Quantitative ultrashort echo time imaging for assessment of massive iron overload at 1.5 and 3 Tesla

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.

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.

QSM Throughout the Body

Magnetic materials in tissue, such as iron, calcium, or collagen, can be studied using quantitative susceptibility mapping (QSM). To date, QSM has been overwhelmingly applied in the brain, but is increasingly utilized outside the brain. QSM relies on the effect of tissue magnetic susceptibility sources on the MR signal phase obtained with gradient echo sequence. However, in the body, the chemical shift of fat present within the region of interest contributes to the MR signal phase as well. Therefore, correcting for the chemical shift effect by means of water-fat separation is essential for body QSM. By employing techniques to compensate for cardiac and respiratory motion artifacts, body QSM has been applied to study liver iron and fibrosis, heart chamber blood and placenta oxygenation, myocardial hemorrhage, atherosclerotic plaque, cartilage, bone, prostate, breast calcification, and kidney stone.

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.

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.

Making the invisible visible-ultrashort echo time magnetic resonance imaging: Technical developments and applications

Magnetic resonance imaging (MRI) uses a large magnetic field and radio waves to generate images of tissues in the body. Conventional MRI techniques have been developed to image and quantify tissues and fluids with long transverse relaxation times (T2s), such as muscle, cartilage, liver, white matter, gray matter, spinal cord, and cerebrospinal fluid. However, the body also contains many tissues and tissue components such as the osteochondral junction, menisci, ligaments, tendons, bone, lung parenchyma, and myelin, which have short or ultrashort T2s. After radio frequency excitation, their transverse magnetizations typically decay to zero or near zero before the receiving mode is enabled for spatial encoding with conventional MR imaging. As a result, these tissues appear dark, and their MR properties are inaccessible. However, when ultrashort echo times (UTEs) are used, signals can be detected from these tissues before they decay to zero. This review summarizes recent technical developments in UTE MRI of tissues with short and ultrashort T2 relaxation times. A series of UTE MRI techniques for high-resolution morphological and quantitative imaging of these short-T2 tissues are discussed. Applications of UTE imaging in the musculoskeletal, nervous, respiratory, gastrointestinal, and cardiovascular systems of the body are included.

MRI for Liver Iron Quantification: Concepts and Current Methods

Liver Iron content is best correlated to total body iron stores and is thus the organ of choice for evaluation in iron overload diseases. Liver biopsy was the historic standard for iron evaluation, but the evaluation is localized, comes with increased risks due to its invasiveness, and is costly. MRI is now widely used for liver iron evaluation. The superparamagnetic properties of iron cause a disturbance in magnetic resonance imaging, which can be evaluated with various techniques. These include signal intensity ratio (SIR), T2 relaxometry, T2* relaxometry, and Dixon-based solutions. Each of the methods has its own advantages and disadvantages, and factors such as availability, ease of use, accuracy, reproducibility, and cost can all play a role in the ultimate technique used for liver iron quantification. Quantitative susceptibility mapping, and ultrashort TE sequences are promising supplemental methods, but are primarily used as research sequences. These may become more clinically accepted in the near future. Dual energy CT is also being explored as an alternative but is still in the nascent stages. Overall, accurate liver iron concentration is feasible with the current tools available at most MR imaging centers and is highly valuable for evaluation of iron overload diseases.

Assessment of iron nanoparticle distribution in mouse models using ultrashort-echo-time MRI

