The role of MRI to estimate liver iron concentration (LIC) for identifying patients with iron overload and guiding the titration of chelation therapy is increasingly established for routine clinical practice. However, the existence of multiple MRI-based LIC quantification techniques limits standardization and widespread clinical adoption. In this article, we review the existing and widely accepted MRI-based LIC estimation methods at 1.5 T and 3 T: signal intensity ratio (SIR) and relaxometry (R2 and R2*) and discuss the basic principles, acquisition and analysis protocols, and MRI-LIC calibrations for each technique. Further, we provide an up-to-date information on MRI vendor implementations and available offline commercial and free software for each MRI-based LIC quantification approach. We also briefly review the emerging and advanced MRI techniques for LIC estimation and their current limitations for clinical use. Lastly, we discuss the implications of MRI-based LIC measurements on clinical use and decision-making in the management of patients with iron overload. Some of the key highlights from this review are as follows: 1) Both R2 and R2* can estimate accurate and reproducible LIC, when validated acquisition parameters and analysis protocols are applied, 2) Although the Ferriscan R2 method has been widely used, recent consensus and guidelines endorse R2*-MRI as the most accurate and reproducible method for LIC estimation, 3) Ongoing efforts aim to establish R2*-MRI as the standard approach for quantifying LIC, and 4) Emerging R2*-MRI techniques employ radial sampling strategies and offer improved motion compensation and broader dynamic range for LIC estimation. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

T1 mapping of the liver is confounded by the presence of fat. Multiparametric T1 mapping combines fat-water separation with T1-weighting to enable imaging of water-specific T1 (T1Water), proton density fat fraction (PDFF), and T2* values. However, normative T1Water values in the liver and its dependence on age/sex is unknown.

Determine normative values for T1Water in the liver with comparison to MOLLI and evaluate a T2*-compensation approach to reduce T1 variability.

Prospective observational; phantoms.

One hundred twenty-four controls (56 male, 18-75 years), 50 patients at-risk for liver disease (18 male, 30-76 years).

2.89 T; Saturation-recovery chemical-shift encoded T1 Mapping (SR-CSE); MOLLI.

SR-CSE provided T1Water measurements, PDFF and T2* values in the liver across three slices in 6 seconds. These were compared with MOLLI T1 values. A new T2*-compensation approach to reduce T1 variability was evaluated test/re-test reproducibility.

Linear regression, ANCOVA, t-test, Bland and Altman, intraclass correlation coefficient (ICC). P < 0.05 was considered statistically significant.

Liver T1 values were significantly higher in healthy females (F) than males (M) for both SR-CSE (F-973 ± 78 msec, M-930 ± 72 msec) and MOLLI (F-802 ± 55 msec, M-759 ± 69 msec). T1 values were negatively correlated with age, with similar sex- and age-dependencies observed in T2*. The T2*-compensation model reduced the variability of T1 values by half and removed sex- and age-differences (SR-CSE: F-946 ± 36 msec, M-941 ± 43 msec; MOLLI: F-775 ± 35 msec, M-770 ± 35 msec). At-risk participants had elevated PDFF and T1 values, which became more distinct from the healthy cohort after T2*-compensation. MOLLI systematically underestimated liver T1 values by ~170 msec with an additional positive T1-bias from fat content (~11 msec/1% in PDFF). Reproducibility ICC values were ≥0.96 for all parameters.

Liver T1Water values were lower in males and decreased with age, as observed for SR-CSE and MOLLI acquisitions. MOLLI underestimated liver T1 with an additional large positive fat-modulated T1 bias. T2*-compensation removed sex- and age-dependence in liver T1, reduced the range of healthy values and increased T1 group differences between healthy and at-risk groups.

2 TECHNICAL EFFICACY: Stage 1.

Gene-expression reporter systems, such as green fluorescent protein, have been instrumental to understanding biological processes in living organisms at organ system, tissue, cell, and molecular scales. More than 30 years of work on developing MRI-visible gene-expression reporter systems has resulted in a variety of clever application-specific methods. However, these techniques have not yet been widely adopted, so a general-purpose expression reporter is still required. Here, we demonstrate that the manganese ion transporter Zip14 is an in vivo MRI-visible, flexible, and robust gene-expression reporter to meet this need.

Plasmid constructs consisting of a cell type-specific promoter, gene coding for human Zip14, and a histology-visible tag were packaged into adeno-associated viruses. These viruses were intracranially injected into the mouse brain. Serial in vivo MRI was performed using a vendor-supplied 3D-MPRAGE sequence. No additional contrast agents were administered. Animals were sacrificed after the last imaging timepoint for immunohistological validation.

Neuron-specific overexpression of Zip14 produced substantial and long-lasting changes in MRI contrast. Using appropriate viruses enabled both anterograde and retrograde neural tracing. Expression of Zip14 in astrocytes also enabled MRI of glia populations in the living mammalian brain.

The flexibility of this system as an MRI-visible gene-expression reporter will enable many applications of serial, high-resolution imaging of gene expression for basic science and therapy development.

To summarize the research progress of magnetic resonance imaging (MRI) in quantifying liver iron load.

To summarize the current status and progress of MRI technology in the quantitative study of liver iron load through reviewing the relevant literature at home and abroad.

Different MRI sequence examination techniques have formed a series of non-invasive methods for the examination of liver iron load. These techniques have important clinical significance in the imaging diagnosis of liver iron load. So far, the main MRI methods used to assess liver iron load are: signal intensity measurement method (signal intensity, SI) [signal intensity ratio (SIR) and difference in in-phase and out-of-phase signal intensity], T2/R2 measurement (such as FerriScan technique), ultra-short echo time (UTE) imaging technique, and susceptibility weighted imaging (including conventional susceptibility weighted imaging) (SWI), quantitative susceptibility mapping (QSM), T2*/R2* measurement, Dixon and its derivative techniques.

MRI has become the first choice for the non-invasive examination of liver iron overload, and it is helpful to improve the early detection of liver injury, liver fibrosis, liver cirrhosis and liver cancer caused by liver iron overload.

Conventional single-echo spin-echo T2 mapping used for liver iron quantification is too long for breath-holding. This study investigated a short TR (~100 ms) single-echo spin-echo T2 mapping technique wherein each image (corresponding to a single TE) could be acquired in ~17 s-short enough for a breath-hold. TE images were combined for T2 fitting. To avoid T1 bias, each TE acquisition incremented TR to maintain a constant TR-TE.

Experiments at 1.5T validated the technique's accuracy in phantoms, 9 healthy volunteers, and 5 iron overload patients. In phantoms and healthy volunteers, the technique was compared to the conventional approach of constant TR for all TEs. Iron overload results were compared to FerriScan.

