Estimation of liver T₂ in transfusion-related iron overload in patients with weighted least squares T₂ IDEAL

Liver Fibrosis, Fat, and Iron Evaluation with MRI and Fibrosis and Fat Evaluation with US: A Practical Guide for Radiologists

Quantitative imaging biomarkers of liver disease measured by using MRI and US are emerging as important clinical tools in the management of patients with chronic liver disease (CLD). Because of their high accuracy and noninvasive nature, in many cases, these techniques have replaced liver biopsy for the diagnosis, quantitative staging, and treatment monitoring of patients with CLD. The most commonly evaluated imaging biomarkers are surrogates for liver fibrosis, fat, and iron. MR elastography is now routinely performed to evaluate for liver fibrosis and typically combined with MRI-based liver fat and iron quantification to exclude or grade hepatic steatosis and iron overload, respectively. US elastography is also widely performed to evaluate for liver fibrosis and has the advantage of lower equipment cost and greater availability compared with those of MRI. Emerging US fat quantification methods can be performed along with US elastography. The author group, consisting of members of the Society of Abdominal Radiology (SAR) Liver Fibrosis Disease-Focused Panel (DFP), the SAR Hepatic Iron Overload DFP, and the European Society of Radiology, review the basics of liver fibrosis, fat, and iron quantification with MRI and liver fibrosis and fat quantification with US. The authors cover technical requirements, typical case display, quality control and proper measurement technique and case interpretation guidelines, pitfalls, and confounding factors. The authors aim to provide a practical guide for radiologists interpreting these examinations. ^© RSNA, 2023 See the invited commentary by Ronot in this issue. Quiz questions for this article are available in the supplemental material.

MRI of Lymphedema

Lymphedema is a devastating disease that has no cure. Management of lymphedema has evolved rapidly over the past two decades with the advent of surgeries that can ameliorate symptoms. MRI has played an increasingly important role in the diagnosis and evaluation of lymphedema, as it provides high spatial resolution of the distribution and severity of soft tissue edema, characterizes diseased lymphatic channels, and assesses secondary effects such as fat hypertrophy. Many different MR techniques have been developed for the evaluation of lymphedema, and the modality can be tailored to suit the needs of a lymphatic clinic. In this review article we provide an overview of lymphedema, current management options, and the current role of MRI in lymphedema diagnosis and management. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 5.

Quantification of pancreatic iron overload and fat infiltration and their correlation with glucose disturbance in pediatric thalassemia major patients

Background

Diabetes mellitus affects more than a quarter of patients with thalassemia major (TM) worldwide, and increases the risk for cardiac complications, contributing to significant morbidity. Pancreatic iron overload (IO) and fat infiltration have been correlated with this endocrinal complication in adult TM patients. It has been shown that in adult TM patients, iron accumulation and fat infiltration are found to be heterogeneous in the pancreatic head, body, and tail region. R2* and a fat fraction (FF) generated by gradient-echo imaging can be used as quantitative parameters to assess the iron and fat contents of the pancreas. This study aimed to determine the pattern of pancreatic iron accumulation and fat infiltration in pediatric TM patients with gradient-echo imaging and evaluate the association between pancreatic IO and fat infiltration and glucose disturbances.

Methods

A total of 90 children with TM (10.7±3.1 years) were included. All patients underwent pancreatic magnetic resonance imaging (MRI) using multi-echo gradient-echo sequences. IO was measured by R2* relaxometry in 90 patients, and FF values were measured using iterative decomposition of water and fat with echo asymmetry and the least-squares estimation (IDEAL) method in 40 patients. R2* and FF were assessed in the pancreatic head, body, and tail. The global R2* and global FF values were obtained by averaging the respective values from the pancreatic head, body, and tail. The correlations between global R2*, global FF, and fasting glucose were determined using Spearman's correlation analysis. The Friedman test was used to compare R2* and FF among different pancreatic regions. Receiver operating characteristic (ROC) analysis was used to determine the performance of global R2* and global FF in discriminating impaired fasting glucose from normal fasting glucose patients.

Results

The global R2* was positively correlated with the global FF in the pancreas (r=0.895, P<0.001). No significant differences were found in R2* among the 3 regions of the pancreas (χ²=4.050, P=0.132), but significant differences were found in FF among the 3 pancreatic regions (χ²=16.350, P<0.001). Both global pancreatic R2* (r=0.408, P<0.001) and global FF (r=0.523, P=0.001) were positively correlated with fasting glucose. ROC analysis showed that global pancreatic R2* and global FF had an area under the curve of 0.769 and 0.931 (both P<0.001), respectively, in discriminating between impaired and normal glucose function patients.

Conclusions

Pediatric TM patients can have homogeneous iron siderosis and heterogeneous fat infiltration in the pancreas as measured by gradient-echo imaging, both of which are risk factors for diabetes.

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.

