay in white matter than gray matter was observed along with the TEs. The white matter regions had higher uT₂ fraction values than gray matter (10.9% ± 1.9% vs. 5.7% ± 2.4%). The uT₂ value was approximately 0.10 ms in white matter .

CONCLUSION

The higher uT₂ fraction value in white matter compared to gray matter demonstrated the ability of the proposed sequence to capture rapidly decaying signals.

Quantitative abdominal magnetic resonance imaging in children-special considerations

The use of quantitative MRI methods for assessment of the abdomen in children has become commonplace over the past decade. Increasingly employed methods include MR elastography, chemical shift encoded (CSE) MR imaging for determination of proton density fat fraction, diffusion-weighted imaging, and a variety of relaxometry techniques, such as T1 and T2* mapping. These techniques can be used in a variety of settings to distinguish normal from abnormal tissue as well as determine the severity of disease. The performance of quantitative MRI methods in the pediatric population presents unique challenges as compared to adult populations. These challenges relate to multiple factors, including patient size, pediatric physiology, inability to breath hold, and greater physical motion during the examination. The purpose of this review article is to review quantitative MRI methods that may be used in clinical practice to assess the pediatric abdomen and to discuss special considerations when performing these techniques in children.

Hepatic Iron Quantification Using a Free-Breathing 3D Radial Gradient Echo Technique and Validation With a 2D Biopsy-Calibrated R2* Relaxometry Method

BACKGROUND

Hepatic iron content (HIC) is an important parameter for the management of iron overload. Non-invasive HIC assessment is often performed using biopsy-calibrated two-dimensional breath-hold Cartesian gradient echo (2D BH GRE) R2* -MRI. However, breath-holding is not possible in most pediatric patients or those with respiratory problems, and three-dimensional free-breathing radial GRE (3D FB rGRE) has emerged as a viable alternative.

PURPOSE

To evaluate the performance of a 3D FB rGRE and validate its R2* and fat fraction (FF) quantification with 3D breath-hold Cartesian GRE (3D BH cGRE) and biopsy-calibrated 2D BH GRE across a wide range of HICs.

STUDY TYPE

Retrospective.

SUBJECTS

Twenty-nine patients with hepatic iron overload (22 females, median age: 15 [5-25] years).

FIELD STRENGTH/SEQUENCE

Three-dimensional radial and 2D and 3D Cartesian multi-echo GRE at 1.5 T.

ASSESSMENT

R2* and FF maps were computed for 3D GREs using a multi-spectral fat model and 2D GRE R2* maps were calculated using a mono-exponential model. Mean R2* and FF values were calculated via whole-liver contouring and T2* -thresholding by three operators.

STATISTICAL TESTS

Inter- and intra-observer reproducibility was assessed using Bland-Altman and intraclass correlation coefficient (ICC). Linear regression and Bland-Altman analysis were performed to compare R2* and FF values among the three acquisitions. One-way repeated-measures ANOVA and Wilcoxon signed-rank tests, respectively, were used to test for significant differences between R2* and FF values obtained with different acquisitions. Statistical significance was assumed at P < 0.05.

RESULTS

The mean biases and ICC for inter- and intra-observer reproducibility were close to 0% and >0.99, respectively for both R2* and FF. The 3D FB rGRE R2* and FF values were not significantly different (P > 0.44) and highly correlated (R2  ≥ 0.98) with breath-hold Cartesian GREs, with mean biases ≤ ±2.5% and slopes 0.90-1.12. In non-breath-holding patients, Cartesian GREs showed motion artifacts, whereas 3D FB rGRE exhibited only minimal streaking artifacts.

DATA CONCLUSION

Free-breathing 3D radial GRE is a viable alternative in non-breath-hold patients for accurate HIC estimation.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Biopsy-based optimization and calibration of a signal-intensity-ratio-based MRI method (1.5 Tesla) in a dextran-iron loaded mini-pig model, enabling estimation of very high liver iron concentrations

Objective

Magnetic resonance imaging (MRI)-based techniques for non-invasive assessing liver iron concentration (LIC) in patients with iron overload have a limited upper measuring range around 35 mg/g dry weight, caused by signal loss from accelerated T1-, T2-, T2* shortening with increasing LIC. Expansion of this range is necessary to allow evaluation of patients with very high LIC.

Aim

To assess measuring range of a gradient-echo R2* method and a T1-weighted spin-echo (SE), signal intensity ratio (SIR)-based method (TE = 25 ms, TR = 560 ms), and to extend the upper measuring range of the SIR method by optimizing echo time (TE) and repetition time (TR) in iron-loaded minipigs.

Methods

Thirteen mini pigs were followed up during dextran-iron loading with repeated percutaneous liver biopsies for chemical LIC measurement and MRIs for parallel non-invasive estimation of LIC (81 examinations) using different TEs and TRs.

Results

SIR and R2* method had similar upper measuring range around 34 mg/g and similar method agreement. Using TE = 12 ms and TR = 1200 ms extended the upper measuring range to 115 mg/g and yielded good method of agreement.