Microscopic magnetic field inhomogeneities caused by iron deposition or tissue-air interfaces may result in rapid decay of transverse magnetization in MRI. The aim of this study is to detect and quantify the distribution of iron-based nanoparticles in mouse models by applying ultrashort-echo-time (UTE) sequences in tissues exhibiting extremely fast transverse relaxation. In 24 C57BL/6 mice (two controls), suspensions containing either non-oxidic Fe or AuFeO_x nanoparticles were injected into the tail vein at two doses (200 μg and 600 μg per mouse). Mice underwent MRI using a UTE sequence at 4.7 T field strength with five different echo times between 100 μs and 5000 μs. Transverse relaxation times T₂ * were computed for the lung, liver, and spleen by mono-exponential fitting. In UTE imaging, the MRI signal could reliably be detected even in liver parenchyma exhibiting the highest deposition of nanoparticles. In animals treated with Fe nanoparticles (600 μg per mouse), the relaxation time substantially decreased in the liver (3418 ± 1534 μs (control) versus 228 ± 67 μs), the spleen (2170 ± 728 μs versus 299 ± 97 μs), and the lungs (663 ± 101 μs versus 413 ± 99 μs). The change in transverse relaxation was dependent on the number and composition of the nanoparticles. By pixel-wise curve fitting, T₂ * maps were calculated showing nanoparticle distribution. In conclusion, UTE sequences may be used to assess and quantify nanoparticle distribution in tissues exhibiting ultrafast signal decay in MRI.

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.

3 T: the good, the bad and the ugly

It is around 20 years since the first commercial 3 T MRI systems became available. The theoretical promise of twice the signal-to-noise ratio of a 1.5 T system together with a greater sensitivity to magnetic susceptibility-related contrast mechanisms, such as the blood oxygen level dependent effect that is the basis for functional MRI, drove the initial market in neuroradiology. However, the limitations of the increased field strength soon became apparent, including the increased radiofrequency power deposition, tissue-dependent changes in relaxation times, increased artifacts, and greater safety concerns. Many of these issues are dependent upon MR physics and workarounds have had to be developed to try and mitigate their effects. This article reviews the underlying principles of the good, the bad and the ugly aspects of 3 T, discusses some of the methods used to improve image quality and explains the remaining challenges and concerns.

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.

Energetic Basis for Exercise-Induced Pulmonary Congestion in Heart Failure With Preserved Ejection Fraction

BACKGROUND

Transient pulmonary congestion during exercise is emerging as an important determinant of reduced exercise capacity in heart failure with preserved ejection fraction (HFpEF). We sought to determine whether an abnormal cardiac energetic state underpins this process.

METHODS

We recruited patients across the spectrum of diastolic dysfunction and HFpEF (controls, n=11; type 2 diabetes, n=9; HFpEF, n=14; and severe diastolic dysfunction attributable to cardiac amyloidosis, n=9). Cardiac energetics were measured using phosphorus spectroscopy to define the myocardial phosphocreatine to ATP ratio. Cardiac function was assessed by cardiovascular magnetic resonance cine imaging and echocardiography and lung water using magnetic resonance proton density mapping. Studies were performed at rest and during submaximal exercise using a magnetic resonance imaging ergometer.

RESULTS

Paralleling the stepwise decline in diastolic function across the groups (E/e' ratio; P<0.001) was an increase in NT-proBNP (N-terminal pro-brain natriuretic peptide; P<0.001) and a reduction in phosphocreatine/ATP ratio (control, 2.15 [2.09, 2.29]; type 2 diabetes, 1.71 [1.61, 1.91]; HFpEF, 1.66 [1.44, 1.89]; cardiac amyloidosis, 1.30 [1.16, 1.53]; P<0.001). During 20-W exercise, lower left ventricular diastolic filling rates (r=0.58; P<0.001), lower left ventricular diastolic reserve (r=0.55; P<0.001), left atrial dilatation (r=-0.52; P<0.001), lower right ventricular contractile reserve (right ventricular ejection fraction change, r=0.57; P<0.001), and right atrial dilation (r=-0.71; P<0.001) were all linked to lower phosphocreatine/ATP ratio. Along with these changes, pulmonary proton density mapping revealed transient pulmonary congestion in patients with HFpEF (+4.4% [0.5, 6.4]; P=0.002) and cardiac amyloidosis (+6.4% [3.3, 10.0]; P=0.004), which was not seen in healthy controls (-0.1% [-1.9, 2.1]; P=0.89) or type 2 diabetes without HFpEF (+0.8% [-1.7, 1.9]; P=0.82). The development of exercise-induced pulmonary congestion was associated with lower phosphocreatine/ATP ratio (r=-0.43; P=0.004).