In phantoms, the constant TR-TE technique provided unbiased estimates of T2, while the conventional constant TR approach underestimated it. In healthy volunteers, there was no significant discrepancy at the 95% confidence level between constant TR-TE and reference T2 values, whereas there was for constant TR scans. In iron overload patients, there was a high correlation between constant TR-TE and FerriScan T2 values (r2 = 0.95), with a discrepancy of 0.6+/- 1.4 ms.

The short-TR single-echo breath-hold spin-echo technique provided unbiased estimates of T2 in phantoms and livers.

Purpose  T2* is the gold standard for iron quantification in liver as well as myocardium. In this study, we evaluated the diagnostic accuracy of myocardial T1 mapping for the assessment of myocardial iron overload (MIO) as compared to the T2* mapping in patients with thalassemia major (TM). Methods  Consecutive TM patients attending the thalassemia clinic were prospectively enrolled. Magnetic resonance imaging was performed on a 1.5 T scanner (Siemens Healthineers, Germany) using a gradient echo T2* as well as a T1 mapping (MOLLI) sequence done at a mid-ventricular short-axis single 8 mm slice of the left ventricle. Values were analyzed by manually drawing a region of interest in the mid-septum. T2*less than 20ms was used as the cutoff for significant MIO. Results  One-hundred three patients (58 males, mean age: 17 ± 7.8 years, mean ferritin: 2009.5 µg/L) underwent cardiovascular magnetic resonance. Median T2* of myocardium was 33.45ms. Nineteen patients (18.4%) had T2*less than 20ms. T1 value was low (<850ms) in all the patients with T2* less than 20 ms. Receiver operating characteristic curve analysis revealed the best cutoff of native T1 mapping value as 850 ms which had high specificity (95.2%), sensitivity (94.2%) and negative predictive value (98.8%) for T2* less than 20ms. There was excellent agreement between T1 and T2* for diagnosis of MIO (Kappa-0.848, p <0.001). We did not find any patient who had normal T1 mapping values but had MIO on T2*. Conclusion  T1 and T2* correlate well and normal T1 values may rule out presence of MIO. T1 mapping can act as additional imaging marker for MIO and may be helpful in centers with nonavailability or limited experience of T2*.

To investigate the value of T2* technique on 3.0 T magnetic resonance imaging (MRI) in evaluating the changes of cardiac and hepatic iron load before and after hematopoietic stem cell transplantation (HSCT) in patients with thalassemia (TM), the 141 TM patients were divided into 6 group for subgroup analysis: 6, 12, 18, 24 and > 24 months group, according to the postoperative interval. The T2* values of heart and liver (H-T2*, L-T2*) were quantified in TM patients before and after HSCT using 3.0 T MRI T2* technology, and the corresponding serum ferritin (SF) was collected at the same time, and the changes of the three before and after HSCT were compared. The overall H-T2* (P = 0.001) and L-T2* (P = 0.041) of patients after HSCT were higher than those before HSCT (mean relative changes = 19.63%, 7.19%). The H-T2* (P < 0.001) and L-T2* (P < 0.001) > 24 months after HSCT were significantly higher than those before HSCT (mean relative changes = 69.19%, 93.73%). The SF of 6 months (P < 0.001), 12 months (P = 0.008), 18 months (P = 0.002) and > 24 months (P = 0.001) were significantly higher than those before HSCT (mean relative changes = 57.93%, 73.84%, 128.51%, 85.47%). There was no significant improvement in cardiac and liver iron content in TM patients within 24 months after HSCT, while the reduction of cardiac and liver iron content in patients is obvious when > 24 months after HSCT.

MR transverse relaxation rate R₂* has been shown to be useful for monitoring liver iron overload. A sequence enabling acquisition of the whole liver in a single breath hold is now available, thus allowing volumetric hepatic R₂* distribution studies. We evaluated the feasibility of computer-assisted whole liver segmentation of 3 D multi-gradient-echo MRI data, and compared whole liver R₂* determination to analyzing only a single slice. Also, segmental R₂* differences were studied.

The liver of 44 patients, investigated by multi-gradient echo MRI at 1.5 T, was segmented and divided into nine segments. Segmental R₂* values were examined for all patients together and with respect to two criteria: average R₂* values, and reason for iron overload. Correlation of single-slice and volumetric data was tested with Spearman's rank test, segmental and group differences were evaluated by analysis of variance.

Whole-liver R₂* values correlated excellent to single slice data (p < 0.001). The lowest R₂* occurred in segment 1 (S1), differences of S1 with regard to other segments were significant in five cases and highly significant in two cases. Patients with high average R₂* showed significant differences between S1 and segments 2, 6, and 7. Disease-related differences with respect to S1 were significant in segments 3 to 5 and 7.

Our results suggest inhomogeneous hepatic iron distribution. Low R₂* in S1 may be explained by its special vascularization.

· Hepatic R2* distribution is not as homogeneous as previously thought.. · Liver segments might have a functional relevance.. · Segmental and total liver R2* values coincide best in segment 8..

· Wunderlich AP, Cario H, Kannengießer S et al. Volumetric Evaluation of 3D Multi-Gradient-Echo MRI Data to Assess Whole Liver Iron Distribution by Segmental R2* Analysis: First Experience. Fortschr Röntgenstr 2023; 195: 224 - 233.

Quantitative T_1ρ imaging is an emerging technique to assess the biochemical properties of tissues. In this paper, we report our observation that liver iron content (LIC) affects T_1ρ quantification of the liver at 3.0T field strength and develop a method to correct the effect of LIC.

On-resonance R_1ρ (1/T_1ρ ) is mainly affected by the intrinsic R₂ (1/T₂ ), which is influenced by LIC. As on-resonance R_1ρ is closely related to the Carr-Purcell-Meiboom-Gill (CPMG) R₂ , and because the calibration between CPMG R₂ and LIC has been reported at 1.5T, a correction method was proposed to correct the R₂ contribution to the R_1ρ . The correction coefficient was obtained from the calibration results and related transformed factors. To compensate for the difference between CPMG R₂ and R_1ρ , a scaling factor was determined using the values of CPMG R₂ and R_1ρ , obtained simultaneously from a single breath-hold from volunteers. The livers of 110 subjects were scanned to validate the correction method.

LIC was significantly correlated with R_1ρ in the liver. However, when the proposed correction method was applied to R_1ρ , LIC and the iron-corrected R_1ρ were not significantly correlated.

LIC can affect T_1ρ in the liver. We developed an iron-correction method for the quantification of T_1ρ in the liver at 3.0T.

This study is to investigate the association of the liver and spleen signal intensity on MRI with anemia in patients with gynecologic cancer.

