Kidney R2* Mapping for Noninvasive Evaluation of Iron Overload in Paroxysmal Nocturnal Hemoglobinuria

PURPOSE

The kidney iron deposition can cause kidney damage and renal insufficiency in paroxysmal nocturnal hemoglobinuria (PNH) patients. Assessment of iron deposition in the kidney is essential for the early diagnosis of renal damage in PNH patients. The purpose of this study was to evaluate kidney R2* (T2* reciprocals) values in PNH patients using the iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL-IQ).

METHODS

Two radiologists measured the R2* values of the renal cortex in 14 PNH patients and 13 healthy volunteers using IDEAL-IQ. Lactate dehydrogenase (LDH), a reliable marker of intravascular hemolysis, was also measured in all participants.

RESULTS

The kidney R2* values were significantly higher in PNH patients compared with those in healthy volunteers (P < 0.001). High inter-operator reproducibility of the measurements was also acquired using IDEAL-IQ. LDH levels were also significantly higher in PNH patients compared with those in healthy volunteers (P < 0.001). Kidney R2* values strongly correlated with LDH levels in PNH patients.

CONCLUSION

IDEAL-IQ has a possibility of becoming a useful method for the noninvasive evaluation of renal iron overload in PNH patients.

Cascade of Denoising and Mapping Neural Networks for MRI R2* Relaxometry of Iron-Loaded Liver

MRI of effective transverse relaxation rate (R2*) measurement is a reliable method for liver iron concentration quantification. However, R2* mapping can be degraded by noise, especially in the case of iron overload. This study aimed to develop a deep learning method for MRI R2* relaxometry of an iron-loaded liver using a two-stage cascaded neural network. The proposed method, named CadamNet, combines two convolutional neural networks separately designed for image denoising and parameter mapping into a cascade framework, and the physics-based R2* decay model was incorporated in training the mapping network to enforce data consistency further. CadamNet was trained using simulated liver data with Rician noise, which was constructed from clinical liver data. The performance of CadamNet was quantitatively evaluated on simulated data with varying noise levels as well as clinical liver data and compared with the single-stage parameter mapping network (MappingNet) and two conventional model-based R2* mapping methods. CadamNet consistently achieved high-quality R2* maps and outperformed MappingNet at varying noise levels. Compared with conventional R2* mapping methods, CadamNet yielded R2* maps with lower errors, higher quality, and substantially increased efficiency. In conclusion, the proposed CadamNet enables accurate and efficient iron-loaded liver R2* mapping, especially in the presence of severe noise.

Mitigating the impact of flip angle and orientation dependence in single compartment R2* estimates via 2-pool modeling

PURPOSE

The effective transverse relaxation rate (R 2 * $$ {\mathrm{R}}_2^{\ast } $$ ) is influenced by biological features that make it a useful means of probing brain microstructure. However, confounding factors such as dependence on flip angle (α) and fiber orientation with respect to the main field (θ $$ \uptheta $$ ) complicate interpretation. The α- andθ $$ \uptheta $$ -dependence stem from the existence of multiple sub-voxel micro-environments (e.g., myelin and non-myelin water compartments). Ordinarily, it is challenging to quantify these sub-compartments; therefore, neuroscientific studies commonly make the simplifying assumption of a mono-exponential decay obtaining a singleR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimate per voxel. In this work, we investigated how the multi-compartment nature of tissue microstructure affects single compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates.

METHODS

We used 2-pool (myelin and non-myelin water) simulations to characterize the bias in single compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates. Based on our numeric observations, we introduced a linear model that partitionsR 2 * $$ {\mathrm{R}}_2^{\ast } $$ into α-dependent and α-independent components and validated this in vivo at 7T. We investigated the dependence of both components on the sub-compartment properties and assessed their robustness, orientation dependence, and reproducibility empirically.

RESULTS

R 2 * $$ {\mathrm{R}}_2^{\ast } $$ increased with myelin water fraction and residency time leading to a linear dependence on α. We observed excellent agreement between our numeric and empirical results. Furthermore, the α-independent component of the proposed linear model was robust to the choice of α and reduced dependence on fiber orientation, although it suffered from marginally higher noise sensitivity.