CONCLUSIONS

A gradient of myocardial energetic deficit exists across the spectrum of HFpEF. Even at low workload, this energetic deficit is related to markedly abnormal exercise responses in all 4 cardiac chambers, which is associated with detectable pulmonary congestion. The findings support an energetic basis for transient pulmonary congestion in HFpEF.

Free-breathing 3D stack-of-radial MRI quantification of liver fat and R2* in adults with fatty liver disease

PURPOSE

To investigate the agreement, intra-session repeatability, and inter-reader agreement of liver proton-density fat fraction (PDFF) and R₂* quantification using free-breathing 3D stack-of-radial MRI, with and without self-gated motion compensation, compared to reference breath-hold techniques in subjects with fatty liver disease (FLD).

METHODS

In this institutional review board-approved prospective study, thirty-eight adults with FLD and/or iron overload (24 male, 58 ± 12 years) were imaged at 3T using free-breathing stack-of-radial MRI, breath-hold 3D Cartesian MRI, and breath-hold single-voxel MR spectroscopy (SVS). Each sequence was acquired twice in random order. To assess agreement compared to reference breath-hold techniques, the dependency of liver PDFF and/or R₂* quantification on the sequence, radial sampling factor, and radial self-gating temporal resolution was assessed by calculating the Bayesian mean difference (MD_B) of the posteriors. Intra-session repeatability and inter-reader agreement (two independent readers) were assessed by the coefficient of repeatability (CR) and intraclass correlation coefficient (ICC), respectively.

RESULTS

Thirty-five participants (21 male, 57 ± 12 years) were included for analysis. Both free-breathing radial MRI techniques (with and without self-gating) achieved ICC ≥ 0.92 for quantifying PDFF and R₂*, and quantified PDFF with MD_B < 1.2% compared to breath-hold techniques. Free-breathing radial MRI required self-gating to accurately quantify R₂* (MD_B < 10s^-1 with self-gating; MD_B < 50s^-1 without self-gating). The radial sampling factor affected PDFF and R₂* quantification while the radial self-gating temporal resolution only affected R₂* quantification. Repeated self-gated free-breathing radial MRI scans achieved CR < 3% and CR < 27 s^-1 for PDFF and R₂*, respectively.

CONCLUSION

A free-breathing stack-of-radial MRI technique with self-gating demonstrated agreement, repeatability, and inter-reader agreement compared to reference breath-hold techniques for quantification of liver PDFF and R₂* in adults with FLD.

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 R 2 ∗ 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.

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.

Advances in Imaging of Diffuse Parenchymal Liver Disease

There are >1.5 billion people with chronic liver disease worldwide, causing liver diseases to be a significant global health issue. Diffuse parenchymal liver diseases, including hepatic steatosis, fibrosis, metabolic diseases, and hepatitis cause chronic liver injury and may progress to fibrosis and eventually hepatocellular carcinoma. As early diagnosis and treatment of these diseases impact the progression and outcome, the need for assessment of the liver parenchyma has increased. While the current gold standard for evaluation of the hepatic parenchymal tissue, biopsy has disadvantages and limitations. Consequently, noninvasive methods have been developed based on serum biomarkers and imaging techniques. Conventional imaging modalities such as ultrasound, computed tomography scan, and magnetic resonance imaging provide noninvasive options for assessment of liver tissue. However, several recent advances in liver imaging techniques have been introduced. This review article focuses on the current status of imaging methods for diffuse parenchymal liver diseases assessment including their diagnostic accuracy, advantages and disadvantages, and comparison between different techniques.

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.

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.

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.

Biexponential R2* relaxometry for estimation of liver iron concentration in children: A better fit for high liver iron states

BACKGROUND

R2* relaxometry's capacity to calculate liver iron concentration (LIC) is limited in patients with severe overload. Hemosiderin increases in these patients, which exhibits a non-monoexponential decay that renders a failed R2* analysis.