332 patients with gynecological cancer and 78 healthy women underwent MRI examination. Liver and spleen MRI parameters and laboratory tests were obtained within 1 week. The signal intensity ratios of liver and spleen to the paraspinous muscle were calculated on gradient echo T1-weighted images (T1WI) and T2-weighted images (T2WI) in both patients and healthy women, respectively.

The ratios of liver and spleen to paraspinous muscle on T1WI and T2WI were lower in patients than in the healthy women, respectively (all P<0.0001). The ratios of the liver and spleen to paraspinous muscle on T1WI and T2WI decreased with the increasing stage of anemia and decreasing of the hemoglobin levels (all P<0.001). The ratios of the liver to paraspinous muscle on T1WI, spleen to paraspinous muscle on T1WI, and the liver and spleen to paraspinous muscle on T2WI could predict anemia stage≥1 (AUC=0.576, 0.643, 0.688, and 0.756, respectively), ≥2 (AUC=0.743, 0.714, 0.891, and 0.922, respectively) and 3 (AUC=0.851, 0.822, 0.854, and 0.949, respectively).

T2WI-based spleen signal intensity ratios showed the highest potential for noninvasive evaluation of anemia in gynecological cancer.

The aim of this study was to reproduce relaxivity-iron calibration in hepatic iron overload using a Monte Carlo model, and further extend the model with multiple spin echo (MSE) imaging. As previously reported, relationships between relaxation rates ( R2* and single spin echo R₂ ) and liver iron concentration (LIC) can be characterized by a Monte Carlo model incorporating realistic liver structure, iron distribution, and proton mobility. In this study, relaxivity-iron calibration curves at 1.5 and 3.0 T were simulated using the Monte Carlo model. Furthermore, the model was extended with MSE imaging, and iron calibrations were evaluated using two different fitting models: mononexponential with a constant offset and nonmonoexponential. Results consistent with previous empirical calibrations and Monte Carlo predictions were accurately reproduced for relaxivity-iron calibration. The predicted R2* and single spin echo R₂ increased by a factor of 2.00 and 1.51, respectively, at 1.5 versus 3.0 T. MSE signals and their corresponding R₂ depended strongly on LIC, interecho time, and field strength. Preliminary results showed that a nonmonoexponential model accurately characterizes the simulated MSE signals, and that strong correlations were found between predicted relaxation parameters and LIC. In conclusion, relaxivity-iron calibration is reproducible using the proposed Monte Carlo model. Furthermore, this model can be readily extended to other important applications, including predicting signal behavior for MSE imaging.

Liver iron concentration (LIC) measured by MRI has become the clinical reference standard for managing iron overload in chronically transfused patients. Transverse relaxivity (R₂ or R₂ ^* ) measurements are converted to LIC units using empirically derived calibration curves.

That flip angle (FA) error due to B₁ ⁺ spatial heterogeneity causes significant LIC quantitation error. B₁ ⁺ scale (b₁ , [FA_actual /FA_specified ]) variation is a major problem at 3 T which could reduce the accuracy of transverse relaxivity measurements.

Prospective.

Forty-seven subjects with chronic transfusional iron overload undergoing clinically indicated LIC assessment.

5 T/3 T dual-repetition time B₁ ⁺ mapping sequence ASSESSMENT: We quantified the average/standard deviation b₁ in the right and left lobes of the liver from B₁ ⁺ maps acquired at 1.5 T and 3 T. The impact of b₁ variation on spin echo LIC estimates was determined using a Monte Carlo model.

Mean, median, and standard deviation in whole liver and right and left lobes; two-sided t-test between whole-liver b₁ means.

Average b₁ within the liver was 99.3% ± 12.3% at 1.5 T versus 69.6% ± 14.6% at 3 T and was independent of iron burden (P < 0.05). Monte Carlo simulations demonstrated that b₁ systematically increased R₂ estimates at lower LIC (<~25 mg/g at 1.5 T, <~15 mg/g at 3 T) but flattened or even inverted the R₂ -LIC relationship at higher LIC (≥~25 mg/g to 1.5 T, ≥~15 mg/g to 3 T); changes in the R₂ -LIC relationship were symmetric with respect to over and under excitation and were similar at 1.5 T and 3 T (for the same R₂ value). The R₂ ^* -LIC relationship was independent of b₁ .

Spin echo R₂ measurement of LIC at 3 T is error-prone without correction for b₁ errors. The impact of b₁ error on current 1.5 T spin echo-based techniques for LIC quantification is large enough to introduce measurable intersubject variability but the in vivo effect size needs a dedicated validation study.

1.

2.

CPMG spin echo acquisitions are attractive for diagnosing and monitoring liver iron concentration in iron overload disorders due to their time efficiency and potential to reveal unique information about tissue iron distribution. Clinical adoption remains low due to the insensitivity of CPMG-based R 2 estimates to liver iron concentration (LIC) when common fitting techniques are applied. In this work, we demonstrate that the inclusion of a proton density estimator (PDE) derived from the CPMG acquisition increase the sensitivity of CPMG R 2 estimates to LIC in both simulated and in-vivo human data.

CPMG R 2 acquisitions from 50 clinically indicated MRI studies in patients with iron overload were analyzed with and without PDE constraints. Liver regions of interest were fit to monoexpontial and nonexponential signal decay equations. LIC by R 2 ∗ served as the reference standard. The observed calibration between CPMG R 2 values and LIC were compared to results predicted from a previously validated Monte Carlo model.

The sensitivity of CPMG-derived R 2 triples when a proton density constraint is applied. When compared with R 2 ∗ -LIC estimates, both monoexponential and nonexponential models were unbiased but demonstrated broad 95% confidence intervals particularly for LIC values below 12 mg/g. Absolute error did not increase with LIC.

A proton density constraint can increase the sensitivity of CPMG-based models to iron. CPMG acquisitions are time-efficient and could potentially improve the dynamic range of single spin echo techniques as well as providing insight into tissue iron distribution.