Discussion

The wider measuring range is likely caused by lesser sensitivity of the SE sequence to iron, due to shorter TE, leading to later signal loss at high LIC, allowing evaluation of most severe hepatic iron overload. Validation in iron-loaded patients is necessary.

Pituitary Volume and Iron Overload Evaluation by 3T MRI in Thalassemia

OBJECTIVE

To evaluate pituitary volume and iron overload in beta thalassemia major, with the objective of assessing the reliability of this method in predicting hypogonadism.

METHODS

3T MRI was used to measure pituitary R2 and T2* in 57 beta thalassemia major patients and 30 controls. Anterior pituitary volume was evaluated by MRI planimetry. Cardiac, hepatic, and pancreatic iron overload were also assessed using MRI T2*. Mean serum ferritin was estimated by sandwich immuno-assay. Short stature was defined as height < 3 rd percentile for age, and clinical hypogonadism defined as absence of secondary sexual characteristics at ages ≥ 13 y for females and ≥ 14 y for males.

RESULTS

Short stature was present in 32 patients (56.1%). Of the 47 patients in the pubertal age group, 11(23.4%) had hypogonadism. Serum ferritin correlated positively with pituitary R2 (p = 0.004) and negatively with anterior pituitary volume (p = 0.006), whereas pituitary R2 correlated negatively with cardiac T2* (p = 0.001). Patients with hypogonadism had lower pituitary R2 (p = 0.186), T2* (p = 0.048), and anterior pituitary volumes (p = 0.012) compared to those with normal sexual maturity. Regardless of stature, no significant difference was observed between pituitary R2 (p = 0.267) and T2* (p = 0.451). Mean pituitary R2 in patients (78.99 Hz) was higher than in controls (20.8 Hz) (p = 0.0001). Anterior pituitary volume was lower in patients (264.83 mm³) than in controls (380.87 mm³) (p = 0.0001). A threshold value of 22.85 Hz for pituitary R2 gave a sensitivity of 84.2% and a specificity of 73.3% in distinguishing pituitary iron content of patients from controls, with an area of 0.864 under the ROC curve.

CONCLUSIONS

3T MRI is a reliable method to detect pituitary iron overload and predict risk of hypogonadism in beta Thalassemia.

MRI-based R2* mapping in patients with suspected or known iron overload

PURPOSE

R2* relaxometry is a quantitative method for assessment of iron overload. The purpose is to analyze the cross-sectional relationships between R2* in organs across patients with primary and secondary iron overload. Secondary analyses were conducted to analyze R2* according to treatment regimen.

METHODS

This is a retrospective, cross-sectional, institutional review board-approved study of eighty-one adult patients with known or suspected iron overload. R2* was measured by segmenting the liver, spleen, bone marrow, pancreas, renal cortex, renal medulla, and myocardium using breath-hold multi-echo gradient-recalled echo imaging at 1.5 T. Phlebotomy, transfusion, and chelation therapy were documented. Analyses included correlation, Kruskal-Wallis, and post hoc Dunn tests. p < 0.01 was considered significant.

RESULTS

Correlations between liver R2* and that of the spleen, bone marrow, pancreas, and heart were respectively 0.49, 0.33, 0.27, and 0.34. R2* differed between patients with primary and secondary overload in the liver (p < 0.001), spleen (p < 0.001), bone marrow (p < 0.01), renal cortex (p < 0.001), and renal medulla (p < 0.001). Liver, spleen, and bone marrow R2* were higher in thalassemia than in hereditary hemochromatosis (all p < 0.01). Renal cortex R2* was higher in sickle cell disease than in hereditary hemochromatosis (p < 0.001) and in thalassemia (p < 0.001). Overall, there was a trend toward lower liver R2* in patients assigned to phlebotomy and higher liver R2* in patients assigned to transfusion and chelation therapy.

CONCLUSION

R2* relaxometry revealed differences in degree or distribution of iron overload between organs, underlying etiologies, and treatment.

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

PURPOSE

To enable motion-robust, ungated, free-breathing R 2 ∗ mapping of hepatic iron overload in children with 3D multi-echo UTE cones MRI.

METHODS

A golden-ratio re-ordered 3D multi-echo UTE cones acquisition was developed with chemical-shift encoding (CSE). Multi-echo complex-valued source images were reconstructed via gridding and coil combination, followed by confounder-corrected R 2 ∗ (=1/ T 2 ∗ ) mapping. A phantom containing 15 different concentrations of gadolinium solution (0-300 mM) was imaged at 3T. 3D multi-echo UTE cones with an initial TE of 0.036 ms and Cartesian CSE-MRI (IDEAL-IQ) sequences were performed. With institutional review board approval, 85 subjects (81 pediatric patients with iron overload + 4 healthy volunteers) were imaged at 3T using 3D multi-echo UTE cones with free breathing (FB cones), IDEAL-IQ with breath holding (BH Cartesian), and free breathing (FB Cartesian). Overall image quality of R 2 ∗ maps was scored by 2 blinded experts and compared by a Wilcoxon rank-sum test. For each pediatric subject, the paired R 2 ∗ maps were assessed to determine if a corresponding artifact-free 15 mm region-of-interest (ROI) could be identified at a mid-liver level on both images. Agreement between resulting R 2 ∗ quantification from FB cones and BH/FB Cartesian was assessed with Bland-Altman and linear correlation analyses.