PURPOSE/HYPOTHESIS

To evaluate a biexponential R2* relaxometry model in children with different ranges of iron overload.

STUDY TYPE

Retrospective.

POPULATION

In all, 181 children with different conditions associated with iron overload.

FIELD STRENGTH/SEQUENCE

1.5T, T₂ *-weighted gradient echo sequence.

ASSESSMENT

Bi- and monoexponential R2* relaxometry were measured in the liver using two regions of interest (ROIs) using a nonproprietary software: one encompassing the whole liver parenchyma (ROI-1) and the other only the periphery (ROI-2). These were drawn by a single trained observer. The residuals for each fitting model were estimated. A ratio between the residuals of the mono- and biexponential models was calculated to identify the best fitting model. Patients with 1) residual ratio ≥1.5 and 2) R2*_fast ≥R2*_slow were considered as having a predominant biexponential behavior.

STATISTICAL TESTS

Nonparametric tests, Bland-Altman plots, linear correlation, intraclass correlation coefficient. Patients were divided according to their LIC into stable (n = 23), mild (n = 58), moderate (n = 61), and severe (n = 39).

RESULTS

The biexponential model was more suitable for patients with severe iron overload when compared with the other three LIC categories (P < 0.001) for both ROIs. For ROI-1, 37 subjects met criteria for a predominant biexponential behavior. The slow component (5.7%) had a lower fraction than the fast component (94.2%). For ROI-2, 22 subjects met criteria for a predominant biexponential behavior. The slow component (4.7%) had a lower fraction than the fast component (95.2%). The intraobserver variability between both ROIs was excellent.

DATA CONCLUSION

The biexponential R2* relaxometry model is more suitable in children with severe iron overload.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1191-1198.

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.

Ultra-short echo time imaging with multiple echo refocusing for porous media T2 mapping

T₂ relaxation time measurement is a powerful tool to distinguish signal components in porous media. As T₂ weighting is generally achieved by spin-echo based methods, it is very challenging to capture very short T₂ relaxation time components, approximately 1 ms, with high resolution spatial encoding. It is especially challenging when T₂ relaxation times of the other signal components are not known a priori. We propose a method, combining ultrashort echo time (UTE) imaging with multiple spin echo refocusing, to generate a series of images with T₂ weighting. The T₂ decay curves for each image voxel were extracted, and multiple T₂ relaxation components were quantitatively evaluated. The method has been applied to a fast relaxation system, namely, moisture content in wood samples to differentiate cell wall (bound) water and cell cavity (lumen) water.

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.

Liver Iron Quantification with MR Imaging: A Primer for Radiologists

Iron overload is a systemic disorder and is either primary (genetic) or secondary (exogenous iron administration). Primary iron overload is most commonly associated with hereditary hemochromatosis and secondary iron overload with ineffective erythropoiesis (predominantly caused by β-thalassemia major and sickle cell disease) that requires long-term transfusion therapy, leading to transfusional hemosiderosis. Iron overload may lead to liver cirrhosis and hepatocellular carcinoma, in addition to cardiac and endocrine complications. The liver is one of the main iron storage organs and the first to show iron overload. Therefore, detection and quantification of liver iron overload are critical to initiate treatment and prevent complications. Liver biopsy was the historical reference standard for detection and quantification of liver iron content. Magnetic resonance (MR) imaging is now commonly used for liver iron quantification, including assessment of distribution, detection, grading, and monitoring of treatment response in iron overload. Several MR imaging techniques have been developed for iron quantification, each with advantages and limitations. The liver-to-muscle signal intensity ratio technique is simple and widely available; however, it assumes that the reference tissue is normal. Transverse magnetization (also known as R2) relaxometry is validated but is prone to respiratory motion artifacts due to a long acquisition time, is presently available only for 1.5-T imaging, and requires additional cost and delay for off-line analysis. The R2* technique has fast acquisition time, demonstrates a wide range of liver iron content, and is available for 1.5-T and 3.0-T imaging but requires additional postprocessing software. Quantitative susceptibility mapping has the highest sensitivity for detecting iron deposition; however, it is still investigational, and the correlation with liver iron content is not yet established. ^©RSNA, 2018.