Free-breathing liver fat and R 2 ∗ quantification using motion-corrected averaging based on a nonlocal means algorithm

PURPOSE

To propose a motion-robust chemical shift-encoded (CSE) method with high signal-to-noise (SNR) for accurate quantification of liver proton density fat fraction (PDFF) and R 2 ∗ .

METHODS

A free-breathing multi-repetition 2D CSE acquisition with motion-corrected averaging using nonlocal means (NLM) was proposed. PDFF and R 2 ∗ quantified with 2D CSE-NLM were compared to two alternative 2D techniques: direct averaging and single acquisition (2D 1ave) in a digital phantom. Further, 2D NLM was compared in patients to 3D techniques (standard breath-hold, free-breathing and navigated), and the alternative 2D techniques. A reader study and quantitative analysis (Bland-Altman, correlation analysis, paired Student's t-test) were performed to evaluate the image quality and assess PDFF and R 2 ∗ measurements in regions of interest.

RESULTS

In simulations, 2D NLM resulted in lower standard deviations (STDs) of PDFF (2.7%) and R 2 ∗ (8.2  s - 1 ) compared to direct averaging (PDFF: 3.1%, R 2 ∗ : 13.6  s - 1 ) and 2D 1ave (PDFF: 8.7%, R 2 ∗ : 33.2  s - 1 ). In patients, 2D NLM resulted in fewer motion artifacts than 3D free-breathing and 3D navigated, less signal loss than 2D direct averaging, and higher SNR than 2D 1ave. Quantitatively, the STDs of PDFF and R 2 ∗ of 2D NLM were comparable to those of 2D direct averaging (p>0.05). 2D NLM reduced bias, particularly in R 2 ∗ (-5.73 to -0.36  s - 1 ) that arises in direct averaging (-3.96 to 11.22  s - 1 ) in the presence of motion.

CONCLUSIONS

2D CSE-NLM enables accurate mapping of PDFF and R 2 ∗ in the liver during free-breathing.

Multi-exponential Transverse Relaxation Times Estimation from Magnetic Resonance Images under Rician Noise and Spatial Regularization

Relaxation signal inside each voxel of magnetic resonance images (MRI) is commonly fitted by a multi-exponential decay curve. The estimation of a discrete multi-component relaxation model parameters from magnitude MRI data is a challenging nonlinear inverse problem since it should be conducted on the entire image voxels under non-Gaussian noise statistics. This paper proposes an efficient algorithm allowing the joint estimation of relaxation time values and their amplitudes using different criteria taking into account a Rician noise model, combined with a spatial regularization accounting for low spatial variability of relaxation time constants and amplitudes between neighboring voxels. The Rician noise hypothesis is accounted for either by an adapted nonlinear least squares algorithm applied to a corrected least squares criterion or by a majorization-minimization approach applied to the maximum likelihood criterion. In order to solve the resulting large-scale non-negativity constrained optimization problem with a reduced numerical complexity and computing time, an optimization algorithm based on a majorization approach ensuring separability of variables between voxels is proposed. The minimization is carried out iteratively using an adapted Levenberg-Marquardt algorithm that ensures convergence by imposing a sufficient decrease of the objective function and the non-negativity of the parameters. The importance of the regularization alongside the Rician noise incorporation is shown both visually and numerically on a simulated phantom and on magnitude MRI images acquired on fruit samples.

Resolving estimation uncertainties of chemical shift encoded fat-water imaging using magnetization transfer effect

PURPOSE

B₀ field inhomogeneity may cause significant errors in chemical shift encoding-based fat-water (F/W) separation. We describe a new approach to improve its robustness using novel B₀ field map pre-estimation.

METHODS

Our method exploits insensitivity of fat to magnetization transfer effect, which allows generating fat-insensitive B₀ field priors with full or partial spatial support using a low-resolution magnetization transfer-weighted scan. The full prior can be employed by most F/W separation methods for initialization or data demodulation. We also propose a modified region-growing algorithm in which the partial prior is utilized for its initial seeding.

RESULTS

The magnetization transfer-based B₀ priors significantly reduced F/W errors of three representative F/W separation methods in all cases. In cases with moderate B₀ inhomogeneity, the full prior allowed error-free separation even with basic, voxel-independent processing. When coupled with methods exploiting B₀ field smoothness, it significantly improved separation accuracy even in the presence of strong inhomogeneities. Seeding the region-growing with the partial prior significantly improved performance of F/W separation, including cases with spatially disconnected tissues.

CONCLUSION

Magnetization transfer-based B₀ field pre-estimation provides valuable prior information for F/W separation, which may significantly improve its robustness at the expense of nominal (< 5%-10%) scan time increase.

Estimation of pancreatic R2* for iron overload assessment in the presence of fat: a comparison of different approaches

OBJECTIVES

To propose a method for estimating pancreatic relaxation rate, R2*, from conventional multi-echo MRI, based on the nonlinear fitting of the acquired magnitude signal decay to MR signal models that take into account both the signal oscillations induced by fat and the different R2* values of pancreatic parenchyma and fat.