RESULTS

ROI-based regression analysis showed a linear relationship between gadolinium concentration and R 2 ∗ in IDEAL-IQ (y = 8.83x - 52.10, R2 = 0.995) as well as in cones (y = 9.19x - 64.16, R2 = 0.992). ROI-based Bland-Altman analysis showed that the mean difference (MD) was 0.15% and the SD was 5.78%. However, IDEAL-IQ R 2 ∗ measurements beyond 200 mM substantially deviated from a linear relationship for IDEAL-IQ (y = 5.85x + 127.61, R2 = 0.827), as opposed to cones (y = 10.87x - 166.96, R2 = 0.984). In vivo, FB cones R 2 ∗ had similar image quality with BH and FB Cartesian in 15 and 42 cases, respectively. FB cones R 2 ∗ had better image quality scores than BH and FB Cartesian in 3 and 21 cases, respectively, where BH/FB Cartesian exhibited severe ghosting artifacts. ROI-based Bland-Altman analyses were 2.23% (MD) and 6.59% (SD) between FB cones and BH Cartesian and were 0.21% (MD) and 7.02% (SD) between FB cones and FB Cartesian, suggesting a good agreement between FB cones and BH (FB) Cartesian R 2 ∗ . Strong linear relationships were observed between BH Cartesian and FB cones (y = 1.00x + 1.07, R2 = 0.996) and FB Cartesian and FB cones (y = 0.98x + 1.68, R2 = 0.999).

CONCLUSION

Golden-ratio re-ordered 3D multi-echo UTE Cones MRI enabled motion-robust, ungated, and free-breathing R 2 ∗ mapping of hepatic iron overload, with comparable R 2 ∗ measurements and image quality to BH Cartesian, and better image quality than FB Cartesian.

Quantitative magnetic resonance imaging for chronic liver disease

Chronic liver disease (CLD) has rapidly increased in prevalence over the past two decades, resulting in significant morbidity and mortality worldwide. Historically, the clinical gold standard for diagnosis, assessment of severity, and longitudinal monitoring of CLD has been liver biopsy with histological analysis, but this approach has limitations that may make it suboptimal for clinical and research settings. Magnetic resonance (MR)-based biomarkers can overcome the limitations by allowing accurate, precise, and quantitative assessment of key components of CLD without the risk of invasive procedures. This review briefly describes the limitations associated with liver biopsy and the need for non-invasive biomarkers. It then discusses the current state-of-the-art for MRI-based biomarkers of liver iron, fat, and fibrosis, and inflammation.

R1ρ at high spin-lock frequency could be a complementary imaging biomarker for liver iron overload quantification

PURPOSE

To compare the correlations among the R1ρ, R2, and R2* relaxation rates with liver iron concentration (LIC) in the assessment of rat liver iron content and explore the application potential of R1ρ in assessing liver iron content.

METHODS

Iron dextran (dosage of 0, 25, 50, 100, and 200 mg/kg body weight) was injected into 35 male rats to increase the amount of iron storage in the liver. After one week, all rats were euthanized with isoflurane. A portion of the largest hepatic lobe was extracted to quantify the LIC by inductively coupled plasma, and the remaining liver tissue was stored in 4% buffered paraformaldehyde for 24 h before MRI. Spin-lock preparation with a RARE (rapid acquisition with relaxation enhancement) readout (9 different spin-lock times and 7 different spin-lock frequencies (FSLs)) and multi-echo UTE (ultrashort TE) pulses were developed to quantify R1ρ and R2 * on a Bruker 11.7 T MR system. For comparisons with R1ρ and R2*, R2 was acquired using the CPMG sequence.

RESULTS

Mean R1ρ values displayed dispersion, with decrease in R1ρ at higher FSLs. Spearman's correlation analysis (two-tailed) indicated that the R1ρ values were significantly associated with LIC at FSL = 2000, 2500, and 3000 Hz (r = 0.365 and P = 0.031, r = 0.608 and P < 0.001, and r = 0.764 and P < 0.001, respectively), and were not significantly associated with LIC at FSL = 500, 1000, 1250, and 1500 Hz (all P > 0.05). R2 and R2* showed significant linear correlations with LIC (r = 0.787 and P < 0.001, and r = 0.859 and P < 0.001, respectively). Correlation analysis across R1ρ, R2, and R* also suggested that the correlation strength between R1ρ and R2 and between R1ρ and R* showed an increasing trend with increase in FSL.

CONCLUSION

In this study, a strong association was observed between R1ρ and LIC at high FSLs further confirming previous findings. The results demonstrated that R1ρ at high FSL might serve as a complementary imaging biomarker for liver iron overload quantification.