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.

Hemochromatosis: pathophysiology, evaluation, and management of hepatic iron overload with a focus on MRI

Hereditary hemochromatosis (HH) is an autosomal recessive disorder that occurs in approximately 1 in 200-250 individuals. Mutations in the HFE gene lead to excess iron absorption. Excess iron in the form of non-transferrin-bound iron (NTBI) causes injury and is readily uptaken by cardiomyocytes, pancreatic islet cells, and hepatocytes. Symptoms greatly vary among patients and include fatigue, abdominal pain, arthralgias, impotence, decreased libido, diabetes, and heart failure. Untreated hemochromatosis can lead to chronic liver disease, fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). Many invasive and noninvasive diagnostic tests are available to aid in diagnosis and treatment. MRI has emerged as the reference standard imaging modality for the detection and quantification of hepatic iron deposition, as ultrasound (US) is unable to detect iron overload and computed tomography (CT) findings are nonspecific and influenced by multiple confounding variables. If caught and treated early, HH disease progression can significantly be altered. Area covered: The data on Hemochromatosis, iron overload, and MRI were gathered by searching PubMed. Expert commentary: MRI is a great tool for diagnosis and management of iron overload. It is safe, effective, and a standard protocol should be included in diagnostic algorithms of future treatment guidelines.

In vivo 13C-MRI using SAMBADENA

Magnetic Resonance Imaging (MRI) is a powerful imaging tool but suffers from a low sensitivity that severely limits its use for detecting metabolism in vivo. Hyperpolarization (HP) methods have demonstrated MRI signal enhancement by several orders of magnitude, enabling the detection of metabolism with a sensitivity that was hitherto inaccessible. While it holds great promise, HP is typically relatively slow (hours), expensive (million $, €) and requires a dedicated device (“polarizer”). Recently, we introduced a new method that creates HP tracers without an external polarizer but within the MR-system itself based on parahydrogen induced polarization (PHIP): Synthesis Amid the Magnet Bore Allows Dramatically Enhanced Nuclear Alignment (SAMBADENA). To date, this method is the simplest and least cost-intensive method for hyperpolarized ¹³C-MRI. HP of P_13C > 20% was demonstrated for 5mM tracer solutions previously. Here, we present a setup and procedure that enabled the first in vivo application of SAMBADENA: Within seconds, a hyperpolarized angiography tracer was produced and injected into an adult mouse. Subsequently, fast ¹³C-MRI was acquired which exhibited the vena cava, aorta and femoral arteries of the rodent. This first SAMBADENA in vivo¹³C-angiography demonstrates the potential of the method as a fast, simple, low-cost alternative to produce HP-tracers to unlock the vast but hidden powers of MRI.

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.

Quantification of liver iron concentration using the apparent susceptibility of hepatic vessels

Background

The quantification of liver iron concentration (LIC) is important for the monitoring of the body iron level in patients with iron overload. Conventionally, LIC is quantified through R2 or R2* mapping using MRI. In this paper, we demonstrate an alternative approach for LIC quantification through measuring the apparent susceptibility of hepatic vessels using quantitative susceptibility mapping (QSM).

Methods

QSM was performed in the liver region with the iterative susceptibility weighted imaging and mapping (iSWIM) algorithm, using the geometry of the vessels extracted from magnitude images as constraints. The susceptibilities of liver tissue were estimated from the apparent susceptibility of the hepatic veins and then converted to LIC. The accuracy of the proposed method was first validated using simulations, and then confirmed using in vivo data collected on 8 healthy controls and 11 patients at 3T. The effects of data acquisition parameters were studied using simulations, and the LICs estimated using QSM were compared with those estimated using R2* mapping.

