R2 and R2* are equally effective in evaluating chronic response to iron chelation

Revisiting iron overload status and change thresholds as predictors of mortality in transfusion-dependent β-thalassemia: a 10-year cohort study

Data on iron overload status and change thresholds that can predict mortality in patients with transfusion-dependent β-thalassemia (TDT) are limited. This was a retrospective cohort study of 912 TDT patients followed for up to 10 years at treatment centers in Italy (median age 32 years, 51.6% female). The crude mortality rate was 2.9%. Following best-predictive threshold identification through receiver operating characteristic curve analyses, data from multivariate Cox-regression models showed that patients with Period Average Serum Ferritin (SF) > 2145 vs ≤ 2145 ng/mL were 7.1-fold (P < 0.001) or with Absolute Change SF > 1330 vs ≤ 1330 ng/mL increase were 21.5-fold (P < 0.001) more likely to die from any cause. Patients with Period Average Liver Iron Concentration (LIC) > 8 vs ≤ 8 mg/g were 20.2-fold (P < 0.001) or with Absolute Change LIC > 1.4 vs ≤ 1.4 mg/g increase were 27.6-fold (P < 0.001) more likely to die from any cause. Patients with Index (first) cardiac T2* (cT2*) < 27 vs ≥ 27 ms were 8.6-fold (P < 0.001) more likely to die from any cause. Similarly, results at varying thresholds were identified for death from cardiovascular disease. These findings should support decisions on iron chelation therapy by establishing treatment targets, including safe iron levels and clinically meaningful changes over time.

Quantification of Liver Iron Overload with MRI: Review and Guidelines from the ESGAR and SAR

Accumulation of excess iron in the body, or systemic iron overload, results from a variety of causes. The concentration of iron in the liver is linearly related to the total body iron stores and, for this reason, quantification of liver iron concentration (LIC) is widely regarded as the best surrogate to assess total body iron. Historically assessed using biopsy, there is a clear need for noninvasive quantitative imaging biomarkers of LIC. MRI is highly sensitive to the presence of tissue iron and has been increasingly adopted as a noninvasive alternative to biopsy for detection, severity grading, and treatment monitoring in patients with known or suspected iron overload. Multiple MRI strategies have been developed in the past 2 decades, based on both gradient-echo and spin-echo imaging, including signal intensity ratio and relaxometry strategies. However, there is a general lack of consensus regarding the appropriate use of these methods. The overall goal of this article is to summarize the current state of the art in the clinical use of MRI to quantify liver iron content and to assess the overall level of evidence of these various methods. Based on this summary, expert consensus panel recommendations on best practices for MRI-based quantification of liver iron are provided.

Thalassaemia

Thalassaemia is a diverse group of genetic disorders with a worldwide distribution affecting globin chain synthesis. The pathogenesis of thalassaemia lies in the unbalanced globin chain production, leading to ineffective erythropoiesis, increased haemolysis, and deranged iron homoeostasis. The clinical phenotype shows heterogeneity, ranging from close to normal without complications to severe requiring lifelong transfusion support. Conservative treatment with transfusion and iron chelation has transformed the natural history of thalassaemia major into a chronic disease with a prolonged life expectancy, albeit with co-morbidities and substantial disease burden. Curative therapy with allogeneic haematopoietic stem cell transplantation is advocated for suitable patients. The understanding of the pathogenesis of the disease is guiding therapeutic advances. Novel agents have shown efficacy in improving anaemia and transfusion burden, and initial results from gene therapy approaches are promising. Despite scientific developments, worldwide inequality in the access of health resources is a major concern, because most patients live in underserved areas.

Effects of B1 + Heterogeneity on Spin Echo-Based Liver Iron Estimates

BACKGROUND

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.

HYPOTHESIS

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.

STUDY TYPE

Prospective.

POPULATION

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

FIELD STRENGTH/SEQUENCE

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.

STATISTICAL TESTS

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

RESULTS

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 .

CONCLUSION

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.