Real-World Experience Measurement of Liver Iron Concentration by R2 vs. R2 Star MRI in Hemoglobinopathies

Background: Non-invasive determination of liver iron concentration (LIC) is a valuable tool that guides iron chelation therapy in transfusion-dependent patients. Multiple methods have been utilized to measure LIC by MRI. The purpose of this study was to compare free breathing R2* (1/T2*) to whole-liver Ferriscan R2 method for estimation of LIC in a pediatric and young adult population who predominantly have hemoglobinopathies. Methods: Clinical liver and cardiac MRI scans from April 2016 to May 2018 on a Phillips 1.5 T scanner were reviewed. Free breathing T2 and T2* weighted images were acquired on each patient. For T2, multi-slice spin echo sequences were obtained. For T2*, a single mid-liver slice fast gradient echo was performed starting at 0.6 ms with 1.2 ms increments with signal averaging. R2 measurements were performed by Ferriscan analysis. R2* measurements were performed by quantitative T2* map analysis. Results: 107 patients underwent liver scans with the following diagnoses: 76 sickle cell anemia, 20 Thalassemia, 9 malignancies and 2 Blackfan Diamond anemia. Mean age was 12.5 ± 4.5 years. Average scan time for R2 sequences was 10 min, while R2* sequence time was 20 s. R2* estimation of LIC correlated closely with R2 with a correlation coefficient of 0.94. Agreement was strongest for LIC < 15 mg Fe/g dry weight. Overall bias from Bland–Altman plot was 0.66 with a standard deviation of 2.8 and 95% limits of agreement −4.8 to 6.1. Conclusion: LIC estimation by R2* correlates well with R2-Ferriscan in the pediatric age group. Due to the very short scan time of R2*, it allows imaging without sedation or anesthesia. Cardiac involvement was uncommon in this cohort.

Complex confounder-corrected R2* mapping for liver iron quantification with MRI

OBJECTIVES

MRI-based R2* mapping may enable reliable and rapid quantification of liver iron concentration (LIC). However, the performance and reproducibility of R2* across acquisition protocols remain unknown. Therefore, the objective of this work was to evaluate the performance and reproducibility of complex confounder-corrected R2* across acquisition protocols, at both 1.5 T and 3.0 T.

METHODS

In this prospective study, 40 patients with suspected iron overload and 10 healthy controls were recruited with IRB approval and informed written consent and imaged at both 1.5 T and 3.0 T. For each subject, acquisitions included four different R2* mapping protocols at each field strength, and an FDA-approved R2-based method performed at 1.5 T as a reference for LIC. R2* maps were reconstructed from the complex data acquisitions including correction for noise effects and fat signal. For each subject, field strength, and R2* acquisition, R2* measurements were performed in each of the nine liver Couinaud segments and the spleen. R2* measurements were compared across protocols and field strength (1.5 T and 3.0 T), and R2* was calibrated to LIC for each acquisition and field strength.

RESULTS

R2* demonstrated high reproducibility across acquisition protocols (p > 0.05 for 96/108 pairwise comparisons across 2 field strengths and 9 liver segments, ICC > 0.91 for each field strength/segment combination) and high predictive ability (AUC > 0.95 for four clinically relevant LIC thresholds). Calibration of R2* to LIC was LIC = - 0.04 + 2.62 × 10^-2 R2* at 1.5 T and LIC = 0.00 + 1.41 × 10^-2 R2* at 3.0 T.

CONCLUSIONS

Complex confounder-corrected R2* mapping enables LIC quantification with high reproducibility across acquisition protocols, at both 1.5 T and 3.0 T.

KEY POINTS

• Confounder-corrected R2* of the liver provides reproducible R2* across acquisition protocols, including different spatial resolutions, echo times, and slice orientations, at both 1.5 T and 3.0 T. • For all acquisition protocols, high correlation with R2-based liver iron concentration (LIC) quantification was observed. • The calibration between confounder-corrected R2* and LIC, at both 1.5 T and 3.0 T, is determined in this study.

Hepcidin-mediated Iron Regulation in P19 Cells is Detectable by Magnetic Resonance Imaging

Magnetic resonance imaging can be used to track cellular activities in the body using iron-based contrast agents. However, multiple intrinsic cellular iron handling mechanisms may also influence the detection of magnetic resonance (MR) contrast: a need to differentiate among those mechanisms exists. In hepcidin-mediated inflammation, for example, downregulation of iron export in monocytes and macrophages involves post-translational degradation of ferroportin. We examined the influence of hepcidin endocrine activity on iron regulation and MR transverse relaxation rates in multi-potent P19 cells, which display high iron import and export activities, similar to alternatively-activated macrophages. Iron import and export were examined in cultured P19 cells in the presence and absence of iron-supplemented medium, respectively. Western blots indicated the levels of transferrin receptor, ferroportin and ubiquitin in the presence and absence of extracellular hepcidin. Total cellular iron was measured by inductively-coupled plasma mass spectrometry and correlated to transverse relaxation rates at 3 Tesla using a gelatin phantom. Under varying conditions of iron supplementation, the level of ferroportin in P19 cells responds to hepcidin regulation, consistent with degradation through a ubiquitin-mediated pathway. This response of P19 cells to hepcidin is similar to that of classically-activated macrophages. The correlation between total cellular iron content and MR transverse relaxation rates was different in hepcidin-treated and untreated P19 cells: slope, Pearson correlation coefficient and relaxation rate were all affected. These findings may provide a tool to non-invasively distinguish changes in endogenous iron contrast arising from hepcidin-ferroportin interactions, with potential utility in monitoring of different macrophage phenotypes involved in pro- and anti-inflammatory signaling. In addition, this work demonstrates that transverse relaxivity is not only influenced by the amount of cellular iron but also by its metabolism.