CONCLUSION

We have demonstrated and validated a simple approach that mitigates flip angle and orientation biases in single-compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates.

Multisite reproducibility of quantitative susceptibility mapping and effective transverse relaxation rate in deep gray matter at 3 T using locally optimized sequences in 24 traveling heads

Iron concentration in the human brain plays a crucial role in several neurodegenerative diseases and can be monitored noninvasively using quantitative susceptibility mapping (QSM) and effective transverse relaxation rate (R₂ *) mapping from multiecho T₂ *-weighted images. Large population studies enable better understanding of pathologies and can benefit from pooling multisite data. However, reproducibility may be compromised between sites and studies using different hardware and sequence protocols. This work investigates QSM and R₂ * reproducibility at 3 T using locally optimized sequences from three centers and two vendors, and investigates possible reduction of cross-site variability through postprocessing approaches. Twenty-four healthy subjects traveled between three sites and were scanned twice at each site. Scan-rescan measurements from seven deep gray matter regions were used for assessing within-site and cross-site reproducibility using intraclass correlation coefficient (ICC) and within-subject standard deviation (SDw) measures. In addition, multiple QSM and R₂ * postprocessing options were investigated with the aim to minimize cross-site sequence-related variations, including: mask generation approach, echo-timing selection, harmonizing spatial resolution, field map estimation, susceptibility inversion method, and linear field correction for magnitude images. The same-subject cross-site region of interest measurements for QSM and R₂ * were highly correlated (R²  ≥ 0.94) and reproducible (mean ICC of 0.89 and 0.82 for QSM and R₂ *, respectively). The mean cross-site SDw was 4.16 parts per billion (ppb) for QSM and 1.27 s^-1 for R₂ *. For within-site measurements of QSM and R₂ *, the mean ICC was 0.97 and 0.87 and mean SDw was 2.36 ppb and 0.97 s^-1 , respectively. The precision level is regionally dependent and is reduced in the frontal lobe, near brain edges, and in white matter regions. Cross-site QSM variability (mean SDw) was reduced up to 46% through postprocessing approaches, such as masking out less reliable regions, matching available echo timings and spatial resolution, avoiding the use of the nonconsistent magnitude contrast between scans in field estimation, and minimizing streaking artifacts.

Reproducibility of liver R2* quantification for liver iron quantification from cardiac R2* acquisitions

OBJECTIVES

To evaluate the reproducibility of liver R2* measurements between a 2D cardiac ECG-gated and a 3D breath-hold liver CSE-MRI acquisition for liver iron quantification.

METHODS

A total of 54 1.5 T MRI exams from 51 subjects (18 women, 36 men, age 35.2 ± 21.8) were included. These included two sub-studies with 23 clinical MRI exams from 19 patients identified retrospectively, 24 participants with known or suspected iron overload, and 7 healthy volunteers acquired prospectively. The 2D cardiac and the 3D liver R2* maps were acquired in the same exam. Either acquisitions were reconstructed using a complex R2* algorithm that accounts for the presence of fat and residual phase errors due to eddy currents. Data were analyzed using colocalized ROIs in the liver.

RESULTS

Linear regression analysis demonstrated high Pearson's correlation and Lin's concordance coefficient for the overall study and both sub-studies. Bland-Altman analysis also showed good agreement, except for a slight increase of the mean R2* value above ~ 400 s^-1. The Kolmogorow-Smirnow test revealed a non-normal distribution for (R2* 3D-R2* 2D) values from 0 to 600 s^-1 in contrast to the 0-200 s^-1 and 0-400 s^-1 subpopulations. Linear regression analysis showed no relevant differences other than the intercept, likely due to only 7 measurements above 400 s^-1.

CONCLUSIONS

The results demonstrate that R2*-measurements in the liver are feasible using 2D cardiac R2* maps compared to 3D liver R2* maps as the reference. Liver R2* may be underestimated for R2* > 400 s^-1 using the 2D cardiac R2* mapping method.