MATERIALS AND METHODS

Single-peak fat (SPF) and multi-peak fat (MPF) models were introduced. Single-R2* and dual-R2* assumptions were considered as well. Analyses were conducted on simulated data and 20 thalassemia major patients.

RESULTS

Simulations revealed the ability of the MPF model to correctly estimate the R2* value in a large range of fat fractions and R2* values. From the comparison between the results obtained with a single R2* value for water and fat and the dual-R2* approach, the latter is more accurate in both water R2* and fat fraction estimation. In patient's data analysis, a strong concordance was found between SPF and MPF estimated data with measurements done with manual signal correction and from fat-saturated images. The MPF method showed better reproducibility.

CONCLUSION

The MPF dual-R2* approach improves reproducibility and reduces image analysis time in the assessment of pancreatic R2* value in patients with iron overload.

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.

Imaging Features of Non-Alcoholic Fatty Liver Disease in Children and Adolescents

Non-invasive diagnosis and quantification of liver steatosis is important to overcome limits of liver biopsy, in order to follow up patients during their therapy and to establish a reference standard that can be used in clinical trials and longitudinal studies. Imaging offers several methods in this setting: ultrasound, which is the cheapest technique and easy to perform; magnetic resonance spectroscopy (MRS), which reflects the real content of triglycerides in a specific volume; and proton density fat fraction (PDFF) magnetic resonance, which is a simple method that reflects the distribution of the fat in the whole liver. Other techniques include ultrasound elastography (EUS) and magnetic resonance elastrography (MRE), which can evaluate the progression of non-alcoholic fatty liver disease (NAFLD) into non-alcoholic steato-hepatitis (NASH) and cirrhosis, by quantifying liver fibrosis.

Assessment of advanced hepatic MR elastography methods for susceptibility artifact suppression in clinical patients

PURPOSE

To assess the success rate, image quality, and the ability to stage liver fibrosis of a standard 2D gradient-recalled echo (GRE) and four different spin-echo (SE) magnetic resonance elastography (MRE) sequences in patients with different liver iron concentrations.

MATERIALS AND METHODS

A total of 332 patients who underwent 3T MRE examinations that included liver fat and iron quantification were enrolled, including 136 patients with all five MRE techniques. Thirty-four patients had biopsy results for fibrosis staging. The liver stiffness, region of interest area, image quality, and success rate of the five sequences were compared in 115/136 patients. The area under the receiver operating characteristic curves (AUCs) and the accuracies for diagnosing early-stage fibrosis and advanced fibrosis were compared. The effect of BMI (body mass index), the R2* relaxation time, and fat fraction on the image quality and liver stiffness measurements were analyzed.

RESULTS

The success rates were significantly higher in the four SE sequences (99.1-100%) compared with GRE MRE (85.3%) (all P < 0.001). There were significant differences of the mean ROI area between every pair of sequences (all P < 0.0001). There were no significant differences in the AUC of the five MRE sequences for discriminating advanced fibrosis (10 P-values ranging from 0.2410-0.9171). R2* had a significant effect on the success rate and image quality for the noniron 2D echo-planar imaging (EPI), 3D EPI and 2D GRE (all P < 0.001) sequences. BMI had a significant effect on the iron 2D EPI (P = 0.0230) and iron 2D SE (P = 0.0040) sequences.

CONCLUSION

All five techniques showed good diagnostic performance in staging liver fibrosis. The SE MRE sequences had higher success rates and better image quality than GRE MRE in 3T clinical hepatic imaging.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018;47:976-987.

Imaging patterns of fatty liver in pediatric patients

Fatty liver can present as focal, diffuse, heterogeneous, and multinodular forms. Being familiar with various patterns of steatosis can enable correct diagnosis. In patients with equivocal findings on ultrasonography, magnetic resonance imaging can be used as a problem solving tool. New techniques are promising for diagnosis and follow-up. We review imaging patterns of steatosis and new quantitative methods such as proton density fat fraction and magnetic resonance elastography for diagnosis of nonalcoholic fatty liver disease in children.

On the R2⁎ relaxometry in complex multi-peak multi-Echo chemical shift-based water-fat quantification: Applications to the neuromuscular diseases

PURPOSE

Investigation of the feasibility of the R₂^⁎ mapping techniques by using latest theoretical models corrected for confounding factors and optimized for signal to noise ratio.

THEORY AND METHODS

The improvement of the performance of state of the art magnetic resonance imaging (MRI) relaxometry algorithms is challenging because of a non-negligible bias and still unresolved numerical instabilities. Here, R₂^⁎ mapping reconstructions, including complex fitting with multi-spectral fat-correction by using single-decay and double-decay formulation, are deeply studied in order to investigate and identify optimal configuration parameters and minimize the occurrence of numerical artifacts. The effects of echo number, echo spacing, and fat/water relaxation model type are evaluated through both simulated and in-vivo data. We also explore the stability and feasibility of the fat/water relaxation model by analyzing the impact of high percentage of fat infiltrations and local transverse relaxation differences among biological species.

