Sub-voxel quantitative susceptibility mapping for assessing whole-brain magnetic susceptibility from ages 4 to 80.

The evolution of magnetic susceptibility of the brain is mainly determined by myelin in white matter (WM) and iron deposition in deep gray matter (DGM). However, existing imaging techniques have limited abilities to simultaneously quantify the myelination and iron deposition within a voxel throughout brain development and aging. For instance, the temporal trajectories of iron in the brain WM and myelination in DGM have not been investigated during the aging process. This study aimed to map the age-related iron and myelin changes in the whole brain, encompassing myelin in DGM and iron deposition in WM, using a novel sub-voxel quantitative susceptibility mapping (QSM) method. To achieve this, a cohort of 494 healthy adults (18-80 years old) was studied. The sub-voxel QSM method was employed to obtain the paramagnetic and diamagnetic susceptibility based on the approximated R 2 ' map from acquired R 2 * map. The linear relationship between R 2 * and R 2 ' maps was established from the regression coefficients on a small cohort data acquired with both 3D gradient recalled echo data and R 2 mapping. Large cohort sub-voxel susceptibility maps were used to create longitudinal and age-specific atlases via group-wise registration. To explore the differential developmental trajectories in the DGM and WM, we employed nonlinear models including exponential and Poisson functions, along with generalized additive models. The constructed atlases reveal the iron accumulation in the posterior part of the putamen and the gradual myelination process in the globus pallidus with aging. Interestingly, the developmental trajectories show that the rate of myelination differs among various DGM regions. Furthermore, the process of myelin synthesis is paralleled by an associated pattern of iron accumulation in the primary WM fiber bundles. In summary, our study offers significant insights into the distinctive developmental trajectories of iron in the brain's WM and myelination/demyelination in the DGM in vivo. These findings highlight the potential of using sub-voxel QSM to uncover new perspectives in neuroscience and improve our understanding of whole-brain myelination and iron deposit processes across the lifespan.

Addressing concomitant gradient phase errors in time-interleaved chemical shift-encoded MRI fat fraction and R2 * mapping with a pass-specific phase fitting method.

PURPOSE: Concomitant gradients induce phase errors that increase quadratically with distance from isocenter. This work proposes a complex-based fitting method that addresses concomitant gradient phase errors in chemical shift encoded (CSE) MRI estimation of proton density fat fraction (PDFF) and R2 * through joint estimation of pass-specific phase terms. This method is applicable to time-interleaved multi-echo gradient-echo acquisitions (i.e., multi-pass acquisitions) and does not require prior knowledge of gradient waveforms typically needed to address concomitant gradient phase errors. THEORY AND METHODS: A CSE-MRI spoiled gradient echo signal model, with pass-specific phase terms, is introduced for non-linear least squares estimation of PDFF and R2 * in the presence of concomitant gradient phase errors. Cramér-Rao lower bound analysis was used to determine noise performance tradeoffs of the proposed fitting method, which was then validated in both phantom and in vivo experiments. RESULTS: The proposed fitting method removed PDFF and R2 * estimation errors up to 12% and 10 s-1 , respectively, at ±12 cm off isocenter (S/I) in a water phantom. In healthy volunteers, PDFF and R2 * bias was reduced by ~10% (12 cm off-isocenter) and ~30 s-1 (16 cm off-isocenter), respectively. An evaluation in 29 clinical liver datasets demonstrated reduced PDFF bias and variability (8.4% improvement in the coefficient of variation), even with the imaging volume centered at isocenter. CONCLUSION: Concomitant gradient induced phase errors in multi-pass CSE-MRI acquisitions can result in PDFF and R2 * estimation biases away from isocenter. The proposed fitting method enables accurate PDFF and R2 * quantification in the presence of concomitant gradient phase errors without knowledge of imaging gradient waveforms.

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 AuFeOx 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.

Liver iron quantification in children and young adults: comparison of a volumetric multi-echo 3-D Dixon sequence with conventional 2-D T2* relaxometry.