LEVEL OF EVIDENCE

1.

TECHNICAL EFFICACY STAGE

2.

Improving CPMG liver iron estimates with a T 1 -corrected proton density estimator

PURPOSE

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.

THEORY AND METHODS

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.

RESULTS

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.

CONCLUSION

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.

R2 and R2* MRI assessment of liver iron content in an undifferentiated diagnostic population with hyperferritinaemia, and impact on clinical decision making

PURPOSE

To confirm the linear correlation between Ferriscan® R2 (1/T2 Relaxomatry) and R2* (1/T2* Relaxometry) derived 3D Gradient echo (GRE) mDIXON-Quant sequence (Philips) with simultaneous production of a proton density fat fraction (PDFF) in undifferentiated patients with hyperferritinaemia, and to prospectively determine the clinical utility of this tool in these patients by recording the impact on clinical decision-making.

MATERIALS AND METHODS

Participants referred to a hospital haematology outpatient clinic for investigation and management of elevated serum ferritin (two serum ferritin levels > 500 μg/L 4 weeks apart) were included in the study.

EXCLUSION CRITERIA

contraindications to MRI; clinically relevant investigations for alternative causes of hyperferritinaemia pending; and terminal illness. Thirty-two participants were recruited: 27 men, 5 women. All MRIs performed at 1.5 T. For R2* quantification, 3D six echo GRE sequence (mDIXON-Quant) was acquired. R2 images were acquired over 20 min as dictated and reported by the licensee (Ferriscan®). Clinician interpretation and patient management based on R2* and liver iron content derived from R2 (LIC_R2) was recorded. Pearson's correlations, linear regression analyses, and ROC curves were calculated. P value <0.05 was considered significant.

RESULTS

A high degree of correlation between mean R2* and LIC_R2 was observed in this novel patient population (slope ± SE of 43.35 ± 1.88 s^-1 permg/g; 95 % CI 39.5-47.2; P < 0.001; R² = 0.87). Clinical decision making was amended in 14/32 (44 %) patients with hyperferritinaemia following the disclosure of R2* results to clinicians, compared with serum ferritin alone. Liver biopsy was avoided in one patient based on LIC_R2 and R2*. Unrecognised hepatic steatosis was diagnosed in one patient from the PDFF map.

CONCLUSION

We have confirmed the linear correlation between R2 and R2* in a real-world diagnostic population with hyperferritinaemia. Non-invasive assessment of liver iron content (LIC) by R2 and R2* MRI is a useful clinical tool and alters management in these patients.

MR imaging assessment and quantification of liver iron

Iron overload is a common clinical problem resulting from hereditary hemochromatosis or secondary hemosiderosis (mainly associated with transfusion therapy), being also associated with chronic liver diseases and metabolic disorders. Excess of iron accumulates in organs like the liver, pancreas and heart. Without treatment, patients with iron overload disorders will develop liver cirrhosis, diabetes and cardiomyopathy. Iron quantification is therefore crucial not only for diagnosis of iron overload but also to monitor iron-reducing therapies. Liver iron concentration is considered the surrogate marker of total body iron stores. Because liver biopsy is invasive and prone to high variability and sampling bias, MR imaging has emerged as a non-invasive method and gained wide acceptance, now being considered the standard of care for assessing iron overload. Nevertheless, there are different MR techniques for iron quantification and there is still no consensus about the best technique or postprocessing tool for hepatic iron quantification, with the choice of imaging technique depending mainly on the local expertise as well on the available equipment and software. Because different methods should not be used interchangeably, it is important to choose one method and use the same one when following up patients over time.

Performance of different Dixon-based methods for MR liver iron assessment in comparison to a biopsy-validated R2* relaxometry method

Objectives

To prospectively evaluate a 3D-multiecho-Dixon sequence with inline calculation of proton density fat fraction (PDFF) and R2* (qDixon), and an improved version of it (qDixon-WIP), for the MR-quantification of hepatic iron in a clinical setting.