Application of Multiparametric Magnetic Resonance Imaging to Monitor the Early Antitumor Effect of CuS@GOD Nanoparticles in a 4 T1 Breast Cancer Xenograft Model

BACKGROUND

We have developed hybrid nanoparticles (NPs) by co-loading copper sulfide (CuS) NPs and glucose oxidase (GOD) (CuS@GOD NPs) to explore their antitumor properties.

PURPOSE

To investigate the feasibility of using multiparametric magnetic resonance imaging (MRI) including intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and R₂ * mapping to quantitatively assess the early antitumor effect of CuS@GOD NPs.

STUDY TYPE

Prospective.

ANIMAL MODEL

The orthotopic BALB/c mice 4 T1 breast cancer model. The 4 T1 xenografts in group 1 mice received normal saline, group 2 received CuS@GOD NPs, group 3 received CuS NPs plus laser, and group 4 received CuS@GOD NPs plus laser (n = 28 for each group).

FIELD STRENGTH/SEQUENCE

A 3.0 T/IVIM-DWI MRI single-shot echo-planar imaging, R₂ * mapping spoiled gradient recalled echo (SPGR) sequence, T2-weighted images (T2WI) and T1-weighted images (T1WI) fast spin echo (FSE) sequence.

ASSESSMENT

The IVIM-DWI and R₂ * mapping were performed before and after treatment at 0 hour, 0.5 hour, 1 hour, 2 hours, 4 hours, and 24 hours in four groups and the MRI parameters were obtained. Correlation analysis between the MRI parameters and histological analyses was conducted.

STATISTICAL TESTS

One-way ANOVA, Pearson's correlation analysis, two independent samples t test, intraclass correlation coefficient. P < 0.05 was considered to be statistically significant.

RESULTS

In group 4, the tumoral D value was significantly higher than that of group 2 at 24 hours (0.541 ± 0.065 vs. 0.492 ± 0.051). The f value of group 4 was significantly lower than that of groups 1 and 2 at 2 hours (10.83 ± 2.16 vs. 14.28 ± 1.86, 16.67 ± 3.53, respectively). The R₂ * value was significantly increased at 0 hour in group 4 compared to that of groups 1 and 2 (64.552 ± 4.663 vs. 42.441 ± 1.516, 43.165 ± 1.709, respectively). D, f, and R₂ * were correlated with the histological staining results (r = 0.695-0.970).

DATA CONCLUSION

The IVIM-DWI-derived D and f and R₂ * mapping-derived R₂ * could monitor early response to CuS@GOD NPs treatment in vivo.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Effectiveness of QSM over R2* in assessment of parkinson's disease - A systematic review

The incidence and prevalence of Parkinson's (PD) are increasing rapidly in developing countries. PD is difficult to diagnose based on clinical assessment. Presently, magnetic resonance imaging (MRI) methods such as R2* and Quantitative Susceptibility Mapping (QSM) were found to be useful in diagnosing the PD based on the iron deposition in different regions of the brain. The objective of this review was to evaluate the efficacy of QSM over R2* in assessment of PD. A comprehensive literature search was made on PubMed-Medline, CINAHL, Science Direct, Scopus, Web of Science, and the Cochrane library databases for original research articles published between 2000 and 2018. Original articles that reported the efficacy of QSM and R2* in assessment of PD were included. A total of 327 studies were identified in the literature search. However, only ten studies were eligible for analysis. Of the ten studies, five studies compared the accuracy of QSM over R2* in measuring the iron deposition in different regions of brain in PD. Our review found that QSM has better accuracy in identifying iron deposition in PD patients compared to R2*. However, there is discrepancy in the results between MRI Imaging methods and Postmortem studies. Additional longitudinal research studies are needed to provide a strong evidence base for the use of MRI imaging methods such as R2*and QSM in accurately measuring iron deposition in different regions of brain and serve as biomarkers in PD.