RESULTS

The main limits of the MRI relaxometry are the presence of bias and the occurrence of artifacts, which significantly affect its accuracy. Chemical-shift complex R₂^⁎-correct single-decay reconstructions exhibit a large bias in presence of a significant difference in the relaxation rates of fat and water and with fat concentration larger than 30%. We find that for fat-dominated tissues or in patients affected by extensive iron deposition, MRI reconstructions accounting for multi-exponential relaxation time provide accurate R₂^⁎ measurements and are less prone to numerical artifacts.

CONCLUSIONS

Complex fitting and fat-correction with multi-exponential decay formulation outperforms the conventional single-decay approximation in various diagnostic scenarios. Although it still lacks of numerical stability, which requires model enhancement and support from spectroscopy, it offers promising perspectives for the development of relaxometry as a reliable tool to improve tissue characterization and monitoring of neuromuscular disorders.

Does fat suppression via chemically selective saturation affect R2*-MRI for transfusional iron overload assessment? A clinical evaluation at 1.5T and 3T

PURPOSE

Fat suppression (FS) via chemically selective saturation (CHESS) eliminates fat-water oscillations in multiecho gradient echo (mGRE) R2*-MRI. However, for increasing R2* values as seen with increasing liver iron content (LIC), the water signal spectrally overlaps with the CHESS band, which may alter R2*. We investigated the effect of CHESS on R2* and developed a heuristic correction for the observed CHESS-induced R2* changes.

METHODS

Eighty patients [female, n = 49; male, n = 31; mean age (± standard deviation), 18.3 ± 11.7 y] with iron overload were scanned with a non-FS and a CHESS-FS mGRE sequence at 1.5T and 3T. Mean liver R2* values were evaluated using three published fitting approaches. Measured and model-corrected R2* values were compared and statistically analyzed.

RESULTS

At 1.5T, CHESS led to a systematic R2* reduction (P < 0.001 for all fitting algorithms) especially toward higher R2*. Our model described the observed changes well and reduced the CHESS-induced R2* bias after correction (linear regression slopes: 1.032/0.927/0.981). No CHESS-induced R2* reductions were found at 3T.

CONCLUSION

The CHESS-induced R2* bias at 1.5T needs to be considered when applying R2*-LIC biopsy calibrations for clinical LIC assessment, which were established without FS at 1.5T. The proposed model corrects the R2* bias and could therefore improve clinical iron overload assessment based on linear R2*-LIC calibrations. Magn Reson Med 76:591-601, 2016. © 2015 Wiley Periodicals, Inc.

The Feasibility of Magnetic Resonance Imaging for Quantification of Liver, Pancreas, Spleen, Vertebral Bone Marrow, and Renal Cortex R2* and Proton Density Fat Fraction in Transfusion-Related Iron Overload

OBJECTIVE

We aimed to evaluate the feasibility of quantification of liver, pancreas, spleen, vertebral bone marrow, and renal cortex R2* and magnetic resonance imaging-proton density fat fraction (MRI-PDFF) and to evaluate the correlations among them in patients with transfusion-related iron overload.

MATERIALS AND METHODS

A total of 9 patients (5 boys, 4 girls) who were referred to our clinic with suspicion of hepatic iron overload were included in this study. All patients underwent T1-independent volumetric multi-echo gradient-echo imaging with T2* correction and spectral fat modeling. MRI examinations were performed on a 1.5 T MRI system.

RESULTS

All patients had hepatic iron overload. Severe hepatic iron overload was recorded in 5/9 patients (56%), and when we evaluated the PDFF maps of these patients, we observed an extensive patchy artifact in the liver in 4 of 5 patients (R2* greater than 671 Hz). When we performed MRI-PDFF measurements despite these artifacts, we observed artifactual high MRI-PDFF values. There was a close correlation between average pancreas R2* and average pancreas MRI-PDFF (p=0.003, r=0.860). There was a significant correlation between liver R2* and average pancreas R2* (p=0.021, r=0.747), liver R2* and renal cortex R2* (p=0.020, r=0.750), and average pancreas R2* and renal cortex R2* (p=0.003, r=0.858). There was a significant negative correlation between vertebral bone marrow R2* and age (p=0.018, r=-0.759).

CONCLUSION

High iron content of the liver, especially with a T2* value shorter than the first echo time can spoil the efficacy of PDFF calculation. Fat deposition in the pancreas is accompanied by pancreatic iron overload. There is a significant correlation between hepatic siderosis and pancreatic siderosis. Renal cortical and pancreatic siderosis are correlated, too.

Quantitative R2* MRI of the liver with rician noise models for evaluation of hepatic iron overload: Simulation, phantom, and early clinical experience

PURPOSE

To compare Rician and non-Rician noise models for quantitative R2 * magnetic resonance imaging (MRI), in a simulation, phantom, and human study.