Methods

Patients with increased serum ferritin underwent 1.5-T MRI of the liver for the evaluation of hepatic iron overload. The imaging protocol for R2* quantification included as follows: (1) a validated, 2D multigradient-echo sequence (initial TE 0.99 ms, R2*-ME-GRE), (2) a 3D-multiecho-Dixon sequence with inline calculation of PDFF and R2* (initial TE 2.38 ms, R2*-qDixon), and optionally (3) a prototype (works-in-progress, WIP) version of the latter (initial TE 1.04 ms, R2*-qDixon-WIP) with improved water/fat separation and noise-corrected parameter fitting. For all sequences, three manually co-registered regions of interest (ROIs) were placed in the liver. R2* values were compared and linear regression analysis and Bland-Altman plots calculated.

Results

Forty-six out of 415 patients showed fat-water (F/W) swap with qDixon and were excluded. A total of 369 patients (mean age 52 years) were included; in 203/369, the optional qDixon-WIP was acquired, which showed no F/W swaps. A strong correlation was found between R2*-ME-GRE and R2*-qDixon (r² = 0.92, p < 0.001) with Bland-Altman revealing a mean difference of − 3.82 1/s (SD = 21.26 1/s). Correlation between R2*-GRE-ME and R2*-qDixon-WIP was r² = 0.95 (p < 0.001) with Bland-Altman showing a mean difference of − 0.125 1/s (SD = 30.667 1/s).

Conclusions

The 3D-multiecho-Dixon sequence is a reliable tool to quantify hepatic iron. Results are comparable with established relaxometry methods. Improvements to the original implementation eliminate occasional F/W swaps and limitations regarding maximum R2* values.

Key Points

• The 3D-multiecho-Dixon sequence for 1.5 T is a reliable tool to quantify hepatic iron.

• Results of the 3D-multiecho-Dixon sequence are comparable with established relaxometry methods.

• An improved version of the 3D-multiecho-Dixon sequence eliminates minor drawbacks.

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 ( R 2 and R 2 * ) and susceptibility.

RESULTS

Simulations demonstrate that R 2 and R 2 * measurements depend on the spatial distribution of iron even for the same iron concentration and volume susceptibility. Similarly, in vitro experiments demonstrate that R 2 and R 2 * 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

R 2 and R 2 * 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.

Practical guide to quantification of hepatic iron with MRI

Abstract

Our intention is to demystify the MR quantification of hepatic iron (i.e., the liver iron concentration) and give you a step-by-step approach by answering the most pertinent questions. The following article should be more of a manual or guide for every radiologist than a classic review article, which just summarizes the literature. Furthermore, we provide important background information for professional communication with clinicians. The information regarding the physical background is reduced to a minimum. After reading this article, you should be able to perform adequate MR measurements of the LIC with 1.5-T or 3.0-T scanners.

Key Points

• MRI is widely accepted as the primary approach to non-invasively determine liver iron concentration (LIC).

• This article is a guide for every radiologist to perform adequate MR measurements of the LIC.

• When using R2* relaxometry, some points have to be considered to obtain correct measurements—all explained in this article.

Characterizing a short T2 * signal component in the liver using ultrashort TE chemical shift-encoded MRI at 1.5T and 3.0T

PURPOSE

Recent studies have suggested the presence of short-T₂ * signals in the liver, which may confound chemical shift-encoded (CSE) fat quantification when using short echo times (TEs). The purpose of this study was to characterize the liver signal at short echo times and to determine its impact on liver fat quantification.

METHODS

An ultrashort echo time (UTE) chemical shift-encoded MRI (CSE-MRI) technique and a multicomponent reconstruction were developed to characterize short-T₂ * liver signals. Subsequently, liver fat fraction was quantified using a short-TE (first TE = 0.7 ms) and UTE CSE-MRI acquisitions and compared with a standard CSE-MRI (first TE = 1.2 ms).