Methods for quantitative susceptibility and R2* mapping in whole post-mortem brains at 7T applied to amyotrophic lateral sclerosis

Susceptibility weighted magnetic resonance imaging (MRI) is sensitive to the local concentration of iron and myelin. Here, we describe a robust image processing pipeline for quantitative susceptibility mapping (QSM) and R2* mapping of fixed post-mortem, whole-brain data. Using this pipeline, we compare the resulting quantitative maps in brains from patients with amyotrophic lateral sclerosis (ALS) and controls, with validation against iron and myelin histology. Twelve post-mortem brains were scanned with a multi-echo gradient echo sequence at 7T, from which susceptibility and R2* maps were generated. Semi-quantitative histological analysis for ferritin (the principal iron storage protein) and myelin proteolipid protein was performed in the primary motor, anterior cingulate and visual cortices. Magnetic susceptibility and R2* values in primary motor cortex were higher in ALS compared to control brains. Magnetic susceptibility and R2* showed positive correlations with both myelin and ferritin estimates from histology. Four out of nine ALS brains exhibited clearly visible hyperintense susceptibility and R2* values in the primary motor cortex. Our results demonstrate the potential for MRI-histology studies in whole, fixed post-mortem brains to investigate the biophysical source of susceptibility weighted MRI signals in neurodegenerative diseases like ALS.

Quantitative Measurement of Metal Accumulation in Brain of Patients With Wilson's Disease

BACKGROUND

Currently, no study has evaluated metal accumulation in the brains of patients with Wilson's disease by using quantitative susceptibility mapping at 3T MRI. The objectives of this study were to qualitatively and quantitatively evaluate changes in magnetic susceptibility and R2* maps in deep gray matter nuclei to discriminate Wilson's disease patients from healthy controls and to evaluate their sensitivities in diagnosing Wilson's disease.

METHODS

Magnetic susceptibility and R2* maps and conventional T1-weighted, T2-weighted, and T2-weighted fluid-attenuated inversion recovery images were obtained from 17 Wilson's disease patients and 14 age-matched healthy controls on a 3T MRI scanner. Differences between Wilson's disease and healthy control groups in susceptibility and R2* values in multiple deep nuclei were evaluated using a Mann-Whitney U test and receiver operating characteristic curves. The correlations of susceptibility and R2* values with Unified Wilson's Disease Rating Scale score were also performed.

RESULTS

Magnetic susceptibility and R2* can effectively distinguish different types of signal abnormalities. Magnetic susceptibility and R2* values in multiple deep nuclei of Wilson's disease patients were significantly higher than those in healthy controls. Magnetic susceptibility value in the substantia nigra had the highest area under the curve (0.888). There were positive correlations of the Unified Wilson's Disease Rating Scale score with susceptibility values in the caudate nucleus (r = 0.757, P = 0.011), putamen (r = 0.679, P = 0.031), and red nucleus (r = 0.638, P = 0.047), as well as R2* values in the caudate nucleus (r = 0.754, P = 0.012).

CONCLUSIONS

Quantitative susceptibility mapping at 3T could be a useful tool to evaluate metal accumulation in deep gray matter nuclei of Wilson's disease patients. © 2020 International Parkinson and Movement Disorder Society.

Evaluation of abnormal iron distribution in specific regions in the brains of patients with Parkinson's disease using quantitative susceptibility mapping and R2* mapping