MATERIALS AND METHODS

Synthetic 12-echo spoiled GRE (SGRE) datasets were generated with various R2 * rates (0-2000 sec(-1) ) at a signal-to-noise ratio (SNR) of 50, 20, 10, and 5. Phantoms of different MnCl2 concentrations (0-25 mM) were constructed and imaged using a 12-echo 3D SGRE sequence at 1.5T. Increasing levels of synthetic noise was added to the original data to simulate sequentially lower SNR conditions. Sixteen patients with suspected or known iron overload were imaged using 12-echo 3D SGRE at 1.5T. Various R2 * quantification methods, based on Rician and non-Rician noise models, were compared in the simulation, phantom, and human datasets.

RESULTS

Non-Rician R2 * estimates were variably inaccurate in the high R2 * range (>500 sec(-1) ), with SNR-dependent linear goodness-of-fit statistic (R(2) ) of 0.373-0.999. Rician R2 * estimates were accurate even in the high R2 * range, with high R(2) of 0.940-0.999 regardless of SNR. Non-Rician R2 * estimates were variably nonlinear at high MnCl2 concentrations, with SNR-dependent R(2) of 0.345-0.994. Rician R2 * estimates were linear even at high MnCl2 concentrations, with high R(2) of 0.923-0.994 regardless of SNR. Between-method agreement of the R2 * estimates was excellent in patients with low ferritin but poor in patients with high ferritin. Rician R2 * estimates had excellent correlation with ferritin (r = 0.966 P < 0.001).

CONCLUSION

Rician R2 * estimates were most consistent in the high R2 * conditions and under varying SNR, and may be more reliable when high iron load is suspected.

Utilization of a balanced steady state free precession signal model for improved fat/water decomposition

PURPOSE

Chemical shift based fat/water decomposition methods such as IDEAL are frequently used in challenging imaging environments with large B0 inhomogeneity. However, they do not account for the signal modulations introduced by a balanced steady state free precession (bSSFP) acquisition. Here we demonstrate improved performance when the bSSFP frequency response is properly incorporated into the multipeak spectral fat model used in the decomposition process.

THEORY AND METHODS

Balanced SSFP allows for rapid imaging but also introduces a characteristic frequency response featuring periodic nulls and pass bands. Fat spectral components in adjacent pass bands will experience bulk phase offsets and magnitude modulations that change the expected constructive and destructive interference between the fat spectral components. A bSSFP signal model was incorporated into the fat/water decomposition process and used to generate images of a fat phantom, and bilateral breast and knee images in four normal volunteers at 1.5 Tesla.

RESULTS

Incorporation of the bSSFP signal model into the decomposition process improved the performance of the fat/water decomposition.

CONCLUSION

Incorporation of this model allows rapid bSSFP imaging sequences to use robust fat/water decomposition methods such as IDEAL. While only one set of imaging parameters were presented, the method is compatible with any field strength or repetition time.

Improving highly accelerated fat fraction measurements for clinical trials in muscular dystrophy: origin and quantitative effect of R2* changes

Purpose To investigate the effect of R2* modeling in conventional and accelerated measurements of skeletal muscle fat fraction in control subjects and patients with muscular dystrophy. Materials and Methods Eight patients with Becker muscular dystrophy and eight matched control subjects were recruited with approval from the Newcastle and North Tyneside 2 Research Ethics Committee and with written consent. Chemical-shift images with six widely spaced echo times (in 3.5-msec increments) were acquired to correlate R2* and muscle fat fraction. The effect of incorporating or neglecting R2* modeling on fat fraction magnitude and variance was evaluated in a typical three-echo protocol (with 0.78-msec increments). Accelerated acquisitions with this protocol with 3.65×, 4.94×, and 6.42× undersampling were reconstructed by using combined compressed sensing and parallel imaging and fat fraction maps produced with R2* modeling. Results Muscle R2* at 3.0 T (33-125 sec(-1)) depended on the morphology of fat replacement, the highest values occurring with the greatest interdigitation of fat. The inclusion of R2* modeling removed bias, which was greatest at low fat fraction, but did not increase variance. The 95% limits of agreement of the accelerated acquisitions were tight and not degraded by R2* modeling (1.65%, 1.95%, and 2.22% for 3.65×, 4.94×, and 6.42× acceleration, respectively). Conclusion Incorporating R2* modeling prevents systematic errors in muscle fat fraction by up to 3.5% without loss of precision and should be incorporated into all muscular dystrophy studies. Fat fraction measurements can be accelerated fivefold by using combined compressed sensing and parallel imaging, modeling for R2* without loss of fidelity.

Rapid look-up table method for noise-corrected curve fitting in the R2* mapping of iron loaded liver

PURPOSE

Fitting the measured decay signal to the first moment in the presence of noncentral chi noise (M(1) NCM) can correctly address the effect of noise on the effective transverse relaxation rate (R2*) relaxometry of iron loaded liver. However, this method requires intensive computation, which restricts its application to R2* mapping. This work aims to develop a rapid implementation of the M(1) NCM method for R2* mapping.