BACKGROUND: Magnetic resonance imaging (MRI)-based liver iron quantification is the standard of care to guide chelation therapy in children at risk of hemochromatosis. T2* relaxometry is the most widely used technique but requires third-party software for post-processing. Vendor-provided three-dimensional (3-D) multi-echo Dixon techniques are now available that allow inline/automated post-processing. OBJECTIVE: The purpose of our study was to evaluate the diagnostic accuracy of a volumetric multi-echo Dixon technique using conventional T2* relaxometry as the reference standard in a pediatric and young adult population. MATERIALS AND METHODS: In this retrospective study, we queried the radiology information system to identify all MRIs performed for liver iron quantification from July 2015 to January 2020. All patients had undergone T2* relaxometry on a 1.5-tesla (T) scanner for liver iron concentration (LIC) estimation. In addition, a 3-D multi-echo Dixon was performed using Siemens Healthineers LiverLab (Erlangen, Germany). Two readers independently estimated liver R2* and T2* on the multi-echo Dixon by drawing free-hand regions of interest on the scanner-generated R2* and T2* maps. Conventional T2*-relaxometry-based LIC was the reference standard. We estimated interobserver agreement by concordance correlation coefficient (CCC). We used Bland-Altman analysis and Pearson correlation coefficient (r) to compare LIC by the two methods. RESULTS: Fifty-four MRIs on 38 patients (22 females) were available for analysis. Mean patient age was 11.8 years (standard deviation [SD] 5.3 years). Reference standard LIC ranged 1.1-21.1 (median 6.8) mg/g dry weight of liver. The concordance between readers for T2* estimation using 3-D multi-echo Dixon was substantial (CCC 0.99, confidence interval 0.99-1.00). Bland-Altman plot showed that all observations were clustered around the zero bias line if the LIC average was ≤8 mg/g, and r was very strong (reader 1 r=0.93, reader 2 r=0.92, both P-values <0.001). With increasing LIC, there was a pattern of poor agreement on the Bland-Altman plot, with observations crossing the lower limits of agreement, and r was very weak (reader 1 r=0.05, P-value 0.84; reader 2 r=0.17, P-value 0.44). CONCLUSION: Vendor-based 3-D multi-echo Dixon allows for excellent interobserver correlation in liver T2* estimation. LIC estimated by this method has a very strong correlation with conventional T2* relaxometry if liver iron overload is mild-moderate (LIC ≤8 mg/g).

Quantitative Susceptibility Mapping: Technical Considerations and Clinical Applications in Neuroimaging.

Quantitative susceptibility mapping (QSM) is a novel magnetic resonance imaging (MRI) technique for quantifying the spatial distribution of magnetic susceptibility within an object or tissue. Recently, QSM has been widely used to study various dominant magnetic susceptibility sources in the brain, including iron and calcium. In addition, the method enables mapping of the cerebral metabolic rate of oxygen, which could act as a new metabolic biomarker for diseases that involve disruption of the brain's oxygen supply. Thus, the clinical applications of QSM are wide-reaching and hold great promise as imaging biomarkers for studying several neurological diseases. This review aims to summarize the physical concepts and potential clinical applications of QSM in neuroimaging. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

Sensitivity of quantitative relaxometry and susceptibility mapping to microscopic iron distribution.

PURPOSE: Determine the impact of the microscopic spatial distribution of iron on relaxometry and susceptibility-based estimates of iron concentration. METHODS: Monte Carlo simulations and in vitro experiments of erythrocytes were used to create different microscopic distributions of iron. Measuring iron with intact erythrocyte cells created a heterogeneous distribution of iron, whereas lysing erythrocytes was used to create a homogeneous distribution of iron. Multi-echo spin echo and spoiled gradient echo acquisitions were then used to estimate relaxation parameters ( R2 and R2* ) and susceptibility. RESULTS: Simulations demonstrate that R2 and R2* measurements depend on the spatial distribution of iron even for the same iron concentration and volume susceptibility. Similarly, in vitro experiments demonstrate that R2 and R2* measurements depend on the microscopic spatial distribution of iron whereas the quantitative susceptibility mapping (QSM) susceptibility estimates reflect iron concentration without sensitivity to spatial distribution. CONCLUSIONS: R2 and R2* for iron quantification depend on the spatial distribution or iron. QSM-based estimation of iron concentration is insensitive to the microscopic spatial distribution of iron, potentially providing a distribution independent measure of iron concentration.

Accurate iron quantification in colloids and nanocomposites by a simple UV-Vis protocol.