The primary aim of the present study was to evaluate abnormal iron distribution in specific regions of the brains in patients with Parkinson's disease (PD) using quantitative susceptibility mapping (QSM) and R2^* mapping, and to compare the diagnostic performances of QSM and R2^* mapping in differentiating patients with PD with that in normal controls. A total of 25 patients with idiopathic PD and 28 sex-and age-matched normal controls were included in the present study and their brains investigated using a 3T scanner. Magnetic resonance imaging techniques, namely, QSM and R2^* mapping, were applied to generate susceptibility and R2^* values. The differences in susceptibility and R2^* values in deep grey matter nuclei between patients with PD and the normal controls were compared using independent samples t-tests. The abilities of QSM and R2^* mapping to classify patients with PD and normal controls were analyzed using receiver operating characteristic curves. Correlation analyses between imaging parameters (e.g. susceptibility and R2^* values) and clinical feature (disease severity assessed using the Hoehn and Yahr score) were performed. The intra-class correlation coefficient (ICC) for susceptibility (ICC=0.977; P<0.001) and R2^* (ICC=0.945; P<0.001) values between two neuro-radiologists were >0.81, showing excellent inter-rater agreement. The susceptibility values were significantly increased in the substantia nigra (SN) and red nucleus, but were decreased in the putamen of patients with PD compared with that in the corresponding brain regions of normal controls. However, increased R2^* values were observed only in the SN in patients with PD. QSM showed higher sensitivity and specificity compared with R2^* mapping to separate the patients with PD from the normal controls. There were no significant correlations between the susceptibility/R2^* values and clinical features in all targeted regions of the brains in patients with PD. In conclusion, both QSM and R2^* mapping are feasible to calculate the iron levels in human brains, and QSM provides a more sensitive and accurate method to assess regional abnormal iron distribution in patients with PD.

Cell density quantification with TurboSPI: R2* mapping with compensation for off-resonance fat modulation

OBJECTIVE

Tracking the migration of superparamagnetic iron oxide (SPIO)-labeled immune cells in vivo is valuable for understanding the immunogenic response to cancer and therapies. Quantitative cell tracking using TurboSPI-based R₂* mapping is a promising development to improve accuracy in longitudinal studies on immune recruitment. However, off-resonance fat signal isochromats lead to modulations in the signal time-course that can be erroneously fit as R₂* signal decay, overestimating the density of labeled cells, while excluding voxels with fat-typical modulations results in underestimation of cell density in voxels with mixed content. Approaches capable of accurate R₂* estimation in the presence of fat are needed.

METHODS

We propose a dual-decay (separate R_2f* and R_2w* for fat and water) Dixon-based signal model that accounts for the presence of fat in a voxel to provide better estimates of SPIO-induced dephasing. This model was tested in silico, in phantoms with varying quantities of fat and SPIO-labeled cells, and in 5 mice injected with SPIO-labeled CD8+ T cells.

RESULTS

In silico single voxel simulations illustrate how the proposed dual-decay model provides stable R_2w* estimates that are invariant to fat content. The proposed model outperforms previous methods when applied to in vitro samples of SPIO-labeled cells and oil prepared with oil content ≥ 15%. Preliminary in vivo results show that, compared to previous methods, the dual-decay model improves the balance of R₂* mapping in fat-dense areas, which will yield more reliable analysis in future cell tracking studies.

DISCUSSION

The proposed model is a promising tool for quantitative TurboSPI R₂* cell tracking, with further refinements offering the possibility of better specificity and sensitivity.

Evaluation of hepatic iron concentration heterogeneities using the MRI R2* mapping method

OBJECTIVE

To measure hepatic iron concentration (HIC) heterogeneities using a magnetic resonance R2* mapping method.

PATIENTS AND METHODS

Ninety-four patients with suspected hepatic iron overload and 10 volunteers were included prospectively. A multi-echo R2* sequence with fat saturation and with three post-processing fitting methods (a single exponential decay model with or without truncation, SED and SEDt, and a constant offset model, COS) was compared to a signal intensity ratio method (SIR), considered as the reference. HIC heterogeneity was evaluated from R2* mapping after placing a ROI on each liver segment.

RESULTS

A strong linear correlation between SIR and R2* methods using the SEDt and COS models was observed (r = 0.973 and 0.955, respectively). Volunteers and patient liver variabilities, quantified by mean intra-liver standard deviation (SD) were 1.58 μmol/g (mean range 5.06 μmol/g) and 4.73 μmol/g (mean range 19.08 μmol/g), respectively. For the patient group, the highest HIC was observed in the IV^th segment. Heterogeneity increased for patients with an HIC > 60 μmol/g (mean intra-liver SD = 13.90 μmol/g; mean range = 50.60 μmol/g).