METHODS

The computation of the confluent hypergeometric function in the M(1) NCM model was approximated using cubic spline interpolation with breakpoints and coefficients precalculated and stored in a look-up table (M(1) NCM-LUT). The performance of the proposed M(1) NCM-LUT method was evaluated through simulation and based on in vivo liver R2* relaxometry data.

RESULTS

In both simulation and in vivo studies, the maximum absolute difference between R2* maps generated by the M(1) NCM and M(1) NCM-LUT methods was nearly 10(-3) s(-1) or less, and the M(1) NCM-LUT method obtained a R2* map in approximately 1 s and achieved an acceleration of approximately five orders of magnitude.

CONCLUSION

The proposed M(1) NCM-LUT method can significantly increase the speed of the liver R2* mapping using the M(1) NCM model. This development is important in promoting application of this R2* mapping technique for tissue iron quantification.

Fat and iron quantification in the liver: past, present, and future

Liver fat, iron, and combined overload are common manifestations of diffuse liver disease and may cause lipotoxicity and iron toxicity via oxidative hepatocellular injury, leading to progressive fibrosis, cirrhosis, and eventually, liver failure. Intracellular fat and iron cause characteristic changes in the tissue magnetic properties in predictable dose-dependent manners. Using dedicated magnetic resonance pulse sequences and postprocessing algorithms, fat and iron can be objectively quantified on a continuous scale. In this article, we will describe the basic physical principles of magnetic resonance fat and iron quantification and review the imaging techniques of the "past, present, and future." Standardized radiological metrics of fat and iron are introduced for numerical reporting of overload severity, which can be used toward objective diagnosis, grading, and longitudinal disease monitoring. These noninvasive imaging techniques serve an alternative or complimentary role to invasive liver biopsy. Commercial solutions are increasingly available, and liver fat and iron quantitative imaging is now within reach for routine clinical use and may soon become standard of care.

Optimal region-of-interest MRI R2* measurements for the assessment of hepatic iron content in thalassaemia major

OBJECTIVES

To evaluate the performance of region-of-interest (ROI)-based MRI R2* measurements by using the first-moment noise-corrected model (M(1)NCM) to correct the non-central Chi noise in magnitude images from phased arrays for hepatic iron content (HIC) assessment.

METHODS

R2* values were quantified using the M(1)NCM model. Three approaches were employed to determine the representative R2*: fitting of the ROI-averaged signal (average-then-fit, ATF); outputting the median and mean of R2*s from the pixel-wise fitting of decay signals within the ROI (denoted as PWFmed and PWFmea, respectively). The accuracy and precision of the three approaches were evaluated on synthesized data. The agreement among these approaches and their intra- and inter-observer reproducibility were assessed on 105 thalassaemia major patients.

RESULTS

Simulations showed that ATF consistently yielded the highest accuracy and precision at varying noise levels. By contrast, PWFmed and PWFmea slightly and significantly overestimated high R2* at poor signal-to-noise ratios, respectively. Patient study showed that ATF agreed well with PWFmed, whereas PWFmea produced high R2* measurements for patients with severe HIC. No significant difference was observed in the reproducibility of the three approaches.

CONCLUSIONS

PWFmea tends to overestimate high R2*, whereas ATF and PWFmed can produce more accurate R2* measurements for HIC assessment.

Quantification of liver iron with MRI: state of the art and remaining challenges

Liver iron overload is the histological hallmark of hereditary hemochromatosis and transfusional hemosiderosis, and can also occur in chronic hepatopathies. Iron overload can result in liver damage, with the eventual development of cirrhosis, liver failure, and hepatocellular carcinoma. Assessment of liver iron levels is necessary for detection and quantitative staging of iron overload and monitoring of iron-reducing treatments. This article discusses the need for noninvasive assessment of liver iron and reviews qualitative and quantitative methods with a particular emphasis on magnetic resonance imaging (MRI). Specific MRI methods for liver iron quantification include signal intensity ratio as well as R2 and R2* relaxometry techniques. Methods that are in clinical use, as well as their limitations, are described. Remaining challenges, unsolved problems, and emerging techniques to provide improved characterization of liver iron deposition are discussed.

On the confounding effect of temperature on chemical shift-encoded fat quantification

PURPOSE

To characterize the confounding effect of temperature on chemical shift-encoded (CSE) fat quantification.

METHODS

The proton resonance frequency of water, unlike triglycerides, depends on temperature. This leads to a temperature dependence of the spectral models of fat (relative to water) that are commonly used by CSE-MRI methods. Simulation analysis was performed for 1.5 Tesla CSE fat-water signals at various temperatures and echo time combinations. Oil-water phantoms were constructed and scanned at temperatures between 0 and 40°C using spectroscopy and CSE imaging at three echo time combinations. An explanted human liver, rejected for transplantation due to steatosis, was scanned using spectroscopy and CSE imaging. Fat-water reconstructions were performed using four different techniques: magnitude and complex fitting, with standard or temperature-corrected signal modeling.