Non-heme iron is an important element supporting the structure and functioning of biological tissues. Imbalance in non-heme iron can lead to different neurological disorders. Several MRI approaches have been developed for iron quantification relying either on the relaxation properties of MRI signal or measuring tissue magnetic susceptibility. Specific quantification of the non-heme iron can, however, be constrained by the presence of the heme iron in the deoxygenated blood and contribution of cellular composition. The goal of this paper is to introduce theoretical background and experimental MRI method allowing disentangling contributions of heme and non-heme irons simultaneously with evaluation of tissue neuronal density in the iron-rich basal ganglia. Our approach is based on the quantitative Gradient Recalled Echo (qGRE) MRI technique that allows separation of the total R2* metric characterizing decay of GRE signal into tissue-specific (R2t*) and the baseline blood oxygen level-dependent (BOLD) contributions. A combination with the QSM data (also available from the qGRE signal phase) allowed further separation of the tissue-specific R2t* metric in a cell-specific and non-heme-iron-specific contributions. It is shown that the non-heme iron contribution to R2t* relaxation can be described with the previously developed Gaussian Phase Approximation (GPA) approach. qGRE data were obtained from 22 healthy control participants (ages 26-63 years). Results suggest that the ferritin complexes are aggregated in clusters with an average radius about 100nm comprising approximately 2600 individual ferritin units. It is also demonstrated that the concentrations of heme and non-heme iron tend to increase with age. The strongest age effect was seen in the pallidum region, where the highest age-related non-heme iron accumulation was observed.

The role of hepatic iron overload (HIO) in nonalcoholic fatty liver disease (NAFLD) pathogenesis has not been fully elucidated.

This study aimed to investigate the effect of HIO and examine the diagnostic usefulness of magnetic resonance imaging (MRI)-based R2^* quantification in evaluating hepatic iron content (HIC) and pathological findings in NAFLD.

Prospective and retrospective.

A prospective study of 168 patients (age, 57.2 ± 15.0; male/female, 80/88) and a retrospective validation study of 202 patients (age, 57.0 ± 14.4; male/female, 113/89) with liver-biopsy-confirmed NAFLD were performed.

3 T; chemical-shift encoded multi-echo gradient echo.

Using liver tissues obtained by liver biopsy, HIC was prospectively evaluated in 168 patients by atomic absorption spectrometry. Diagnostic accuracies of HIC and R2^* for grading hepatic inflammation plus ballooning (HIB) as an indicator of NAFLD activity were assessed.

Student's t-test and analysis of variance (ANOVA) with Scheffe's multiple testing correction for univariate comparisons; multivariate logistic analysis. P-value less than 0.05 is statistically significant.

HIC was significantly correlated with HIB grades (r = 0.407). R2^* was significantly correlated with HIC (r = 0.557) and HIB grades (r = 0.569). R2^* mapped an area under the receiver operating characteristic (AUROC; 0.774) for HIC ≥808 ng/mL (median value) with cutoff value of 62.5 s^-1 . In addition, R2^* mapped AUROC of HIB for grades ≥3 was 0.799 with cutoff value of 58.5 s^-1 . When R2^* was <62.5 s^-1 , R2^* correlated weakly with HIC (r = 0.372) as it was affected by fat deposition and did not correlate with HIB grades (P = 0.052). Conversely, when R2^* was ≥62.5 s^-1 , a significant correlation of R2^* with HIC (r = 0.556) and with HIB grades was observed (P < 0.0001) with being less affected by fat deposition.

R2^*  ≥ 62.5 s^-1 is a promising modality for non-invasive diagnosis of clinically important high grades (≥3) of HIB associated with increased HIC.

1 TECHNICAL EFFICACY STAGE: 2.

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

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

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

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

To describe and validate a simultaneous proton density fat-fraction (PDFF) imaging and water-specific T₁ mapping (T_1(Water) ) approach for the liver (PROFIT₁ ) with R 2 ∗ mapping and low sensitivity to B 1 + calibration or inhomogeneity.

A multiecho gradient-echo sequence, with and without saturation preparation, was designed for simultaneous imaging of liver PDFF, R 2 ∗ , and T_1(Water) (three slices in ~13 seconds). Chemical-shift-encoded MRI processing yielded fat-water separated images and R 2 ∗ maps. T_1(Water)  calculation utilized saturation and nonsaturation-recovery water-separated images. Several variable flip angle schemes across k-space (increasing flip angles in sequential RF pulses) were evaluated for minimization of T₁ weighting, to reduce the B 1 + dependence of T_1(Water)  and PDFF (reduced flip angle dependence). T_1(Water)  accuracy was validated in mixed fat-water phantoms, with various PDFF and T₁ values (3T). In vivo application was illustrated in five volunteers and five patients with nonalcoholic fatty liver disease (PDFF, T_1(Water) , R 2 ∗ ).

A sin³ (θ) flip angle pattern (0 < θ < π/2 over k-space) yielded the largest PROFIT₁ signal yield with negligible B 1 + dependence for both T_1(Water) and PDFF. Mixed fat-water phantom experiments illustrated excellent agreement between PROFIT₁ and gold-standard spectroscopic evaluation of PDFF and T_1(Water)  (<1% T₁ error). In vivo PDFF, T_1(Water) , and R 2 ∗ maps illustrated independence of the PROFIT₁ values from B 1 + inhomogeneity and significant differences between volunteers and patients with nonalcoholic fatty liver disease for T_1(Water) (927 ± 56 ms vs. 1033 ± 23 ms; P < .05) and PDFF (2.0% ± 0.8% vs. 13.4% ± 5.0%, P < .05).  R 2 ∗ was similar between groups.

The PROFIT₁ pulse sequence provides fast simultaneous quantification of PDFF, T_1(Water) , and R 2 ∗ with minimal sensitivity to B 1 + miscalibration or inhomogeneity.

To assess clinically relevant difference in hepatic iron quantification using R2* relaxometry with (FS) and without (non-FS) fat saturation for the evaluation of patients with suspected hepatic iron overload.

We prospectively enrolled 134 patients who underwent 1.5-T MRI R2* relaxometry with FS and non-FS gradient echo sequences (12 echoes, initial TE = 0.99 ms). Proton density fat fraction for the quantification of steatosis was assessed. Linear regression analyses and Bland-Altman plots including Lin's concordance correlation coefficient were performed for correlation of FS R2* with non-FS R2*. Patients were grouped into 4 severity classes of iron overload (EASL based), and agreement was evaluated by contingency tables and the proportion of overall agreement.

A total of 41.8% of patients showed hepatic iron overload; 67.9% had concomitant steatosis; and 58.2% revealed no iron overload of whom 60.3% had steatosis. The mean R2* value for all FS data was 102.86 1/s, for non-FS 108.16 1/s. Linear regression resulted in an R-squared value of 0.99 (p < 0.001); Bland-Altman plot showed a mean R2* difference of 5.26 1/s (SD 17.82). The concordance correlation coefficient was only slightly lower for patients with steatosis compared with non-steatosis (0.988 vs. 0.993). The overall agreement between FS and non-FS R2* measurements was 94.8% using either method to classify patients according to severity of iron storage. No correlation between R2* and proton density fat fraction was found for both methods.

R2* relaxometry showed an excellent overall agreement between FS and non-FS acquisition. Both variants can therefore be used in daily routine. However, clinically relevant differences might result when switching between the two methods or during patient follow-up, when fat content changes over time. We therefore recommend choosing a method and keeping it straight in the context of follow-up examinations.