Results

Simulation results showed that the use of a 3D data acquisition protocol with higher image resolution led to improved accuracy in LIC quantification using QSM. Both simulations and in vivo data results demonstrated that the LICs estimated using the proposed QSM method agreed well with those estimated using R2* mapping. With the shortest echo time being 2.5ms in the multi-echo gradient echo sequence, simulations results showed that LIC up to 12.45 mg iron/g dry tissue can be quantified using the proposed QSM method. For the in vivo data, the highest LIC measured was 11.32 mg iron/g dry tissue.

Conclusions

The proposed method offers a reliable and flexible way to quantify LIC and has the potential to extend the range of LIC that can be accurately measured using R2* and QSM.

Quantitative susceptibility mapping in combination with water-fat separation for simultaneous liver iron and fat fraction quantification

PURPOSES

To evaluate the feasibility of simultaneous quantification of liver iron concentration (LIC) and fat fraction (FF) using water-fat separation and quantitative susceptibility mapping (QSM).

METHODS

Forty-five patients suspected of liver iron overload (LIO) were included. A volumetric interpolated breath-hold examination sequence for QSM and FF, a fat-saturated gradient echo sequence for R₂^*, a spin echo sequence for LIC measurements and MRS analyses for FF (FF-MRS) were performed. Magnetic susceptibility and FF were calculated using a water-fat separation method (FF-MRI). Correlation and receiver operating characteristic analyses were performed.

RESULTS

Magnetic susceptibility showed strong correlation with LIC (r_s=0.918). The optimal susceptibility cut-off values were 0.34, 0.63, 1.29 and 2.23 ppm corresponding to LIC thresholds of 1.8, 3.2, 7.0 and 15.0 mg/g dry weight. The area under the curve (AUC) were 0.948, 0.970, 1 and 1, respectively. No difference in AUC was found between susceptibility and R₂^* at all LIC thresholds. Correlation was found between FF-MRI and FF-MRS (R²=0.910).

CONCLUSIONS

QSM has a high diagnostic performance for LIC quantification, similar to that of R₂^*. FF-MRI provides simultaneous fat quantification. Findings suggest QSM in combination with water-fat separation has potential value for evaluating LIO, especially in cases with coexisting steatosis.

KEY POINTS

• Magnetic susceptibility showed strong correlation with LIC (r _s =0.918). • QSM showed high diagnostic performance for LIC, similar to that of R ₂^* . • Simultaneously estimated FF-MRI showed strong correlation with MR-Spectroscopy-based FF (R ² =0.910). • QSM combining water-fat separation has quantitative value for LIO with coexisted steatosis.

Non-invasive measurement of liver iron concentration using 3-Tesla magnetic resonance imaging: validation against biopsy

OBJECTIVES

To evaluate the performance and limitations of the R2* and signal intensity ratio (SIR) methods for quantifying liver iron concentration (LIC) at 3 T.

METHODS

A total of 105 patients who underwent a liver biopsy with biochemical LIC (LIC_b) were included prospectively. All patients underwent a 3-T MRI scan with a breath-hold multiple-echo gradient-echo sequence (mGRE). LIC calculated by 3-T SIR algorithm (LIC_SIR) and by R2* (LIC_R2*) were correlated with LIC_b. Sensitivity and specificity were calculated. The comparison of methods was analysed for successive classes.

RESULTS

LIC_b was strongly correlated with R2* (r = 0.95, p < 0.001) and LIC_SIR (r = 0.92, p < 0.001). In comparison to LIC_b, LIC_R2* and LIC_SIR detect liver iron overload with a sensitivity/specificity of 0.96/0.93 and 0.92/0.95, respectively, and a bias ± SD of 7.6 ± 73.4 and 14.8 ± 37.6 μmol/g, respectively. LIC_R2* presented the lowest differences for patients with LIC_b values under 130 μmol/g. Above this value, LIC_SIR has the lowest differences.