Topics on quantitative liver magnetic resonance imaging

Liver magnetic resonance imaging (MRI) is subject to continuous technical innovations through advances in hardware, sequence and novel contrast agent development. In order to utilize the abilities of liver MR to its full extent and perform high-quality efficient exams, it is mandatory to use the best imaging protocol, to minimize artifacts and to select the most adequate type of contrast agent. In this article, we review the routine clinical MR techniques applied currently and some latest developments of liver imaging techniques to help radiologists and technologists to better understand how to choose and optimize liver MRI protocols that can be used in clinical practice. This article covers topics on (I) fat signal suppression; (II) diffusion weighted imaging (DWI) and intravoxel incoherent motion (IVIM) analysis; (III) dynamic contrast-enhanced (DCE) MR imaging; (IV) liver fat quantification; (V) liver iron quantification; and (VI) scan speed acceleration.

Short-T2 MRI: Principles and recent advances

Among current modalities of biomedical and diagnostic imaging, MRI stands out by virtue of its versatile contrast obtained without ionizing radiation. However, in various cases, e.g., water protons in tissues such as bone, tendon, and lung, MRI performance is limited by the rapid decay of resonance signals associated with short transverse relaxation times T₂ or T₂*. Efforts to address this shortcoming have led to a variety of specialized short-T₂ techniques. Recent progress in this field expands the choice of methods and prompts fresh considerations with regard to instrumentation, data acquisition, and signal processing. In this review, the current status of short-T₂ MRI is surveyed. In an attempt to structure the growing range of techniques, the presentation highlights overarching concepts and basic methodological options. The most frequently used approaches are described in detail, including acquisition strategies, image reconstruction, hardware requirements, means of introducing contrast, sources of artifacts, limitations, and applications.

Characterizing a short T2 * signal component in the liver using ultrashort TE chemical shift-encoded MRI at 1.5T and 3.0T

PURPOSE

Recent studies have suggested the presence of short-T₂ * signals in the liver, which may confound chemical shift-encoded (CSE) fat quantification when using short echo times (TEs). The purpose of this study was to characterize the liver signal at short echo times and to determine its impact on liver fat quantification.

METHODS

An ultrashort echo time (UTE) chemical shift-encoded MRI (CSE-MRI) technique and a multicomponent reconstruction were developed to characterize short-T₂ * liver signals. Subsequently, liver fat fraction was quantified using a short-TE (first TE = 0.7 ms) and UTE CSE-MRI acquisitions and compared with a standard CSE-MRI (first TE = 1.2 ms).

RESULTS

Short-T₂ * signals were consistently observed in the liver of all healthy volunteers imaged at both 1.5T and 3.0T. At 3.0T, short-T₂ * signal fractions of 9.6 ± 1.5%, 7.0 ± 1.7%, and 7.4 ± 1.7% with T₂ * of 0.23 ± 0.05 ms, 0.20 ± 0.05 ms, and 0.10 ± 0.02 ms were measured in healthy volunteers, patients with liver cirrhotic disease, and patients with hepatic steatosis (but no cirrhosis), respectively. For proton density fat fraction (PDFF) estimation, 1.7% (P < .01) and 3.4% (P < .01) biases were observed in subjects imaged using short-TE CSE-MRI and using UTE CSE-MRI at 1.5T, respectively. The biases were reduced to 0.4% and -0.7%, respectively, by excluding short echoes less than 1 ms. A 3.2% bias (P < .01) was observed in subjects imaged using UTE CSE-MRI at 3.0T, which was reduced to 0.1% by excluding short echoes <1 ms.

CONCLUSIONS

A liver short-T₂ * signal component was consistently observed and was shown to confound liver fat quantification when short echo times were used with CSE-MRI.

Protocol optimization for cardiac and liver iron content assessment using MRI: What sequence should I use?

OBJECTIVE

To determine the optimal MRI protocol and sequences for liver and cardiac iron estimation in children.

METHODS

We evaluated patients ≤18 years with cardiac and liver MRIs for iron content estimation. Liver T2 was determined by a third-party company. Cardiac and Liver T2* values were measured by an observer. Liver T2* values were calculated using the available liver parenchyma in the cardiac MRI. Linear correlations and Bland-Altman plots were run between liver T2 and T2*, cardiac T2* values; and liver T2* on dedicated cardiac and liver MRIs.