The selection and comparative study is reported of calibration curves to quantify iron by a simple UV-Vis protocol based on the formation of iron (III) chloride complexes. The reliability of each calibration curve was evaluated using statistical and analytical parameters. The robustness of each calibration curve using superparamagnetic iron oxide nanoparticles (SPIONs) of different sizes and surface functionalization is demonstrated . We have also evaluated the effect of the particle coating and estimated the minimum time to ensure the full oxidation of iron (II) to (III) in sample solutions. Results from UV-Vis are comparable with those obtained from ICP-OES and from other spectroscopic techniques to quantify the iron. We advocate the proposed protocol as a simple and non-expensive route to determine accurately the iron content in colloidal and nanocomposite iron-based materials. Graphical abstract.

Quantifying iron content in magnetic resonance imaging.

Measuring iron content has practical clinical indications in the study of diseases such as Parkinson's disease, Huntington's disease, ferritinopathies and multiple sclerosis as well as in the quantification of iron content in microbleeds and oxygen saturation in veins. In this work, we review the basic concepts behind imaging iron using T2, T2*, T2', phase and quantitative susceptibility mapping in the human brain, liver and heart, followed by the applications of in vivo iron quantification in neurodegenerative diseases, iron tagged cells and ultra-small superparamagnetic iron oxide (USPIO) nanoparticles.

Prospective Evaluation of an R2* Method for Assessing Liver Iron Concentration (LIC) Against FerriScan: Derivation of the Calibration Curve and Characterization of the Nature and Source of Uncertainty in the Relationship.

BACKGROUND: FerriScan is the method-of-choice for noninvasive liver iron concentration (LIC) quantification. However, it has a number of drawbacks including cost and expediency. PURPOSE/HYPOTHESIS: To characterize an R2*-based MRI technique that may potentially be used as an alternative to FerriScan. This was accomplished through the derivation of a calibration curve that characterized the relationship between FerriScan-derived LIC and R2*. The nature and source of uncertainty in this curve were investigated. It was hypothesized that the source of uncertainty is heterogeneity of LIC across the liver. STUDY TYPE: Prospective. SUBJECTS: In all, 125 patients (69 women, 56 men) undergoing chelation treatment for iron overload prospectively underwent FerriScan and R2* MRI during the same exam. FIELD STRENGTH/SEQUENCE: Pulse sequences included 2D multislice spin-echo pulse for FerriScan, and a prototype 3D 6-echo gradient echo acquisition for R2* mapping at 1.5T. ASSESSMENT: A linear calibration curve was derived from the relationship between FerriScan-derived LIC estimates and R2* through least-squares fitting. STATISTICAL TESTS: The nature of the uncertainty in the curve was characterized through tests of normality and homoscedasticity. The source of uncertainty was tested by comparing the magnitude of LIC variation over the FerriScan ROI to the observed uncertainty in the R2*-derived LIC estimates. RESULTS: A linear relationship between logarithmically transformed FerriScan-derived LIC and R2* (log{FerriScan-derived LIC} = 1.029 log{R2*} - 3.822) was confirmed. Uncertainty was random, with a behaviour that was normal and homoscedastic. The source of uncertainty was confirmed as iron heterogeneity across the liver. The nontransformed calibration curve was: FerriScan-derived LIC = 0.0266⋅R2*, with a constant coefficient-of-variation of 0.32. DATA CONCLUSION: FerriScan and R2* techniques were found to provide equivalent quantification of LIC in this study. Any difference in accuracy or precision was at a level lower than the uncertainty caused by variation in LIC over the liver. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1467-1474.

Quantitative analysis of hepatic iron in patients suspected of coexisting iron overload and steatosis using multi-echo single-voxel magnetic resonance spectroscopy: Comparison with fat-saturated multi-echo gradient echo sequence.