CONCLUSIONS

At 3 T, R2* provides precise LIC quantification for lower overload but the SIR method is recommended to overcome R2* limitations in higher overload. Our software, available at www.mrquantif.org , uses both methods jointly and selects the best one.

KEY POINTS

• Liver iron can be accurately quantified by MRI at 3 T • At 3 T, R2* provides precise quantification of slight liver iron overload • At 3 T, SIR method is recommended in case of high iron overload • Slight liver iron overload present in metabolic syndrome can be depicted • Treatment can be monitored with great confidence.

Fast quantitative parameter maps without fitting: Integration yields accurate mono-exponential signal decay rates

PURPOSE

To develop a computationally fast and accurate algorithm for mono-exponential signal modelling and validate the new technique in the context of R2* mapping for iron overload assessment.

METHODS

An algorithm is introduced that directly calculates R2* values from a series of images based on integration of the mono-exponential signal decay curve. The algorithm is fast, because fitting is avoided and only arithmetic computations without iterations are applied. Precision and accuracy of the method is determined in comparison to the conventional log-linear (LL), nonlinear least-squares-based Levenberg-Marquardt (NLM), and squared nonlinear Levenberg-Marquardt (SQNLM) methods, which rely on iterative curve fitting.

RESULTS

In simulations, the signal integration based method consistently had the same or better accuracy than the LL, NLM, and SQNLM algorithms for R2* values ranging from 50 s^-1 to 1200 s^-1 . In phantoms and in vivo (12 participants), this method was robust over a wide range of R2* values and signal-to-noise ratios. Computation times were approximately 100, 1460, and 930 times faster than those of the LL, NLM, and SQNLM methods, respectively.

CONCLUSIONS

The fast signal integration method accurately calculates R2* maps. It has the potential to replace conventional, mono-exponential fitting methods for quantitative MRI such as R2* parameter mapping. Magn Reson Med 79:2978-2985, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Automated vessel exclusion technique for quantitative assessment of hepatic iron overload by R2*-MRI

BACKGROUND

Extraction of liver parenchyma is an important step in the evaluation of R2*-based hepatic iron content (HIC). Traditionally, this is performed by radiologists via whole-liver contouring and T2*-thresholding to exclude hepatic vessels. However, the vessel exclusion process is iterative, time-consuming, and susceptible to interreviewer variability.

PURPOSE

To implement and evaluate an automatic hepatic vessel exclusion and parenchyma extraction technique for accurate assessment of R2*-based HIC.

STUDY TYPE

Retrospective analysis of clinical data.

SUBJECTS

Data from 511 MRI exams performed on 257 patients were analyzed.

FIELD STRENGTH/SEQUENCE

All patients were scanned on a 1.5T scanner using a multiecho gradient echo sequence for clinical monitoring of HIC.

ASSESSMENT

An automated method based on a multiscale vessel enhancement filter was investigated for three input data types-contrast-optimized composite image, T2* map, and R2* map-to segment blood vessels and extract liver tissue for R2*-based HIC assessment. Segmentation and R2* results obtained using this automated technique were compared with those from a reference T2*-thresholding technique performed by a radiologist.

STATISTICAL TESTS

The Dice similarity coefficient was used to compare the segmentation results between the extracted parenchymas, and linear regression and Bland-Altman analyses were performed to compare the R2* results, obtained with the automated and reference techniques.

RESULTS

Mean liver R2* values estimated from all three filter-based methods showed excellent agreement with the reference method (slopes 1.04-1.05, R² > 0.99, P < 0.001). Parenchyma areas extracted using the reference and automated methods had an average overlap area of 87-88%. The T2*-thresholding technique included small vessels and pixels at the vessel/tissue boundaries as parenchymal area, potentially causing a small bias (<5%) in R2* values compared to the automated method.