CONCLUSION

This study is the first to demonstrate in vivo HIC heterogeneities using whole-liver mapping analysis. These preliminary results require confirmation through further studies, but might be useful in cases of single ROI analysis.

Detection of Hyperacute Reactions of Desacetylvinblastine Monohydrazide in a Xenograft Model Using Intravoxel Incoherent Motion DWI and R2* Mapping

OBJECTIVE

This study aimed to investigate the feasibility of intravoxel incoherent motion (IVIM) DWI and R2* (transverse relaxation rate) mapping to monitor the hyperacute therapeutic efficacy of desacetylvinblastine monohydrazide (DAVLBH) on an experimental hepatocellular carcinoma mouse model within 24 hours.

MATERIALS AND METHODS

Forty-four mice were implanted with hepatocellular carcinoma and divided into three random groups. A treatment group and a control group underwent IVIM-DWI and R2* mapping examinations before and after a single injection of DAVLBH or saline at 1, 2, 4, and 24 hours. The pathology group was set for pathologic analysis, including H and E staining and CD31 and hypoxia-inducible factor (HIF)-1α immunohistochemical staining.

RESULTS

DAVLBH caused hyperacute disruptions on the tumor capillaries in the treatment group. Water molecule diffusion (D), microcirculation perfusion (D*), and perfusion fraction (f) decreased initially but then gradually recovered to the baseline level by 24 hours after the first injection of DAVLBH. In contrast, R2* increased dramatically at 1 hour and then gradually decreased from 1 hour to 24 hours after treatment. D*, f, and D showed similar trends and were positively correlated with CD31 expression (r = 0.868, 0.721, and 0.730, respectively), but were negatively correlated with HIF-1α expression (r = -0.784, -0.737, and -0.673, respectively). R2* showed a negative correlation with CD31 expression (r = -0.823) and a positive correlation with HIF-1α expression (r = 0.791).

CONCLUSION

Both IVIM-DWI and R2* mapping can adequately detect the vascular-disrupting effect of DAVLBH as early as 1 hour after injection in a mouse xenograft model. Moreover, D* and R2* are the two most sensitive hemodynamic parameters and can monitor the hyperacute changes associated with DAVLBH treatment in vivo.

Assessment of MR-based R2* and quantitative susceptibility mapping for the quantification of liver iron concentration in a mouse model at 7T

PURPOSE

To assess the feasibility of quantifying liver iron concentration (LIC) using R2* and quantitative susceptibility mapping (QSM) at a high field strength of 7 Tesla (T).

METHODS

Five different concentrations of Fe-dextran were injected into 12 mice to produce various degrees of liver iron overload. After mice were sacrificed, blood and liver samples were harvested. Ferritin enzyme-linked immunosorbent assay (ELISA) and inductively coupled plasma mass spectrometry were performed to quantify serum ferritin concentration and LIC. Multiecho gradient echo MRI was conducted to estimate R2* and the magnetic susceptibility of each liver sample through complex nonlinear least squares fitting and a morphology enabled dipole inversion method, respectively.

RESULTS

Average estimates of serum ferritin concentration, LIC, R2*, and susceptibility all show good linear correlations with injected Fe-dextran concentration; however, the standard deviations in the estimates of R2* and susceptibility increase with injected Fe-dextran concentration. Both R2* and susceptibility measurements also show good linear correlations with LIC (R²  = 0.78 and R²  = 0.91, respectively), and a susceptibility-to-LIC conversion factor of 0.829 ppm/(mg/g wet) is derived.

CONCLUSION

The feasibility of quantifying LIC using MR-based  R2* and QSM at a high field strength of 7T is demonstrated. Susceptibility quantification, which is an intrinsic property of tissues and benefits from being field-strength independent, is more robust than R2* quantification in this ex vivo study. A susceptibility-to-LIC conversion factor is presented that agrees relatively well with previously published QSM derived results obtained at 1.5T and 3T.