• Both variants of R2* relaxometry (FS and non-FS) may be used in daily routine. • Clinically relevant differences might result when switching between the two methods or during patient follow-up, when fat content changes over time. • It seems advisable choosing one method and keeping it straight in the context of follow-up examinations.

Intramyocardial hemorrhage is an independent predictor of adverse outcomes in ST-segment elevation myocardial infarction (STEMI). Iron deposition resulting from ischemia-reperfusion injury (I/R) is pro-inflammatory and has been associated with adverse remodeling. The role of iron chelation in hemorrhagic acute myocardial infarction (AMI) has never been explored. The purpose of this study was to investigate the cardioprotection offered by the iron-chelating agent deferiprone (DFP) in a porcine AMI model by evaluating hemorrhage neutralization and subsequent cardiac remodeling. Two groups of animals underwent a reperfused AMI procedure: control and DFP treated (N = 7 each). A comprehensive MRI examination was performed in healthy state and up to week 4 post-AMI, followed by histological assessment. Infarct size was not significantly different between the two groups; however, the DFP group demonstrated earlier resolution of hemorrhage (by T2* imaging) and edema (by T2 imaging). Additionally, ventricular enlargement and myocardial hypertrophy (wall thickness and mass) were significantly smaller with DFP, suggesting reduced adverse remodeling, compared to control. The histologic results were consistent with the MRI findings. To date, there is no effective targeted therapy for reperfusion hemorrhage. Our proof-of-concept study is the first to identify hemorrhage-derived iron as a therapeutic target in I/R and exploit the cardioprotective properties of an iron-chelating drug candidate in the setting of AMI. Iron chelation could potentially serve as an adjunctive therapy in hemorrhagic AMI.

We report a case of undifferentiated carcinoma of the pancreas with osteoclast-like giant cells ocalized within the main pancreatic duct (MPD). A 61-year-old woman was referred to our hospital for evaluation of dilatation of the MPD that was detected on screening sonogram. Preoperative MR imaging revealed a small hypervascular tumor within the dilated MPD, showing high signal on R2* map and signal reduction on in-phase as compared to out-of-phase. R2* hyperintensity and in-phase signal reduction may be a characteristic feature of undifferentiated carcinoma of the pancreas with osteoclast-like giant cells, which indicates intratumoral hemorrhage even if they are small.

Patients with chronic haemolytic anaemia, such as in thalassaemia, require repeated blood transfusions, which leads to iron overload and cellular damage, especially in the heart and liver. Classically, serum ferritin and liver biopsy have been used to monitor patient response to chelation therapy. Magnetic resonance imaging (MRI) has proven to be effective in detecting and quantifying iron in the heart and liver. The aim of the paper is to evaluate the accuracy of the MRI T2* procedure in the assessment of liver iron concentration and myocardial iron overload.

In 210 cases of monthly transfused patients, hepatic and myocardial iron overload was measured by multi-breath-hold MRI T2* and compared to serum ferritin (a traditional marker of iron overload).

No significant correlation was observed between serum ferritin level and cardiac T2* MRI (p = 0.68, r = 0.06). However, a significant correlation was observed between serum ferritin and liver iron concentration evaluated by MRI (p = 0.04, r = 0.68).

Routine evaluation of liver and heart iron content using MRI T2* is suggested to better evaluate the haemosiderosis status in thalassaemic patients.

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

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

Retrospective.

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

1.5T, T₂ *-weighted gradient echo sequence.

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

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

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

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

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

Modified Look-Locker inversion recovery (MOLLI) T1 mapping sequences can be useful in cardiac and liver tissue characterization, but determining underlying water T1 is confounded by iron, fat and frequency offsets. This article proposes an algorithm that provides an independent water MOLLI T1 (referred to as on-resonance water T1 ) that would have been measured if a subject had no fat and normal iron, and imaging had been done on resonance. Fifteen NiCl2 -doped agar phantoms with different peanut oil concentrations and 30 adults with various liver diseases, nineteen (63.3%) with liver steatosis, were scanned at 3 T using the shortened MOLLI (shMOLLI) T1 mapping, multiple-echo spoiled gradient-recalled echo and 1 H MR spectroscopy sequences. An algorithm based on Bloch equations was built in MATLAB, and water shMOLLI T1 values of both phantoms and human participants were determined. The quality of the algorithm's result was assessed by Pearson's correlation coefficient between shMOLLI T1 values and spectroscopically determined T1 values of the water, and by linear regression analysis. Correlation between shMOLLI and spectroscopy-based T1 values increased, from r = 0.910 (P < 0.001) to r = 0.998 (P < 0.001) in phantoms and from r = 0.493 (for iron-only correction; P = 0.005) to r = 0.771 (for iron, fat and off-resonance correction; P < 0.001) in patients. Linear regression analysis revealed that the determined water shMOLLI T1 values in patients were independent of fat and iron. It can be concluded that determination of on-resonance water (sh)MOLLI T1 independent of fat, iron and macroscopic field inhomogeneities was possible in phantoms and human subjects.

Magneto-endosymbionts (MEs) show promise as living magnetic resonance imaging (MRI) contrast agents for in vivo cell tracking. Here we characterize the biomedical imaging properties of ME contrast agents, in vitro and in vivo.

By adapting and engineering magnetotactic bacteria to the intracellular niche, we are creating magneto-endosymbionts (MEs) that offer advantages relative to passive iron-based contrast agents (superparamagnetic iron oxides, SPIOs) for cell tracking. This work presents a biomedical imaging characterization of MEs including: MRI transverse relaxivity (r ₂) for MEs and ME-labeled cells (compared to a commercially available iron oxide nanoparticle); microscopic validation of labeling efficiency and subcellular locations; and in vivo imaging of a MDA-MB-231BR (231BR) human breast cancer cells in a mouse brain.

At 7T, r ₂ relaxivity of bare MEs was higher (250 s^-1 mM^-1) than that of conventional SPIO (178 s^-1 mM^-1). Optimized in vitro loading of MEs into 231BR cells yielded 1-4 pg iron/cell (compared to 5-10 pg iron/cell for conventional SPIO). r ₂ relaxivity dropped by a factor of ~3 upon loading into cells, and was on the same order of magnitude for ME-loaded cells compared to SPIO-loaded cells. In vivo, ME-labeled cells exhibited strong MR contrast, allowing as few as 100 cells to be detected in mice using an optimized 3D SPGR gradient-echo sequence.

Our results demonstrate the potential of magneto-endosymbionts as living MR contrast agents. They have r ₂ relaxivity values comparable to traditional iron oxide nanoparticle contrast agents, and provide strong MR contrast when loaded into cells and implanted in tissue.