RESULTS

139 patients were included. Mean liver T2 and T2* values were 8.6 ± 5.4 ms and 4.5 ± 4.1 ms, respectively. A strong correlation between liver T2 and T2* values was observed (r = 0.96, p < 0.001) with a bias (+4.1 ms). Mean cardiac bright- and dark-blood T2* values were 26.5 ± 12.9 ms and 27.2 ± 11.9 ms, respectively. Cardiac T2* values showed a strong correlation (r = 0.81, p < 0.001) with a low bias (-1.0 ms). The mean liver T2* on liver and cardiac MRIs were 4.9 ± 4.7 ms and 4.6 ± 3.9 ms, respectively. A strong correlation between T2* values was observed (r = 0.96, p < 0.001) with a small bias (-0.2 ms).

CONCLUSION

MRI protocols for iron concentration in the liver and the heart can be simplified to avoid redundant information and reduce scan time. In most patients, a single breath-hold GRE sequence can be used to evaluate the iron concentration in both the liver and heart.

The application value of ultra-short echo time MRI in the quantification of liver iron overload in a rat model

Background

The quantitative evaluation of liver iron concentration (LIC) is important in guiding the treatment of blood transfusion-dependent patients. Conventionally, LIC is assessed through R2*or R2 values using magnetic resonance imaging (MRI). However, most of the studies using MRI to determine iron overload were restricted by the minimum echo time, so that severe iron overload could hardly be quantified. In our study, we demonstrate a new approach to overcome the limitation of the shortest echo time using ultra-short echo time (UTE) MRI to quantify liver iron overload of varying degrees in a rat model.

Methods

Sixty female Sprague-Dawley rats were included and randomly assigned into 10 equal groups. Group 1 was not injected with iron dextran. Groups 2 to 10 were intraperitoneally injected with iron dextran at a dose of 15 mg/kg every 3 days. On every 6th day, one group was randomly selected from groups 2 to 10 for MRI scanning and liver iron concentration (LIC) detection. For groups 1 to 10, images were acquired by UTE sequence using a 3.0T MR scanner, and the T2* value and R2* value were obtained (R2* =1/T2*). In addition, LIC was measured using an atomic absorption photometer. The correlation analysis between R2* value and LIC was performed and the regression equation of R2* and LIC was established and its reliability verified.

Results

For groups 1 to 10, R2* values and LIC ranged from 60.16±4.76 to 1,306.90±42.26 Hz and from 0.84±0.11 to 5.89±2.64 mg/g dry, respectively. The R2* value was linearly correlated to the LIC (r=0.897, P<0.001), and the linear regression equation was LIC = 0.005 × R2* + 1.783. The validation analysis results showed that the intragroup correlation coefficient (ICC) between the predicted and measured LIC was 89.5%.

Conclusions

The UTE sequence could be used for quantification of varying degrees of hepatic iron overload in the rat model, and the LIC could be predicted by using the R2* value on an MR 3.0T scanner.

Conical ultrashort echo time (UTE) MRI in the evaluation of pediatric acute appendicitis

PURPOSE

Magnetic resonance imaging (MRI) sequences with conical k-space trajectories are able to decrease motion artifacts while achieving ultrashort echo times (UTE). We assessed the performance of free-breathing conical UTE MRI in the evaluation of the pediatric pelvis for suspected appendicitis.

METHODS

Our retrospective review of 84 pediatric patients who underwent MRI for suspected appendicitis compared three contrast-enhanced sequences: free-breathing conical UTE, breath-hold three-dimensional (3D) spoiled gradient echo (BH-SPGR), and free-breathing high-resolution 3D SPGR (FB-SPGR). Two radiologists performed blinded and independent evaluations of each sequence for image quality (four point scale), anatomic delineation (four point scale), and diagnostic confidence (five point scale). Subsequently, the three sequences were directly compared for overall image quality (- 3 to + 3 scale). Scores were compared using Kruskal-Wallis and Wilcoxon signed-rank tests.

RESULTS

UTE demonstrated significantly better perceived signal-to-noise ratio (SNR) and fewer artifacts than BH-SPGR and FB-SPGR (means of 3.6 and 3.4, 3.4 and 3.2, 3.1 and 2.7, respectively; p < 0.0006). BH-SPGR and FB-SPGR demonstrated significantly better contrast than UTE (means of 3.6, 3.4, and 3.2, respectively; p < 0.03). In the remaining categories, UTE performed significantly better than FB-SPGR (p < 0.00001), while there was no statistical difference between UTE and BH-SPGR. Direct paired comparisons of overall image quality demonstrated the readers significantly preferred UTE over both BH-SPGR (mean + 0.5, p < 0.00001) and FB-SPGR (mean + 1.2, p < 0.00001).

CONCLUSIONS

In the evaluation of suspected appendicitis, free-breathing conical UTE MRI performed better in the assessed metrics than FB-SPGR. When compared to BH-SPGR, UTE demonstrated superior perceived SNR and fewer artifacts.

Ultrashort echo time imaging for quantification of hepatic iron overload: Comparison of acquisition and fitting methods via simulations, phantoms, and in vivo data

BACKGROUND

Current R2*-MRI techniques for measuring hepatic iron content (HIC) use various acquisition types and fitting models.