RESULTS

In all experiments, magnitude fitting with standard signal modeling resulted in large fat quantification errors. Errors were largest for echo time combinations near TEinit ≈ 1.3 ms, ΔTE ≈ 2.2 ms. Errors in fat quantification caused by temperature-related frequency shifts were smaller with complex fitting, and were avoided using a temperature-corrected signal model.

CONCLUSION

Temperature is a confounding factor for fat quantification. If not accounted for, it can result in large errors in fat quantifications in phantom and ex vivo acquisitions.

Regional alveolar partial pressure of oxygen measurement with parallel accelerated hyperpolarized gas MRI

RATIONALE AND OBJECTIVES

Alveolar oxygen tension (Pao2) is sensitive to the interplay between local ventilation, perfusion, and alveolar-capillary membrane permeability, and thus reflects physiologic heterogeneity of healthy and diseased lung function. Several hyperpolarized helium ((3)He) magnetic resonance imaging (MRI)-based Pao2 mapping techniques have been reported, and considerable effort has gone toward reducing Pao2 measurement error. We present a new Pao2 imaging scheme, using parallel accelerated MRI, which significantly reduces measurement error.

MATERIALS AND METHODS

The proposed Pao2 mapping scheme was computer-simulated and was tested on both phantoms and five human subjects. Where possible, correspondence between actual local oxygen concentration and derived values was assessed for both bias (deviation from the true mean) and imaging artifact (deviation from the true spatial distribution).

RESULTS

Phantom experiments demonstrated a significantly reduced coefficient of variation using the accelerated scheme. Simulation results support this observation and predict that correspondence between the true spatial distribution and the derived map is always superior using the accelerated scheme, although the improvement becomes less significant as the signal-to-noise ratio increases. Paired measurements in the human subjects, comparing accelerated and fully sampled schemes, show a reduced Pao2 distribution width for 41 of 46 slices.

CONCLUSION

In contrast to proton MRI, acceleration of hyperpolarized imaging has no signal-to-noise penalty; its use in Pao2 measurement is therefore always beneficial. Comparison of multiple schemes shows that the benefit arises from a longer time-base during which oxygen-induced depolarization modifies the signal strength. Demonstration of the accelerated technique in human studies shows the feasibility of the method and suggests that measurement error is reduced here as well, particularly at low signal-to-noise levels.

Multipeak fat-corrected complex R2* relaxometry: theory, optimization, and clinical validation

PURPOSE

To develop R2* mapping techniques corrected for confounding factors and optimized for noise performance.

THEORY AND METHODS

Conventional R2* mapping is affected by two key confounding factors: noise-related bias and the presence of fat in tissue. Noise floor effects introduce bias in magnitude-based reconstructions, particularly at high R2* values. The presence of fat, if uncorrected, introduces severe protocol-dependent bias. In this work, the bias/noise properties of different R2* mapping reconstructions (magnitude- and complex-fitting, fat-uncorrected, and fat-corrected) are characterized using Cramer-Rao Bound analysis, simulations, and in vivo data. A framework for optimizing the choice of echo times is provided. Finally, the robustness of liver R2* mapping in the presence of fat is evaluated in 28 subjects.

RESULTS

Fat-corrected R2* mapping removes fat-related bias without noise penalty over a wide range of R2* values. Complex nonlinear least-squares fitted and fat-corrected R2* reconstructions that account for the spectral complexity of fat provide robust R2* estimates with low bias and optimized noise performance over a wide range of echo times combinations and R2* values.

CONCLUSION

The use of complex fitting and fat-correction improves the robustness, noise performance, and accuracy of R2* measurements, and are necessary to establish R2* as quantitative imaging biomarker in the liver.

MRI evaluation of hepatic iron overload: Recent advances

Many studies show that hepatic iron overload has a close association with hepatitis, hepatic fibrosis, cirrhosis, and hepatic tumors. Methods currently used for detection of hepatic iron overload, such as plasma ferritin detection, liver biopsy, and superconducting quantum interface device, have some limitations. Improvement in software and hardware has enabled MRI to become a safe, noninvasive and accurate method for detecting hepatic iron overload. This article aims to summarize the performance and application of MRI in the evaluation of hepatic iron overload.

Quantification of hepatic macrosteatosis in living, related liver donors using T1-independent, T2*-corrected chemical shift MRI

PURPOSE

To evaluate the diagnostic implications of the iterative decomposition of water and fat using echo-asymmetry and the least-squares estimation (IDEAL) technique to detect hepatic steatosis (HS) in potential liver donors using histopathology as the reference standard.