RESULTS

Short-T₂ * signals were consistently observed in the liver of all healthy volunteers imaged at both 1.5T and 3.0T. At 3.0T, short-T₂ * signal fractions of 9.6 ± 1.5%, 7.0 ± 1.7%, and 7.4 ± 1.7% with T₂ * of 0.23 ± 0.05 ms, 0.20 ± 0.05 ms, and 0.10 ± 0.02 ms were measured in healthy volunteers, patients with liver cirrhotic disease, and patients with hepatic steatosis (but no cirrhosis), respectively. For proton density fat fraction (PDFF) estimation, 1.7% (P < .01) and 3.4% (P < .01) biases were observed in subjects imaged using short-TE CSE-MRI and using UTE CSE-MRI at 1.5T, respectively. The biases were reduced to 0.4% and -0.7%, respectively, by excluding short echoes less than 1 ms. A 3.2% bias (P < .01) was observed in subjects imaged using UTE CSE-MRI at 3.0T, which was reduced to 0.1% by excluding short echoes <1 ms.

CONCLUSIONS

A liver short-T₂ * signal component was consistently observed and was shown to confound liver fat quantification when short echo times were used with CSE-MRI.

MRI for Iron Overload in Thalassemia

MRI is a key tool in the current management of patients with thalassemia. Given its capability of assessing iron overload in different organs noninvasively and without contrast, it has significant advantages over other metrics, including serum ferritin. Liver iron concentration can be measured either with relaxometry methods T2*/T2 or signal intensity ratio techniques. Myocardial iron can be assessed in the same examination through T2* imaging. In this review, we focus on showing how MRI evaluates iron in both organs and the clinical applications as well as practical approaches to using this tool by clinicians taking care of patients with thalassemia.

Ultrashort echo time imaging for quantification of hepatic iron overload: Comparison of acquisition and fitting methods via simulations, phantoms, and in vivo data

BACKGROUND

Current R2*-MRI techniques for measuring hepatic iron content (HIC) use various acquisition types and fitting models.

PURPOSE

To evaluate the accuracy and precision of R2*-HIC acquisition and fitting methods.

STUDY TYPE

Signal simulations, phantom study, and prospective in vivo cohort.

POPULATION

In all, 132 patients (58/74 male/female, mean age 17.7 years).

FIELD STRENGTH/SEQUENCE

2D-multiecho gradient-echo (GRE) and ultrashort echo time (UTE) acquisitions at 1.5T.

ASSESSMENT

Synthetic MR signals were created to mimic published GRE and UTE methods, using different R2* values (25-2000 s^-1 ) and signal-to-noise ratios (SNR). Phantoms with varying iron concentrations were scanned at 1.5T. In vivo data were analyzed from 132 patients acquired at 1.5T. R2* was estimated by fitting using three signal models. Accuracy and precision of R2* measurements for UTE acquisition parameters (SNR, echo spacing [ΔTE], maximum echo time [TE_max ]) and fitting methods were compared for simulated, phantom, and in vivo datasets.

STATISTICAL TESTS

R2* accuracy was determined from the relative error and by linear regression analysis. Precision was evaluated using coefficient of variation (CoV) analysis.

RESULTS

In simulations, all models had high R2* accuracy (error <5%) and precision (CoV <10%) for all SNRs, shorter ΔTE (≤0.5 msec), and longer TE_max (≥10.1 msec); except the constant offset model overestimated R2* at the lowest SNR. In phantoms and in vivo, all models produced similar R2* values for different SNRs and shorter ΔTEs (slopes: 0.99-1.06, R² > 0.99, P < 0.001). In all experiments, R2* results degraded for high R2* values with longer ΔTE (≥1 msec). In vivo, shorter and longer TE_max gave similar R2* results (slopes: 1.02-1.06, R² > 0.99, P < 0.001) for the noise subtraction model for 25≤R2*≤2000 s^-1 . However, both quadratic and constant offset models, using shorter TE_max (≤4.7 msec) overestimated R2* and yielded high CoVs up to ∼170% for low R2* (<250 s^-1 ).