BACKGROUND: The coexistence of hepatic iron and fat is common in patients with hyperferritinemia, which plays an interactive and aggressive role in the progression of diseases (fibrosis, cirrhosis, and hepatocellular carcinomas). PURPOSE: To evaluate a modified high-speed T2 -corrected multi-echo, single voxel spectroscopy sequence (HISTOV) for liver iron concentration (LIC) quantification in patients with hyperferritinemia, with simultaneous fat fraction (FF) estimation. STUDY TYPE: Retrospective cohort study. POPULATION: Thirty-eight patients with hyperferritinemia were enrolled. FIELD STRENGTH/SEQUENCE: HISTOV, a fat-saturated multi-echo gradient echo (GRE) sequence, and a spin echo sequence (FerriScan) were performed at 1.5T. ASSESSMENT: R2 of the water signal and FF were calculated with HISTOV, and R2* values were derived from the GRE sequence, with R2 and LIC from FerriScan serving as the references. STATISTICAL TESTS: Linear regression, correlation analyses, receiver operating characteristic analyses, and Bland-Altman analyses were conducted. RESULTS: Abnormal hepatic iron load was detected in 32/38 patients, of whom 10/32 had coexisting steatosis. Strong correlation was found between R2* and FerriScan-LIC (R2 = 0.861), and between HISTOV-R2_ water and FerriScan-R2 (R2 = 0.889). Furthermore, HISTOV-R2_ water was not correlated with HISTOV-FF. The area under the curve (AUC) for HISTOV-R2_ water was 0.974, 0.971, and 1, corresponding to clinical FerriScan-LIC thresholds of 1.8, 3.2, and 7.0 mg/g dw, respectively. No significant difference in the AUC was found between HISTOV-R2_ water and R2* at any of the LIC thresholds, with P-values of 0.42, 0.37, and 1, respectively. HISTOV-LIC showed excellent agreement with FerriScan-LIC, with a mean bias of 0.00 ± 1.18 mg/g dw, whereas the mean bias between GRE-LIC and FerriScan-LIC was 0.53 ± 1.49 mg/g dw. DATA CONCLUSION: HISTOV is useful for the quantification and grading of liver iron overload in patients with hyperferritinemia, particularly in cases with coexisting steatosis. HISTOV-LIC showed no systematic bias compared with FerriScan-LIC, making it a promising alternative for iron quantification. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage 2 J. Magn. Reson. Imaging 2018.

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.

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.

T2* Measurement bias due to concomitant gradient fields.

PURPOSE: To demonstrate that concomitant magnetic fields can cause significant spatially dependent biases in T2* relaxometry measurements with implications for clinical applications such as BOLD and dynamic susceptibility contrast-enhanced MRI. THEORY AND METHODS: After developing a theoretical framework for intravoxel dephasing and signal loss from concomitant magnetic fields, this framework and the effect of concomitant fields on T2* are validated with phantom experiments and numerical simulation. In lower leg and renal T2* mapping, we quantify measurement bias for imaging protocols with high gradient amplitude multiecho readouts, comparable to those used in clinical applications. RESULTS: Concordance between phantom experiment and numerical simulation validate the theoretical framework. Changes in T2* measured in the lower leg and kidney varied by up to 15% and 35%, respectively, as a result of concomitant gradient effects when compared with the control measurements. CONCLUSION: Concomitant magnetic fields produced by imaging gradient coils can cause clinically significant T2* mapping errors when high amplitude, long duration gradient waveforms are used. While we have shown that measurement biases can be quite large, modification of imaging parameters can potentially reduce concomitant field-induced measurement errors to acceptable levels. Magn Reson Med 77:1562-1572, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

The effects of concomitant gradients on chemical shift encoded MRI.

PURPOSE: The purpose of this work was to characterize the effects of concomitant gradients (CGs) on chemical shift encoded (CSE)-based estimation of B0 field map, proton density fat fraction (PDFF), and R2*. THEORY: A theoretical framework was used to determine the effects of CG-induced phase errors on CSE-MRI data. METHODS: Simulations, phantom experiments, and in vivo experiments were conducted at 3 Tesla to assess the effects of CGs on quantitative CSE-MRI techniques. Correction of phase errors attributable to CGs was also investigated to determine whether these effects could be removed. RESULTS: Phase errors attributed to CGs introduce errors in the estimation of B0 field map, PDFF, and R2*. Phantom and in vivo experiments demonstrated that CGs can introduce estimation errors greater than 30 Hz in the B0 field map, 10% in PDFF, and 16 s-1 in R2*, 16 cm off isocenter. However, CG phase correction before parameter estimation was able to reduce estimation errors to less than 10 Hz in the B0 field map, 1% in PDFF, and 2 s-1 in R2*. CONCLUSION: CG effects can impact CSE-MRI, leading to inaccurate estimation of B0 field map, PDFF, and R2*. However, correction for phase errors caused by CGs improve the accuracy of quantitative parameters estimated from CSE-MRI acquisitions. Magn Reson Med 78:730-738, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Can multi-slice or navigator-gated R2* MRI replace single-slice breath-hold acquisition for hepatic iron quantification?