PURPOSE

To evaluate the accuracy and precision of R2*-HIC acquisition and fitting methods.

STUDY TYPE

Signal simulations, phantom study, and prospective in vivo cohort.

POPULATION

In all, 132 patients (58/74 male/female, mean age 17.7 years).

FIELD STRENGTH/SEQUENCE

2D-multiecho gradient-echo (GRE) and ultrashort echo time (UTE) acquisitions at 1.5T.

ASSESSMENT

Synthetic MR signals were created to mimic published GRE and UTE methods, using different R2* values (25-2000 s^-1 ) and signal-to-noise ratios (SNR). Phantoms with varying iron concentrations were scanned at 1.5T. In vivo data were analyzed from 132 patients acquired at 1.5T. R2* was estimated by fitting using three signal models. Accuracy and precision of R2* measurements for UTE acquisition parameters (SNR, echo spacing [ΔTE], maximum echo time [TE_max ]) and fitting methods were compared for simulated, phantom, and in vivo datasets.

STATISTICAL TESTS

R2* accuracy was determined from the relative error and by linear regression analysis. Precision was evaluated using coefficient of variation (CoV) analysis.

RESULTS

In simulations, all models had high R2* accuracy (error <5%) and precision (CoV <10%) for all SNRs, shorter ΔTE (≤0.5 msec), and longer TE_max (≥10.1 msec); except the constant offset model overestimated R2* at the lowest SNR. In phantoms and in vivo, all models produced similar R2* values for different SNRs and shorter ΔTEs (slopes: 0.99-1.06, R² > 0.99, P < 0.001). In all experiments, R2* results degraded for high R2* values with longer ΔTE (≥1 msec). In vivo, shorter and longer TE_max gave similar R2* results (slopes: 1.02-1.06, R² > 0.99, P < 0.001) for the noise subtraction model for 25≤R2*≤2000 s^-1 . However, both quadratic and constant offset models, using shorter TE_max (≤4.7 msec) overestimated R2* and yielded high CoVs up to ∼170% for low R2* (<250 s^-1 ).

DATA CONCLUSION

UTE with TE_max ≥ 10.1 msec and ΔTE ≤ 0.5 msec yields accurate R2* estimates over the entire clinical HIC range. Monoexponential fitting with noise subtraction is the most robust signal model to changes in UTE parameters and achieves the highest R2* accuracy and precision.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1475-1488.

Measuring liver T2* and cardiac T2* in a single acquisition

PURPOSE

The purpose of this study is determine if both liver T2* and cardiac T2* can be measured on a single breath-hold acquisition.

MATERIALS AND METHODS

For this IRB-approved retrospective study, 137 patients with dedicated Cardiac MRI and Liver MRI examinations obtained sequentially on 1.5T scanners and on the same day were included for analysis. Both the cardiac and liver MRI examinations utilized GRE sequences for quantification of tissue iron. Specifically, T2* was measured using an 8-echo, multi-echo gradient echo single breath-hold sequence. Liver T2* was measured in a blinded manner on images from each of the cardiac and dedicated liver MRI examinations and were correlated. Bland-Altman difference plot was used to assess mean bias.

RESULTS

137 examinations from 93 subjects met inclusion criteria. 10 examination pairs were excluded because the first echo time (TE) on the cardiac MRI was insufficiently short for the very high liver iron content. After exclusion, 127 studies from 89 subjects (67.4% males) were included in the final analysis. The mean subject age (± standard deviation) was 11.5 ± 7.5 years (range 0-29.3 years; median 10.5 years). Mean liver T2* measured on cardiac MRI was 8.3 ± 7.7 ms and mean liver T2* measured on dedicated liver MRI was 7.8 ± 7.4 ms (p < 0.001). There was strong positive correlation between the two liver T2* measurements (r = 0.989, p < 0.0001; 95% CI 0.985-0.992). With the exception of borderline outliers, all values fell within two standard deviations on the Bland-Altman difference plots, with a mean bias of 0.5 ms (range - 1.8 to + 2.7 ms).

CONCLUSION

In most patients with suspected or known iron overload, a single breath-hold GRE sequence may be sufficient to evaluate the iron concentration (T2*) of both the myocardium and the liver.

3D R 2 * mapping of the placenta during early gestation using free-breathing multiecho stack-of-radial MRI at 3T

BACKGROUND

Multiecho gradient-echo Cartesian MRI characterizes placental oxygenation by quantifying R 2 * . Previous research was performed at 1.5T using breath-held 2D imaging during later gestational age (GA).

PURPOSE

To evaluate the accuracy and repeatability of a free-breathing (FB) 3D multiecho gradient-echo stack-of-radial technique (radial) for placental R 2 * mapping at 3T and report placental R 2 * during early GA.

STUDY TYPE

Prospective.

POPULATION

Thirty subjects with normal pregnancies and three subjects with ischemic placental disease (IPD) were scanned twice: between 14-18 and 19-23 weeks GA.

FIELD STRENGTH

3T.

SEQUENCE

FB radial.