To develop multiparameter mapping including T₁ , R2*, and proton density fat fraction with a single breath-hold to evaluate liver disease and liver function.

A 6-echo spoiled gradient-echo sequence with dual flip angles was used to acquire a 12-set MRI volume data set. To shorten the scan time, undersampling and multicontrast compressed-sensing reconstruction were used. The scan time was 18 seconds. R2* and proton density fat fraction mapping were achieved by using the iterative least-squares method. T₁ mapping was estimated using driven equilibrium single-pulse observation of T₁ . Quantitative values were validated by performing phantom and volunteer studies.

Statistical analysis showed that the quantitative values measured using the proposed methods agreed with those measured using conventional methods. T₁ values of water proton measured by the proposed method in phantom and volunteer studies were in good agreement with those by MRS.

The results showed that accurate quantitative mapping of T₁ , R2*, and proton density fat fraction with a single breath-hold was achieved using our approach.

Liver iron accumulates in various chronic liver diseases where it is an independent factor for survival and carcinogenesis. We tested a novel room-temperature susceptometer (RTS) to non-invasively assess liver iron concentration (LIC).

Two hundred and sixty-four patients with or without signs of iron overload or liver disease were prospectively enrolled. Thirty-five patients underwent liver biopsy with semiquantitative iron determination (Prussian Blue staining), atomic absorption spectroscopy (AAS, n=33), or magnetic resonance imaging (MRI, n=15).

In vitro studies demonstrated a highly linear (r²=0.998) association between RTS-signal and iron concentration, with a detection limit of 0.3mM. Using an optimized algorithm, accounting for the skin-to-liver capsule distance, valid measurements could be obtained in 84% of cases. LIC-RTS showed a significant correlation with LIC-AAS (r=0.74, p<0.001), LIC-MRI (r=0.64, p<0.001) and hepatocellular iron (r=0.58, p<0.01), but not with macrophage iron (r=0.32, p=0.30). Normal LIC-RTS was 1.4mg/g dry weight. Besides hereditary and transfusional iron overload, LIC-RTS was also significantly elevated in patients with alcoholic liver disease. The areas under the receiver operating characteristic curve (AUROC) for grade 1, 2 and 3 hepatocellular iron overload were 0.72, 0.89 and 0.97, respectively, with cut-off values of 2.0, 4.0 and 5.0mg/g dry weight. Notably, the positive and negative predictive values, sensitivity, specificity and accuracy of severe hepatic iron overload (HIO) (grade ≥2) detection, were equal to AAS and superior to all serum iron markers. Depletion of hepatic iron could be efficiently monitored upon phlebotomy.

RTS allows for the rapid and non-invasive measurement of LIC. In comparison to MRI, it could be a cost-effective bedside method for LIC screening. Lay summary: Novel room-temperature susceptometer (RTS) allows for the rapid, sensitive, and non-invasive measurement of liver iron concentration. In comparison to MRI, it could be a cost-effective bedside method for liver iron concentration screening.

Patients with thalassemia become iron overloaded from increased absorption of iron, ineffective erythropoiesis, and chronic transfusion. Before effective iron chelation became available, thalassemia major patients died of iron-related cardiac failure in the second decade of life. Initial treatment goals for chelation therapy were aimed at levels of ferritin and liver iron concentrations associated with prevention of adverse cardiac outcomes and avoidance of chelator toxicity. Cardiac deaths were greatly reduced and survival was much longer. Epidemiological data from the general population draw clear associations between increased transferrin saturation (and, by inference, labile iron) and early death, diabetes, and malignant transformation. The rate of cancers now seems to be significantly higher in thalassemia than in the general population. Reduction in iron can reverse many of these complications and reduce the risk of malignancy. As toxicity can result from prolonged exposure to even low levels of excess iron, and survival in thalassemia patients is now many decades, it would seem prudent to refocus attention on prevention of long-term complications of iron overload and to maintain labile iron and total body iron levels within a normal range, if expertise and resources are available to avoid complications of overtreatment.

To evaluate the performance and limitations of the signal intensity ratio method for quantifying liver iron overload at 3 T.

Institutional review board approval and written informed consent from all participants were obtained. One hundred and five patients were included prospectively. All patients underwent a liver biopsy with biochemical assessment of hepatic iron concentration and a 3 T MRI scan with 5 breath-hold single-echo gradient-echo sequences. Linear correlation between liver-to-muscle signal intensity ratio and liver iron concentration was calculated. The algorithm for calculating magnetic resonance hepatic iron concentration was adapted from the method described by Gandon et al. with echo times divided by 2. Sensitivity and specificity were calculated.

Five patients were excluded (coil selection failure or missing sequence) and 100 patients were analyzed, 64 men and 36 women, 52 ± 13.3 years old, with a biochemical hepatic iron concentration range of 0-630 µmol/g. Linear correlation between biochemical hepatic iron concentration and MR-hepatic iron concentration was excellent with a correlation coefficient = 0.96, p < 0.0001. Sensitivity and specificity were, respectively, 83% (0.70-0.92) and 96% (0.85-0.99), with a pathological threshold of 36 µmol/g.

Signal intensity ratio method for quantifying liver iron overload can be used at 3 T with echo times divided by 2.

Magnetic resonance imaging (MRI) is a well-established imaging modality to evaluate increased iron deposition in the liver. Both standard liver imaging series with in-phase and out-of-phase T1-weighted sequences for visual detection, as well as advanced T2- and T2*-weighted measurements may be used for mapping the iron concentration. In this article, we describe different forms of liver iron accumulation (diffuse, heterogeneous, multinodular, focal, segmental, intralesional, periportal, and lobar) and hepatic iron sparing (focal, geographic and nodular). Focal iron sparing is characterized by hypointense areas on R2* map and hyperintense areas on T2* map. We also illustrate MRI findings of simultaneous hepatic iron and fat accumulation. Coexistence of iron (siderosis) and fat (steatosis) can make interpretation of in- and out-of-phase T1-weighted images difficult; calculation of proton density fat fraction and R2* maps can characterize abnormal signal changes observed on in- and out-of-phase images. Knowledge of different forms of hepatic iron overload and iron sparing and evaluation of T2* and R2* maps would allow correct diagnosis of iron-associated liver disorders.