BACKGROUND: Liver R2* values calculated from multi-gradient echo (mGRE) magnetic resonance images (MRI) are strongly correlated with hepatic iron concentration (HIC) as shown in several independently derived biopsy calibration studies. These calibrations were established for axial single-slice breath-hold imaging at the location of the portal vein. Scanning in multi-slice mode makes the exam more efficient, since whole-liver coverage can be achieved with two breath-holds and the optimal slice can be selected afterward. Navigator echoes remove the need for breath-holds and allow use in sedated patients. OBJECTIVE: To evaluate if the existing biopsy calibrations can be applied to multi-slice and navigator-controlled mGRE imaging in children with hepatic iron overload, by testing if there is a bias-free correlation between single-slice R2* and multi-slice or multi-slice navigator controlled R2*. MATERIALS AND METHODS: This study included MRI data from 71 patients with transfusional iron overload, who received an MRI exam to estimate HIC using gradient echo sequences. Patient scans contained 2 or 3 of the following imaging methods used for analysis: single-slice images (n = 71), multi-slice images (n = 69) and navigator-controlled images (n = 17). Small and large blood corrected region of interests were selected on axial images of the liver to obtain R2* values for all data sets. Bland-Altman and linear regression analysis were used to compare R2* values from single-slice images to those of multi-slice images and navigator-controlled images. RESULTS: Bland-Altman analysis showed that all imaging method comparisons were strongly associated with each other and had high correlation coefficients (0.98 ≤ r ≤ 1.00) with P-values ≤0.0001. Linear regression yielded slopes that were close to 1. CONCLUSION: We found that navigator-gated or breath-held multi-slice R2* MRI for HIC determination measures R2* values comparable to the biopsy-validated single-slice, single breath-hold scan. We conclude that these three R2* methods can be interchangeably used in existing R2*-HIC calibrations.

Quantitative susceptibility mapping (QSM) of white matter multiple sclerosis lesions: Interpreting positive susceptibility and the presence of iron.

PURPOSE: Within multiple sclerosis (MS) lesions iron is present in chronically activated microglia. Thus, iron detection with MRI might provide a biomarker for chronic inflammation within lesions. Here, we examine contributions of iron and myelin to magnetic susceptibility of lesions on quantitative susceptibility mapping (QSM). METHODS: Fixed MS brain tissue was assessed with MRI including gradient echo data, which was processed to generate field (phase), R2* and QSM. Five lesions were sectioned and evaluated by immunohistochemistry for presence of myelin, iron and microglia/macrophages. Two of the lesions had an elemental analysis for iron concentration mapping, and their phospholipid content was estimated from the difference in the iron and QSM data. RESULTS: Three of the five lesions had substantial iron deposition that was associated with microglia and positive susceptibility values. For the two lesions with elemental analysis, the QSM derived phospholipid content maps were consistent with myelin labeled histology. CONCLUSION: Positive susceptibility values with respect to water indicate the presence of iron in MS lesions, although both demyelination and iron deposition contribute to QSM.

Iron mapping using the temperature dependency of the magnetic susceptibility.

PURPOSE: The assessment of iron content in brain white matter (WM) is of high importance for studying neurodegenerative diseases. While R2 * mapping and quantitative susceptibility mapping is suitable for iron mapping in gray matter, iron mapping in WM still remains an unsolved problem. We propose a new approach for iron mapping, independent of diamagnetic contributions of myelin by assessing the temperature dependency of the paramagnetic susceptibility. THEORY AND METHODS: We used unfixed human brain slices for relaxometry and calculated R2 ' as a measure for microscopic susceptibility variations at several temperatures (4°C-37°C) at 3 Tesla. The temperature coefficient of R2 ' (TcR2p) was calculated by linear regression and related to the iron concentration found by subsequent superconducting quantum interference device (SQUID) magnetometry and by inductively coupled plasma mass spectrometry. RESULTS: In line with SQUID measurements, R2 ' mapping showed a linear temperature dependency of the bulk susceptibility with the highest slope in gray matter. Even in WM, TcR2p yielded a high linear correlation with the absolute iron concentration. CONCLUSION: According to Curie's law, only paramagnetic matter exhibits a temperature dependency while the diamagnetism shows no effect. We have demonstrated that the temperature coefficient (TcR2p) can be used as a measure of the paramagnetic susceptibility despite of an unknown diamagnetic background.

Liver fat quantification using a multi-step adaptive fitting approach with multi-echo GRE imaging.