Discriminative analysis of regional evolution of iron and myelin/calcium in deep gray matter of multiple sclerosis and healthy subjects

BACKGROUND

Combined R2* and quantitative susceptibility (QS) has been previously used in cross-sectional multiple sclerosis (MS) studies to distinguish deep gray matter (DGM) iron accumulation and demyelination.

PURPOSE

We propose and apply discriminative analysis of regional evolution (DARE) to define specific changes in MS and healthy DGM.

STUDY TYPE

Longitudinal (baseline and 2-year follow-up) retrospective study.

SUBJECTS

Twenty-seven relapsing-remitting MS (RRMS), 17 progressive MS (PMS), and corresponding age-matched healthy subjects.

FIELD STRENGTH/SEQUENCE

4.7T 10-echo gradient-echo acquisition.

ASSESSMENT

Automatically segmented caudate nucleus (CN), thalamus (TH), putamen (PU), globus pallidus, red nucleus (RN), substantia nigra, and dentate nucleus were retrospectively analyzed to quantify regional volumes, bulk mean R2*, and bulk mean QS. DARE utilized combined R2* and QS localized changes to compute spatial extent, mean intensity, and total changes of DGM iron and myelin/calcium over 2 years.

STATISTICAL TESTS

We used mixed factorial analysis for bulk analysis, nonparametric tests for DARE (α = 0.05), and multiple regression analysis using backward elimination of DGM structures (α = 0.05, P = 0.1) to regress bulk and DARE measures with the follow-up Multiple Sclerosis Severity Score (MSSS). False detection rate correction was applied to all tests.

RESULTS

Bulk analysis only detected significant (Q ≤ 0.05) interaction effects in RRMS CN QS (η = 0.45; Q = 0.004) and PU volume (η = 0.38; Q = 0.034). DARE demonstrated significant group differences in all RRMS structures, and in all PMS structures except the RN. The largest RRMS effect size was CN total R2* iron decrease (r = 0.74; Q = 0.00002), and TH mean QS myelin/calcium decrease for PMS (r = 0.70; Q = 0.002). DARE iron increase using total QS demonstrated the highest correlation with MSSS (r = 0.68; Q = 0.0005).

DATA CONCLUSION

DARE enabled discriminative assessment of specific DGM changes over 2 years, where iron and myelin/calcium changes were the primary drivers in RRMS and PMS compared to age-matched controls, respectively. Specific DARE measures of MS DGM correlated with follow-up MSSS, and may reflect complex disease pathology.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018.

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 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.

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.

In vivo normative atlas of the hippocampal subfields using multi-echo susceptibility imaging at 7 Tesla

OBJECTIVES

To generate a high-resolution atlas of the hippocampal subfields using images acquired from 7 T, multi-echo, gradient-echo MRI for the evaluation of epilepsy and neurodegenerative disorders as well as investigating R2* (apparent transverse relaxation rate) and quantitative volume magnetic susceptibility (QS) of the subfields.

EXPERIMENTAL DESIGN

Healthy control subjects (n=17) were scanned at 7 T using a multi-echo gradient-echo sequence and susceptibility-weighted magnitude images, R2* and QS maps were reconstructed. We defined a hippocampal subfield labeling protocol for the magnitude image produced from the average of all echoes and assessed reproducibility through volume and shape metrics. A group-wise diffeomorphic registration procedure was used to generate an average atlas of the subfields for the whole subject cohort. The quantitative MRI maps and subfield labels were then warped to the average atlas space and used to measure mean values of R2* and QS characterizing each subfield.

PRINCIPAL OBSERVATIONS

We were able to reliably label hippocampal subfields on the multi-echo susceptibility images. The group-averaged atlas accurately aligns these structures to produce a high-resolution depiction of the subfields, allowing assessment of both quantitative susceptibility and R2* across subjects. Our analysis of variance demonstrates that there are more apparent differences between the subfields on these quantitative maps than the normalized magnitude images.

CONCLUSION

We constructed a high-resolution atlas of the hippocampal subfields for use in voxel-based studies and demonstrated in vivo quantification of susceptibility and R2* in the subfields. This work is the first in vivo quantification of susceptibility values within the hippocampal subfields at 7 T.