DATA CONCLUSION

The excellent agreement between reference and automated hepatic vessel segmentation methods confirms the accuracy and robustness of the proposed method. This automated approach might improve the radiologist's workflow by reducing the interpretation time and operator dependence for assessing HIC, an important clinical parameter that guides iron overload management.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1542-1551.

Ultra-short echo time images quantify high liver iron

PURPOSE

1.5T gradient echo-based R2∗ estimates are standard-of-care for assessing liver iron concentration (LIC). Despite growing popularity of 3T, echo time (TE) limitations prevent 3T liver iron quantitation in the upper half of the clinical range (LIC ⪆20 mg/g). In this work, a 3D radial pulse sequence was assessed to double the dynamic range of 3T LIC estimates.

THEORY AND METHODS

The minimum TE limits the dynamic range of pulse sequences to estimate R2∗. 23 chronically-transfused human volunteers were imaged with 1.5T Cartesian gradient echo (1.5T-GRE), 3T Cartesian gradient echo (3T-GRE), and 3T ultrashort TE radial (3T-UTE) pulse sequences; minimum TEs were 0.96, 0.76, and 0.19 ms, respectively. R2∗ was estimated with an exponential signal model, normalized to 1.5T equivalents, and converted to LIC. Bland-Altman analysis compared 3T-based estimates to 1.5T-GRE.

RESULTS

LIC by 3T-GRE was unbiased versus 1.5T-GRE for LIC ≤ 25 mg/g (sd = 9.6%); 3T-GRE failed to quantify LIC > 25 mg/g. At high iron loads, 3T-UTE was unbiased (sd = 14.5%) compared to 1.5T-GRE. Further, 3T-UTE estimated LIC up to 50 mg/g, exceeding 1.5T-GRE limits.

CONCLUSION

3T-UTE imaging can reliably estimate high liver iron burdens. In conjunction with 3T-GRE, 3T-UTE allows clinical LIC estimation across a wide range of liver iron loads. Magn Reson Med 79:1579-1585, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Radial Ultrashort TE Imaging Removes the Need for Breath-Holding in Hepatic Iron Overload Quantification by R2* MRI

OBJECTIVE

The objective of this study is to evaluate radial free-breathing (FB) multiecho ultrashort TE (UTE) imaging as an alternative to Cartesian FB multiecho gradient-recalled echo (GRE) imaging for quantitative assessment of hepatic iron content (HIC) in sedated patients and subjects unable to perform breath-hold (BH) maneuvers.

MATERIALS AND METHODS

FB multiecho GRE imaging and FB multiecho UTE imaging were conducted for 46 test group patients with iron overload who could not complete BH maneuvers (38 patients were sedated, and eight were not sedated) and 16 control patients who could complete BH maneuvers. Control patients also underwent standard BH multiecho GRE imaging. Quantitative R2* maps were calculated, and mean liver R2* values and coefficients of variation (CVs) for different acquisitions and patient groups were compared using statistical analysis.

RESULTS

FB multiecho GRE images displayed motion artifacts and significantly lower R2* values, compared with standard BH multiecho GRE images and FB multiecho UTE images in the control cohort and FB multiecho UTE images in the test cohort. In contrast, FB multiecho UTE images produced artifact-free R2* maps, and mean R2* values were not significantly different from those measured by BH multiecho GRE imaging. Motion artifacts on FB multiecho GRE images resulted in an R2* CV that was approximately twofold higher than the R2* CV from BH multiecho GRE imaging and FB multiecho UTE imaging. The R2* CV was relatively constant over the range of R2* values for FB multiecho UTE, but it increased with increases in R2* for FB multiecho GRE imaging, reflecting that motion artifacts had a stronger impact on R2* estimation with increasing iron burden.

CONCLUSION

FB multiecho UTE imaging was less motion sensitive because of radial sampling, produced excellent image quality, and yielded accurate R2* estimates within the same acquisition time used for multiaveraged FB multiecho GRE imaging. Thus, FB multiecho UTE imaging is a viable alternative for accurate HIC assessment in sedated children and patients who cannot complete BH maneuvers.