DATA CONCLUSION

UTE with TE_max ≥ 10.1 msec and ΔTE ≤ 0.5 msec yields accurate R2* estimates over the entire clinical HIC range. Monoexponential fitting with noise subtraction is the most robust signal model to changes in UTE parameters and achieves the highest R2* accuracy and precision.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1475-1488.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Thalassaemia

Inherited haemoglobin disorders, including thalassaemia and sickle-cell disease, are the most common monogenic diseases worldwide. Several clinical forms of α-thalassaemia and β-thalassaemia, including the co-inheritance of β-thalassaemia with haemoglobin E resulting in haemoglobin E/β-thalassaemia, have been described. The disease hallmarks include imbalance in the α/β-globin chain ratio, ineffective erythropoiesis, chronic haemolytic anaemia, compensatory haemopoietic expansion, hypercoagulability, and increased intestinal iron absorption. The complications of iron overload, arising from transfusions that represent the basis of disease management in most patients with severe thalassaemia, might further complicate the clinical phenotype. These pathophysiological mechanisms lead to an array of clinical manifestations involving numerous organ systems. Conventional management primarily relies on transfusion and iron-chelation therapy, as well as splenectomy in specific cases. An increased understanding of the molecular and pathogenic factors that govern the disease process have suggested routes for the development of new therapeutic approaches that address the underlying chain imbalance, ineffective erythropoiesis, and iron dysregulation, with several agents being evaluated in preclinical models and clinical trials.

Ultra-short echo time images quantify high liver iron

PURPOSE

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

THEORY AND METHODS

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

RESULTS

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

CONCLUSION

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

A USPIO doped gel phantom for R2* relaxometry

OBJECTIVE

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.

MATERIALS AND METHODS

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.

RESULTS

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.

CONCLUSION

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

Comparison between different software programs and post-processing techniques for the MRI quantification of liver iron concentration in thalassemia patients

PURPOSE

In magnetic resonance imaging (MRI) relaxometry, various software programs are available to perform R2* measurements and to estimate the liver iron concentration (LIC). The main objective of our study was to compare R2* LIC values, obtained with three different software programs based on specific decay models and calibration curves, with LIC estimates provided by R2-relaxometry (FerriScan).

METHODS

This retrospective study included 15 patients with 15 baseline MRIs and 34 serial examinations. R2* LIC estimates were calculated using the FuncTool, CMRtools/Thalassemia Tools and Quanta Hematology programs. Longitudinal LIC changes (ΔLIC) were calculated using the subset of 34 serial MRIs.

RESULTS

After Bland-Altman analysis on baseline data, Quanta Hematology, which employs the monoexponential-plus-constant fit, produced the lowest mean difference [0.01 ± 0.14 log(mg/gdw)] with the closest limits of agreement. In the longitudinal setting, Quanta Hematology again gave the lowest mean difference between R2 and R2* LIC (0.1 ± 2.6 mg/gdw). Using FerriScan as reference, the value of concordant directional ΔLIC changes was the same for all programs (27/34, 85.7 %).

CONCLUSIONS

R2* LICs are higher than R2 LICs at iron levels <7 mg/gdw, while R2 LIC averages higher than R2* LIC with increasing iron load. The monoexponential-plus-constant model provided the best agreement with R2 LIC estimates.

Pierre T, Heeney MM, Schultz WH, Davis BR, Ware RE. Liver iron concentration measurements by MRI in chronically transfused children with sickle cell anemia: baseline results from the TWiTCH trial