MATERIALS AND METHODS

Forty-nine potential liver donors (32 male, 17 female; mean age, 31.7 years) were included. All patients were imaged using the in- and out-of-phase (IOP) gradient-echo (GRE) and IDEAL techniques on a 1.5 T MR scanner. To estimate the hepatic fat fraction (FF), two reviewers performed regions-of-interest measurement in 15 areas of the liver seen on the IOP images and on the IDEAL-FF images. The magnetic resonance imaging (MRI) and pathology values of macrosteatosis were correlated using the Pearson correlation coefficient. We analyzed the diagnostic performance of IOP imaging and IDEAL for detecting HS.

RESULTS

The results of the hepatic-FF estimated on IDEAL were well correlated with the histologic degree of macrosteatosis (γ = 0.902, P < 0.001). IDEAL showed 100% sensitivity and 91% specificity for detecting HS, and IOP imaging showed 87.5% sensitivity and 97% specificity, respectively.

CONCLUSION

IDEAL is a useful tool for the preoperative diagnosis of HS in potential living liver donors; it can also help to avoid unnecessary biopsies in these patients.

The magnetic resonance imaging spectrum of facioscapulohumeral muscular dystrophy

INTRODUCTION

Facioscapulohumeral muscular dystrophy (FSHD) is associated with a repeat contraction in the D4Z4 gene locus on chromosome 4q35. We used a one-step quantitative magnetic resonance imaging (MRI) method to evaluate muscle, edema, and fat in patients spanning the range of severity.

METHODS

Fifteen patients with FSHD were compared with 10 healthy subjects using non-negative linear least-squares fitting of 32-echo relaxation data (T2). The results were compared with a biexponential approach for characterizing muscle/fat ratio and T2 relaxation measurements from fat-suppressed inversion recovery.

RESULTS

Increased T2 signal consistent with edema was common in FSHD subjects, a pattern not present in healthy controls. A varied pattern of edema and fatty replacement in muscles was shown.

CONCLUSIONS

As a discrete biomarker, edema may be useful for following the clinical course of FSHD. Future work toward optimizing measurement is discussed.

Variations in T(2)* and fat content of murine brown and white adipose tissues by chemical-shift MRI

PURPOSE

The purpose was to compare T(2)* relaxation times and proton density fat-fraction (PDFF) values between brown (BAT) and white (WAT) adipose tissue in lean and ob/ob mice.

MATERIALS AND METHODS

A group of lean male mice (n=6) and two groups of ob/ob male mice placed on similar 4-week (n=6) and 8-week (n=8) ad libitum diets were utilized. The animals were imaged at 3 T using a T(2)*-corrected chemical-shift-based water-fat magnetic resonance imaging (MRI) method that provides simultaneous estimation of T(2)* and PDFF on a voxel-wise basis. Regions of interest were drawn within the interscapular BAT and gonadal WAT depots on co-registered T(2)* and PDFF maps. Measurements were assessed using analysis of variance, Bonferroni-adjusted t test for multigroup comparisons and the Tukey post hoc test.

RESULTS

Significant differences (P<.01) in BAT T(2)* and PDFF were observed between the lean and ob/ob groups. The ob/ob animals exhibited longer BAT T(2)* and greater PDFF than lean animals. However, only BAT PDFF was significantly different (P<.01) between the two ob/ob groups. When comparing BAT to WAT within each group, T(2)* and PDFF values were consistently lower in BAT than WAT (P<.01). The difference was most prominent in the lean animals. In both ob/ob groups, BAT exhibited very WAT-like appearances and properties on the MRI images.

CONCLUSION

T(2)* and PDFF are lower in BAT than WAT. This is likely due to variations in tissue composition. The values were consistently lower in lean mice than in ob/ob mice, suggestive of the former's greater demand for BAT thermogenesis and reflective of leptin hormone deficiencies and diminished BAT metabolic activity in the latter.

Simultaneous field and R2 mapping to quantify liver iron content using autoregressive moving average modeling

PURPOSE

To investigate the use of a complex multigradient echo (mGRE) acquisition and an autoregressive moving average (ARMA) model for simultaneous susceptibility and R 2 measurements for the assessment of liver iron content (LIC) in patients with iron overload.

MATERIALS AND METHODS

Fifty magnetic resonance imaging (MRI) exams with magnitude and phase mGRE images were processed using the ARMA model, which provides fat-separated field maps, R 2 maps, and T(1) -W imaging. The LIC was calculated by measuring the susceptibility between the liver and the right transverse abdominal muscle from the field maps. The relationship between LIC derived from susceptibility measurements and LIC from R 2 measurements was determined using linear least-squares regression analysis.

RESULTS

LIC measured from R 2 is highly correlated to the LIC with the susceptibility method (mg/g dry = 8.99 ± 0.15 × [mg Fe/mL of wet liver] -2.38 ± 0.29, R(2) = 0.94). The field inhomogeneity in the liver is correlated with R 2 (R(2) = 0.85).

CONCLUSION

By using the ARMA model on complex mGRE images, both susceptibility and R 2-based LIC measurements can be made simultaneously. The susceptibility measurement can be used to help verify R 2 measurements in the assessment of iron overload.