Age-related declines in spatial navigation are associated with deficits in procedural and episodic memory and deterioration of their neural substrates. For the lack of longitudinal evidence, the pace and magnitude of these declines and their neural mediators remain unclear. Here we examined virtual navigation in healthy adults (N=213, age 18-77 years) tested twice, two years apart, with complementary indices of navigation performance (path length and complexity) measured over six learning trials at each occasion. Slopes of skill acquisition curves and longitudinal change therein were estimated in structural equation modeling, together with change in regional brain volumes and iron content (R2* relaxometry). Although performance on the first trial did not differ between occasions separated by two years, the slope of path length improvement over trials was shallower and end-of-session performance worse at follow-up. Advanced age, higher pulse pressure, smaller cerebellar and caudate volumes, and greater caudate iron content were associated with longer search paths, i.e. poorer navigation performance. In contrast, path complexity diminished faster over trials at follow-up, albeit less so in older adults. Improvement in path complexity after two years was predicted by lower baseline hippocampal iron content and larger parahippocampal volume. Thus, navigation path length behaves as an index of perceptual-motor skill that is vulnerable to age-related decline, whereas path complexity may reflect cognitive mapping in episodic memory that improves with repeated testing, although not enough to overcome age-related deficits.

To propose a simple multicompartment model of the liver and use Bloch-McConnell simulations to demonstrate the effects of iron and fibrosis on shortened-MOLLI (shMOLLI) T₁ measurements. Liver T₁ values have shown sensitivity to inflammation and fibrosis, but are also affected by hepatic iron content. Modified Look-Locker inversion recovery (MOLLI) T₁ measurements are biased by the lower T₂ associated with high iron.

A tissue model was generated consisting of liver cells and extracellular fluid (ECF), with iron-dependent relaxation rates. Fibrosis was imitated by increasing the ECF proportion. Simulations of the shMOLLI sequence produced a look-up table (LUT) of shMOLLI-T₁ for a given ECF fraction and iron content. The LUT was used to calculate ECF(shMOLLI-T₁ ), assuming normal hepatic iron content (HIC), and ECF(shMOLLI- T1,T2*), accounting for HIC determined by T2*, for 77 patients and compared to fibrosis assessed by liver biopsy.

Simulations showed that increasing HIC decreases shMOLLI-T₁ , with an increase in HIC from 1.0 to 2.5 mg/g at normal ECF fraction decreasing shMOLLI-T₁ by 160 msec, while increasing ECF increased ShMOLLI-T₁ , with an increase of 20% ECF at normal iron increasing shMOLLI-T₁ by 200 msec. Calculated patient ECF(shMOLLI-T₁ ) showed a strong dependence on Ishak score (3.3 ± 0.8 %ECF/Ishak stage) and 1/T2* (-0.23 ± 0.04 %ECF/Hz). However, when iron was accounted for to produce ECF(shMOLLI- T1,T2*), it was independent of HIC but retained sensitivity to Ishak score.

Use of this multicompartment model of the liver with Bloch-McConnell simulation should enable compensation of iron effects when using shMOLLI-T₁ to assess fibrosis.

1 J. Magn. Reson. Imaging 2017;45:450-462.

This work describes a phantom containing regions of controlled R2* (1/T2*) values to provide a stable reference object for testing implementations of R2* relaxometry commonly used for liver and heart iron assessments.

A carrageenan-strengthened gadolinium DTPA doped agarose gel was used to enclose nine gels additionally doped with ultra-small superparamagnetic iron oxide. R2* values were determined at 1.5 T using multi-echo GRE sequences and exponential regression of pixel values from a region of interest against echo time using non-linear regression algorithms. We measured R2*, R2 and R1 values and the inter-scan and inter-operator reproducibility.

The phantom reliably demonstrated R2* values in seven steps between 22.4 s^-1 (SE 1.98) and 441.9 s^-1 (SE 6.76), with an R2* relaxivity (r2*) of 792 (SE 5.6) mM^-1 s^-1. The doped gels displayed a concentration-dependent R2' component of R2* phantom, indicating superparamagnetic enhancement effects. We observed no significant change in relaxivity (r2*) over 12 months, and estimate a useful life of 3 years. Detailed descriptions of the production process and calculators are been provided as Online Resources.

The phantom provides a durable test object with controlled R2* relaxation behaviour, useful for a range of R2* relaxometry reference work.

A model of dysmyelination, the Long Evans Shaker (les) rat, was used to study the contribution of myelin to MR tissue properties in white matter. A large region of white matter was identified in the deep cerebellum and was used for measurements of the MR relaxation rate constants, R1  = 1/T1 and R2  = 1/T2 , at 7 T. In this study, R1 of the les deep cerebellar white matter was found to be 0.55 ± 0.08 s (-1) and R2 was found to be 15 ± 1 s(-1) , revealing significantly lower R1 and R2 in les white matter relative to wild-type (wt: R1  = 0.69 ± 0.05 s(-1) and R2  = 18 ± 1 s(-1) ). These deviated from the expected ΔR1 and ΔR2 values, given a complete lack of myelin in the les white matter, derived from the literature using values of myelin relaxivity, and we suspect that metals could play a significant role. The absolute concentrations of the paramagnetic transition metals iron (Fe) and manganese (Mn) were measured by a micro-synchrotron radiation X-ray fluorescence (μSRXRF) technique, with significantly greater Fe and Mn in les white matter than in wt (in units of μg [metal]/g [wet weight tissue]: les: Fe concentration,19 ± 1; Mn concentration, 0.71 ± 0.04; wt: Fe concentration,10 ± 1; Mn concentration, 0.47 ± 0.04). These changes in Fe and Mn could explain the deviations in R1 and R2 from the expected values in white matter. Although it was found that the influence of myelin still dominates R1 and R2 in wt rats, there were non-negligible changes in the contribution of the metals to relaxation. Although there are already problems with the estimation of myelin from R1 and R2 changes in disease models with pathology that also affects the relaxation rate constants, this study points to a specific pitfall in the estimation of changes in myelin in diseases or models with disrupted concentrations of paramagnetic transition metals. Copyright © 2016 John Wiley & Sons, Ltd.

Quantitative T2 (qT2), diffusion tensor imaging (DTI), and histology were used to investigate a cervical model of spinal cord injury (SCI) in the rat. While quantitative MRI can significantly increase the specificity in the presence of pathology, it must be validated for each type of injury or disease. In the case of traumatic SCI most models are difficult to image, either due to the location of the injury, or as a result of damage to surrounding tissues resulting from invasive surgical procedures. In this study a non-surgical cervical model of SCI, produced using a combination of focused ultrasound and microbubbles, was used to produce pathology similar to that seen in models of contusive and compressive injuries. qT2 and DTI were performed at 24 h and 1 and 2 weeks following injury, and compared with H&E and luxol fast blue histology. In the injured spinal cord, in addition to intra/extracellular (I/E) water and myelin water in white matter, qT2 revealed a large component with very short T2 of about 3 ms, which was highly correlated with the presence of hemorrhage in both gray and white matter at 24 h, and with the presence of hemosiderin in gray matter at 2 weeks following injury. The T2 of the I/E water peak was also elevated at 24 h in both gray and white matter, which was correlated with the presence of vacuolation/edema on histology. Cystic cavities were only seen at the 1 or 2 week timepoints, and were correlated with the presence of a water peak with T2  > 250 ms. No significant changes in diffusivity parameters were observed. Pathologies were often co-occurring, with opposite effects on the average T2 in a given voxel, reducing the visibility of injured tissue on standard T2 -weighted MR images.