PURPOSE: The purpose of this study was to develop a multi-step adaptive fitting approach for liver proton density fat fraction (PDFF) and R(2)* quantification, and to perform an initial validation on a broadly available hardware platform. THEORY AND METHODS: The proposed method uses a multi-echo three-dimensional gradient echo acquisition, with initial guesses for the fat and water signal fractions based on a Dixon decomposition of two selected echoes. Based on magnitude signal equations with a multi-peak fat spectral model, a multi-step nonlinear fitting procedure is then performed to adaptively update the fat and water signal fractions and R(2)* values. The proposed method was validated using numeric phantoms as ground truth, followed by preliminary clinical validation of PDFF calculations against spectroscopy in 30 patients. RESULTS: The results of the proposed method agreed well with the ground truth of numerical phantoms, and were relatively insensitive to changes in field strength, field homogeneity, monopolar/bipolar readout, signal to noise ratio, and echo time selections. The in vivo patient study showed excellent consistency between the PDFF values measured with the proposed approach compared with spectroscopy. CONCLUSION: This multi-step adaptive fitting approach performed well in both simulated and initial clinical evaluation, and shows potential in the quantification of hepatic steatosis.

MR characterization of hepatic storage iron in transfusional iron overload.

PURPOSE: To quantify the two principal forms of hepatic storage iron, diffuse, soluble iron (primarily ferritin), and aggregated, insoluble iron (primarily hemosiderin) using a new MRI method in patients with transfusional iron overload. MATERIALS AND METHODS: Six healthy volunteers and 20 patients with transfusion-dependent thalassemia syndromes and iron overload were examined. Ferritin- and hemosiderin-like iron were determined based on the measurement of two distinct relaxation parameters: the "reduced" transverse relaxation rate, RR2 , and the "aggregation index," A, using three sets of Carr-Purcell-Meiboom-Gill (CPMG) datasets with different interecho spacings. Agarose phantoms, simulating the relaxation and susceptibility properties of tissue with different concentrations of dispersed (ferritin-like) and aggregated (hemosiderin-like) iron, were used for validation. RESULTS: Both phantom and in vivo human data confirmed that transverse relaxation components associated with the dispersed and aggregated iron could be separated using the two-parameter (RR2 , A) method. The MRI-determined total hepatic storage iron was highly correlated (r = 0.95) with measurements derived from biopsy or biosusceptometry. As total hepatic storage iron increased, the proportion stored as aggregated iron became greater. CONCLUSION: This method provides a new means for noninvasive MRI determination of the partition of hepatic storage iron between ferritin and hemosiderin in iron overload disorders.

Quantification of Macrophage Cellular Ferrous Iron (Fe2+) Content Using a Highly Specific Fluorescent Probe in a Plate Reader.

Macrophages are at the center of innate immunity and iron metabolism. In the case of an infection, macrophages adapt their cellular iron metabolism to deprive iron from invading bacteria to combat intracellular bacterial proliferation. A concise evaluation of the cellular iron content upon an infection with bacterial pathogens and diverse cellular stimuli is necessary to identify underlying mechanisms concerning iron homeostasis in macrophages. For the characterization of cellular iron levels during infection, we established an in vitro infection model where the murine macrophage cell line J774A.1 is infected with Salmonella enterica serovar Typhimurium (S.tm), the mouse counterpart to S. enterica serovar Typhi, under normal and iron-overload conditions using ferric chloride (FeCl3) treatment. To evaluate the effect of infection and iron stimulation on cellular iron levels, the macrophages are stained with FerroOrange. This fluorescent probe specifically detects Fe2+ ions and its fluorescence can be quantified photometrically in a plate reader. Importantly, FerroOrange fluorescence does not increase with chelated iron or other bivalent metal ions. In this protocol, we present a simple and reliable method to quantify cellular Fe2+ levels in cultured macrophages by applying a highly specific fluorescence probe (FerroOrange) in a TECAN Spark microplate reader. Compared to already established techniques, our protocol allows assessing cellular iron levels in innate immune cells without the use of radioactive iron isotopes or extensive sample preparation, exposing the cells to stress. Key features • Easy quantification of Fe2+ in cultured macrophages with a fluorescent probe. • Analysis of iron in living cells without the need for fixation. • Performed on a plate reader capable of 540 nm excitation and 585 nm emission by trained employees for handling biosafety level 2 bacteria.