Noninvasive, quantitative, and accurate assessment of liver iron concentration (LIC) by MRI is useful for patients receiving transfusions, but R2 and R2* MRI techniques have not been systematically compared in sickle cell anemia (SCA). We report baseline LIC results from the TWiTCH trial, which compares hydroxyurea with blood transfusion treatment for primary stroke prophylaxis assessed by transcranial Doppler sonography in pediatric SCA patients. Liver R2 was collected and processed using a FDA-approved commercial process (FerriScan®), while liver R2* quality control and processing were performed by a Core Laboratory blinded to clinical site and patient data. Baseline LIC studies using both MRI techniques were available for 120 participants. LICR2* and LICR2 results were highly correlated (r(2)  = 0.93). A proportional bias of LIC(R2*)/LIC(R2), decreasing with average LIC, was observed. Systematic differences between LICR2* and LICR2 were also observed by MRI manufacturer. Importantly, LICR2* and LICR2 estimates had broad 95% limits of agreement with respect to each other. We recommend LICR2 and LICR2* not be used interchangeably in SCA patients to follow individual patient trends in iron burden.

Estimating tissue iron burden: current status and future prospects

Iron overload is becoming an increasing problem as haemoglobinopathy patients gain greater access to good medical care and as therapies for myelodysplastic syndromes improve. Therapeutic options for iron chelation therapy have increased and many patients now receive combination therapies. However, optimal utilization of iron chelation therapy requires knowledge not only of the total body iron burden but the relative iron distribution among the different organs. The physiological basis for extrahepatic iron deposition is presented in order to help identify patients at highest risk for cardiac and endocrine complications. This manuscript reviews the current state of the art for monitoring global iron overload status as well as its compartmentalization. Plasma markers, computerized tomography, liver biopsy, magnetic susceptibility devices and magnetic resonance imaging (MRI) techniques are all discussed but MRI has come to dominate clinical practice. The potential impact of recent pancreatic and pituitary MRI studies on clinical practice are discussed as well as other works-in-progress. Clinical protocols are derived from experience in haemoglobinopathies but may provide useful guiding principles for other iron overload disorders, such as myelodysplastic syndromes.

Guidelines for quantifying iron overload

Both primary and secondary iron overload are increasingly prevalent in the United States because of immigration from the Far East, increasing transfusion therapy in sickle cell disease, and improved survivorship of hematologic malignancies. This chapter describes the use of historical data, serological measures, and MRI to estimate somatic iron burden. Before chelation therapy, transfusional volume is an accurate method for estimating liver iron burden, whereas transferrin saturation reflects the risk of extrahepatic iron deposition. In chronically transfused patients, trends in serum ferritin are helpful, inexpensive guides to relative changes in somatic iron stores. However, intersubject variability is quite high and ferritin values may change disparately from trends in total body iron load over periods of several years. Liver biopsy was once used to anchor trends in serum ferritin, but it is invasive and plagued by sampling variability. As a result, we recommend annual liver iron concentration measurements by MRI for all patients on chronic transfusion therapy. Furthermore, it is important to measure cardiac T2* by MRI every 6-24 months depending on the clinical risk of cardiac iron deposition. Recent validation data for pancreas and pituitary iron assessments are also presented, but further confirmatory data are suggested before these techniques can be recommended for routine clinical use.

Methodologies and Tools Used Today for Measuring Iron Load

Iron overload is a matter of an extreme clinical importance, in the overall management of Thalassaemia. Magnetic Resonance Imaging (MRI), has evolved in a novel tool for iron quantification during the last decade and it is considered as a validated, accurate and noninvasive method with worldwide distribution. The MRI scanner exploits the intrinsic magnetic properties of the hydrogen nuclei in order to discriminate the tissue characteristics. The presence of iron in a tissue causes a faster dephasing of the protons and a reduction in T2* and T2. R2 and R2* represent the reciprocal of T2 and T2*. In order to measure the signal intensity and quantify iron concentration the Gradient Echo (GRE) T2* and the Spin Echo (SE) T2 sequence are used. There are two broad groups of techniques to quantify the iron. The signal intensity ratio (SIR) methods and the relaxometry methods. The later are sub grouped in the R2 (T2) relaxometry methods with the predominant of this category being the FerriScan® and the R2* (T2*) methods. CMR Gradient Echo T2* pulse sequence is the preferred technique for the quantification of iron in the heart. The R2 and R2* methodologies are both very accurate in predicting the true LIC with high levels of sensitivity and specificity in the range of clinically important LIC thresholds and can be both used over a wide clinical range, individually.