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

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.

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).

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.

The accumulation of non-heme iron in the brain has been proposed as a harbinger of neural and cognitive decline in aging and neurodegenerative disease, but support for this proposal has been drawn from cross-sectional studies, which do not provide valid estimates of change. Here, we present longitudinal evidence of subcortical iron accumulation in healthy human adults (age 19-77 at baseline). We used R2* relaxometry to estimate regional iron content twice within a 2 year period, measured volumes of the striatum and the hippocampus by manual segmentation, and assessed cognitive performance by working memory tasks. Two-year change and individual differences in the change of regional volumes, regional iron content, and working memory were examined by latent change score models while taking into account the age at baseline and metabolic risk indicators. Over the examined period, volume reduction occurred in the caudate nucleus and hippocampus, but iron content increased only in the striatum, where it explained shrinkage. Higher iron content in the caudate nucleus at baseline predicted lesser improvement in working memory after repeat testing. Although advanced age and elevated metabolic syndrome risk were associated with greater iron content in the putamen at baseline, neither age nor metabolic risk influenced change in any variable. Thus, longitudinal evidence supports the notion that accumulation of subcortical iron is a risk factor for neural and cognitive decline in normal aging.

Exposure to elevated levels of iron causes tissue damage and organ failure, and increases the risk of cancer. The toxicity of iron is mediated through generation of oxidants. There is also solid evidence indicating that oxidant stress plays a significant role in a variety of human disease states, including malignant transformation. Iron toxicity is the main focus when managing thalassemia. However, the short- and long-term toxicities of iron have not been extensively considered in children and adults treated for malignancy, and only recently have begun to draw oncologists' attention. The treatment of malignancy can markedly increase exposure of patients to elevated toxic iron species without the need for excess iron input from transfusion. This under-recognized exposure likely enhances organ toxicity and may contribute to long-term development of secondary malignancy and organ failure. This review discusses the current understanding of iron metabolism, the mechanisms of production of toxic free iron species in humans, and the relation of the clinical marker, transferrin saturation (TS), to the presence of toxic free iron. We will present epidemiological data showing that high TS is associated with poor outcomes and development of cancer, and that lowering free iron may improve outcomes. Finally, we will discuss the possible relation between some late complications seen in survivors of cancer and those due to iron toxicity.

R2* (1/T2*) and single echo R2 (1/T2) have been calibrated to liver iron concentration (LIC) in patients with thalassemia and transfusion-dependent sickle cell disease at 1.5T. The R2*-LIC relationship is linear, whereas that of R2 is curvilinear. However, the increasing popularity of high-field scanners requires generalizing these relationships to higher field strengths. In this study, we tested the hypothesis that numerical simulation can accurately determine the field dependence of iron-mediated transverse relaxation rates.

We previously replicated the calibration curves between R2 and R2* and iron at 1.5T using Monte Carlo models incorporating realistic liver structure, iron deposit susceptibility, and proton mobility. In this paper, we extend our model to predict relaxivity-iron calibrations at higher field strengths. Predictions were validated by measuring R2 and R2* at 1.5T and 3T in six β-thalassemia major patients.

Predicted R2* increased twofold at 3T from 1.5T, whereas R2 increased by a factor of 1.47. Patient data exhibited a coefficient of variation of 3.6% and 7.2%, respectively, to the best-fit simulated data. Simulations over the range 0.25T-7T showed R2* increasing linearly with field strength, whereas R2 exhibited a concave-downward relationship.

A model-based approach predicts alterations in relaxivity-iron calibrations with field strength without repeating imaging studies. The model may generalize to alternative pulse sequences and tissue iron distribution.

Iron accumulation is observed in liver and spleen during hemochromatosis and important neurodegenerative diseases involve iron overload in brain. Storage of iron is ensured by ferritin, which contains a magnetic core. It causes a darkening on T2 -weighted MR images. This work aims at improving the understanding of the NMR relaxation of iron-loaded human tissues, which is necessary to develop protocols of iron content measurements by MRI. Relaxation times measurements on brain, liver and spleen samples were realized at different magnetic fields. Iron content was determined by atomic emission spectroscopy. For all samples, the longitudinal relaxation rate (1/T1 ) of tissue protons decreases with the magnetic field up to 1 T, independently of iron content, while their transverse relaxation rate (1/T2 ) strongly increases with the field, either linearly or quadratically, or a combination thereof. The extent of the inter-echo time dependence of 1/T2 also varies according to the sample. A combination of theoretical models is necessary to describe the relaxation of iron-containing tissues. This can be due to the presence, inside tissues, of ferritin clusters of different sizes and densities. When considering all samples, a correlation (r(2)  = 0.6) between 1/T1 and iron concentration is observed at 7.0 T. In contrast the correlation between 1/T2 and iron content is poor, even at high field (r(2)  = 0.14 at 7.0 T). Our results show that MRI methods based on T1 or T2 measurements will easily detect an iron overloading at high magnetic field, but will not provide an accurate quantification of tissue iron content at low iron concentrations.

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.

To determine whether systematic differences were present between myocardial R2* values obtained with two different decay models: truncation and exponential + constant (Exp-C).

Single-center cohorts were used to compare black and bright blood sequences separately, and a multicenter cohort of mixed bright and black blood studies was used to assess the generalizability. Truncated exponential estimates were calculated with CMRtools, which uses a single region of interest (ROI) method. Exp-C estimates were calculated using a pixelwise approach.

No differences could be distinguished based upon whether a white or black blood sequence was examined. The two fitting algorithms yielded similar R2* values, with R-squared values exceeding 0.997 and a coefficient of variation of 3% to 4%. Results using the pixelwise method yielded a small systematic bias (∼3%) that became apparent in patients with severe iron deposition. This disparity disappeared when Exp-C fitting was used on a single ROI, suggesting that the use of pixelwise mapping was responsible for the bias. In the multicenter cohort, the strong agreement between the two fitting approaches was reconfirmed.

Cardiac R2* values are independent of the signal model used for its calculation over clinically relevant ranges. Clinicians can compare results among centers using these disparate approaches with confidence.