ASSESSMENT

Linear correlation (concordance coefficient, ρ_c ) and Bland-Altman analyses (mean difference, MD) were performed to evaluate radial R 2 * mapping accuracy compared to Cartesian in a phantom. Radial R 2 * mapping repeatability was characterized using the coefficient of repeatability (CR) between back-to-back scans. The mean and spatial coefficient of variation (CV) of R 2 * was determined for all subjects, and separately for anterior and posterior placentas, at each GA range.

STATISTICAL TESTS

ρ_c was tested for significance. Differences in mean R 2 * and CV were tested using Wilcoxon Signed-Rank and Rank-Sum tests. P < 0.05 was considered significant. Z-scores for the IPD subjects were determined.

RESULTS

FB radial demonstrated accurate (ρ_c ≥0.996; P < 0.001; |MD|<0.2s^-1 ) and repeatable (CR<4s^-1 ) R 2 * mapping in a phantom, and repeatable (CR≤4.6s^-1 ) R 2 * mapping in normal subjects. At 3T, placental R 2 * mean ± standard deviation was 12.9s^-1  ± 2.7s^-1 for 14-18 and 13.2s^-1  ± 1.9s^-1 for 19-23 weeks GA. The CV was significantly greater (P = 0.043) at 14-18 (0.63 ± 0.12) than 19-23 (0.58 ± 0.13) weeks GA. At 19-23 weeks, the CV was significantly lower (P < 0.001) for anterior (0.49 ± 0.08) than posterior (0.67 ± 0.11) placentas. One IPD subject had a lower mean R 2 * than normal subjects at both GA ranges (Z<-2).

DATA CONCLUSION

FB radial provides accurate and repeatable 3D R 2 * mapping for the entire placenta at 3T during early GA.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:291-303.

Free-breathing quantification of hepatic fat in healthy children and children with nonalcoholic fatty liver disease using a multi-echo 3-D stack-of-radial MRI technique

BACKGROUND

In adults, noninvasive chemical shift encoded Cartesian magnetic resonance imaging (MRI) and single-voxel magnetic resonance (MR) spectroscopy (SVS) accurately quantify hepatic steatosis but require breath-holding. In children, especially young and sick children, breath-holding is often limited or not feasible. Sedation can facilitate breath-holding but is highly undesirable. For these reasons, there is a need to develop free-breathing MRI technology that accurately quantifies steatosis in all children.

OBJECTIVE

This study aimed to compare non-sedated free-breathing multi-echo 3-D stack-of-radial (radial) MRI versus standard breath-holding MRI and SVS techniques in a group of children for fat quantification with respect to image quality, accuracy and repeatability.

MATERIALS AND METHODS

Healthy children (n=10, median age [±interquartile range]: 10.9 [±3.3] years) and overweight children with nonalcoholic fatty liver disease (NAFLD) (n=9, median age: 15.2 [±3.2] years) were imaged at 3 Tesla using free-breathing radial MRI, breath-holding Cartesian MRI and breath-holding SVS. Acquisitions were performed twice to assess repeatability (within-subject mean difference, MD_within). Images and hepatic proton-density fat fraction (PDFF) maps were scored for image quality. Free-breathing and breath-holding PDFF were compared using linear regression (correlation coefficient, r and concordance correlation coefficient, ρ_c) and Bland-Altman analysis (mean difference). P<0.05 was considered significant.

RESULTS

In patients with NAFLD, free-breathing radial MRI demonstrated significantly less motion artifacts compared to breath-holding Cartesian (P<0.05). Free-breathing radial PDFF demonstrated a linear relationship (P<0.001) versus breath-holding SVS PDFF and breath-holding Cartesian PDFF with r=0.996 and ρ_c=0.994, and r=0.997 and ρ_c=0.995, respectively. The mean difference in PDFF between free-breathing radial MRI, breath-holding Cartesian MRI and breath-holding SVS was <0.7%. Repeated free-breathing radial MRI had MD_within=0.25% for PDFF.

CONCLUSION

In this pediatric study, non-sedated free-breathing radial MRI provided accurate and repeatable hepatic PDFF measurements and improved image quality, compared to standard breath-holding MR techniques.

Iron deposition quantification: Applications in the brain and liver

Iron has long been implicated in many neurological and other organ diseases. It is known that over and above the normal increases in iron with age, in certain diseases there is an excessive iron accumulation in the brain and liver. MRI is a noninvasive means by which to image the various structures in the brain in three dimensions and quantify iron over the volume of the object of interest. The quantification of iron can provide information about the severity of iron-related diseases as well as quantify changes in iron for patient follow-up and treatment monitoring. This article provides an overview of current MRI-based methods for iron quantification, specifically for the brain and liver, including: signal intensity ratio, R₂ , R2*, R2', phase, susceptibility weighted imaging and quantitative susceptibility mapping (QSM). Although there are numerous approaches to measuring iron, R₂ and R2* are currently preferred methods in imaging the liver and QSM has become the preferred approach for imaging iron in the brain.

LEVEL OF EVIDENCE

5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018. J. MAGN. RESON. IMAGING 2018;48:301-317.