Quantitative susceptibility mapping in the abdomen as an imaging biomarker of hepatic iron overload

PURPOSE

The purpose of this work was to develop and demonstrate feasibility and initial clinical validation of quantitative susceptibility mapping (QSM) in the abdomen as an imaging biomarker of hepatic iron overload.

THEORY AND METHODS

In general, QSM is faced with the challenges of background field removal and dipole inversion. Respiratory motion, the presence of fat, and severe iron overload further complicate QSM in the abdomen. We propose a technique for QSM in the abdomen that addresses these challenges. Data were acquired from 10 subjects without hepatic iron overload and 33 subjects with known or suspected iron overload. The proposed technique was used to estimate the susceptibility map in the abdomen, from which hepatic iron overload was measured. As a reference, spin-echo data were acquired for R2-based LIC estimation. Liver R2* was measured for correlation with liver susceptibility estimates.

RESULTS

Correlation between susceptibility and R2-based LIC estimation was R(2) = 0.76 at 1.5 Tesla (T) and R(2) = 0.83 at 3T. Furthermore, high correlation between liver susceptibility and liver R2* (R(2) = 0.94 at 1.5T; R(2) = 0.93 at 3T) was observed.

CONCLUSION

We have developed and demonstrated initial validation of QSM in the abdomen as an imaging biomarker of hepatic iron overload.

Use of magnetic resonance imaging to monitor iron overload

Treatment of iron overload requires robust estimates of total-body iron burden and its response to iron chelation therapy. Compliance with chelation therapy varies considerably among patients, and individual reporting is notoriously unreliable. Even with perfect compliance, intersubject variability in chelator effectiveness is extremely high, necessitating reliable iron estimates to guide dose titration. In addition, each chelator has a unique profile with respect to clearing iron stores from different organs. This article presents the tools available to clinicians to monitor their patients, focusing on noninvasive magnetic resonance imaging methods because they have become the de facto standard of care.

Biopsy-based calibration of T2* magnetic resonance for estimation of liver iron concentration and comparison with R2 Ferriscan

BACKGROUND

There is a need to standardise non-invasive measurements of liver iron concentrations (LIC) so clear inferences can be drawn about body iron levels that are associated with hepatic and extra-hepatic complications of iron overload. Since the first demonstration of an inverse relationship between biopsy LIC and liver magnetic resonance (MR) using a proof-of-concept T2* sequence, MR technology has advanced dramatically with a shorter minimum echo-time, closer inter-echo spacing and constant repetition time. These important advances allow more accurate calculation of liver T2* especially in patients with high LIC.

METHODS

Here, we used an optimised liver T2* sequence calibrated against 50 liver biopsy samples on 25 patients with transfusional haemosiderosis using ordinary least squares linear regression, and assessed the method reproducibility in 96 scans over an LIC range up to 42 mg/g dry weight (dw) using Bland-Altman plots. Using mixed model linear regression we compared the new T2*-LIC with R2-LIC (Ferriscan) on 92 scans in 54 patients with transfusional haemosiderosis and examined method agreement using Bland-Altman approach.

RESULTS

Strong linear correlation between ln(T2*) and ln(LIC) led to the calibration equation LIC = 31.94(T2*)-1.014. This yielded LIC values approximately 2.2 times higher than the proof-of-concept T2* method. Comparing this new T2*-LIC with the R2-LIC (Ferriscan) technique in 92 scans, we observed a close relationship between the two methods for values up to 10 mg/g dw, however the method agreement was poor.

CONCLUSIONS

New calibration of T2* against liver biopsy estimates LIC in a reproducible way, correcting the proof-of-concept calibration by 2.2 times. Due to poor agreement, both methods should be used separately to diagnose or rule out liver iron overload in patients with increased ferritin.