Hepatic Iron Quantification Research Articles

Dual gradient echo in-phase and out of phase sequences in assessment of hepatic iron overload in patients with beta-thalassemia, would be better?

PurposeTo evaluate the diagnostic accuracy of the dual gradient-echo (GRE) in- and out-of-phase sequences as a quantitative tool for hepatic iron overload in comparison with MRI R2* relaxometry in paediatric patients with beta-thalassemia. MethodSixty-three patients with beta-thalassemia major (transfusion-dependent) or beta-thalassemia intermedia (transfusion- and non-transfusion-dependent) were referred from the paediatric department (haematology unit) to the radiology department at a university hospital. The paediatrician conducted a clinical examination for the studied group, assessed their laboratory data, conducted R2* relaxometry and dual gradient echo sequences to calculate R2* and relative signal intensity index at the axial mid-section of the liver, and studied their correlation. A 1.5 Tesla MR scanner was used (Achieva; Philips Medical Systems, the Netherlands). Data were fed to the computer and analysed using the IBM SPSS software package version 20.0 (Armonk, NY: IBM Corp). The Kolmogorov-Smirnov test was used to verify the normality of distribution. The significance of the results was determined at the 5% level. The Chi-square, Fisher’s exact correction, Pearson coefficient, and Bland–Altman tests were used. ResultsDual gradient-echo in- and out-of-phase sequences using visual assessment accurately assessed 93.65% of our patient group with hepatic iron overload. A significant correlation was found between the relative signal intensity index and hepatic MRI R2* relaxometry (p < 0.001, r = 0.861). ConclusionsDual gradient-echo in and out-of-phase sequences are good imaging tools for hepatic iron detection and quantification. These sequences showed good correlation with R2* relaxometry (r = 0.861, p < 0.001).

Automated Whole-Liver MRI Segmentation to Assess Steatosis and Iron Quantification in Chronic Liver Disease.

Background Standardized manual region of interest (ROI) sampling strategies for hepatic MRI steatosis and iron quantification are time consuming, with variable results. Purpose To evaluate the performance of automatic MRI whole-liver segmentation (WLS) for proton density fat fraction (PDFF) and iron estimation (transverse relaxometry [R2*]) versus manual ROI, with liver biopsy as the reference standard. Materials and Methods This prospective, cross-sectional, multicenter study recruited participants with chronic liver disease who underwent liver biopsy and chemical shift-encoded 3.0-T MRI between January 2017 and January 2021. Biopsy evaluation included histologic grading and digital pathology. MRI liver sampling strategies included manual ROI (two observers) and automatic whole-liver (deep learning algorithm) segmentation for PDFF- and R2*-derived measurements. Agreements between segmentation methods were measured using intraclass correlation coefficients (ICCs), and biases were evaluated using Bland-Altman analyses. Linear regression analyses were performed to determine the correlation between measurements and digital pathology. Results A total of 165 participants were included (mean age ± standard deviation, 55 years ± 12; 96 women; 101 of 165 participants [61%] with nonalcoholic fatty liver disease). Agreements between mean measurements were excellent, with ICCs of 0.98 for both PDFF and R2*. The median bias was 0.5% (interquartile range, -0.4% to 1.2%) for PDFF and 2.7 sec-1 (interquartile range, 0.2-5.3 sec-1) for R2* (P < .001 for both). Margins of error were lower for WLS than ROI-derived parameters (-0.03% for PDFF and -0.3 sec-1 for R2*). ROI and WLS showed similar performance for steatosis (ROI AUC, 0.96; WLS AUC, 0.97; P = .53) and iron overload (ROI AUC, 0.85; WLS AUC, 0.83; P = .09). Correlations with digital pathology were high (P < .001) between the fat ratio and PDFF (ROI r = 0.89; WLS r = 0.90) and moderate (P < .001) between the iron ratio and R2* (ROI r = 0.65; WLS r = 0.64). Conclusion Proton density fat fraction and transverse relaxometry measurements derived from MRI automatic whole-liver segmentation (WLS) were accurate for steatosis and iron grading in chronic liver disease and correlated with digital pathology. Automated WLS estimations were higher, with a lower margin of error than manual region of interest estimations. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Moura Cunha and Fowler in this issue.

MRI-Based Iron Phenotyping and Patient Selection for Next-Generation Sequencing of Non-Homeostatic Iron Regulator Hemochromatosis Genes.

Background and AimsHigh serum ferritin is frequent among patients with chronic liver disease and commonly associated with hepatic iron overload. Genetic causes of high liver iron include homozygosity for the p.Cys282Tyr variant in homeostatic iron regulator (HFE) and rare variants in non‐HFE genes. The aims of the present study were to describe the landscape and frequency of mutations in hemochromatosis genes and determine whether patient selection by noninvasive hepatic iron quantification using MRI improves the diagnostic yield of next‐generation sequencing (NGS) in patients with hyperferritinemia.Approach and ResultsA cohort of 410 unselected liver clinic patients with high serum ferritin (defined as ≥200 μg/L for women and ≥300 μg/L for men) was investigated by HFE genotyping and abdominal MRI R2*. Forty‐one (10%) patients were homozygous for the p.Cys282Tyr variant in HFE. Of the remaining 369 patients, 256 (69%) had high transferrin saturation (TSAT; ≥45%) and 199 (53%) had confirmed hepatic iron overload (liver R2* ≥70 s−1). NGS of hemochromatosis genes was carried out in 180 patients with hepatic iron overload, and likely pathogenic variants were identified in 68 of 180 (38%) patients, mainly in HFE (79%), ceruloplasmin (25%), and transferrin receptor 2 (19%). Low spleen iron (R2* <50 s−1), but not TSAT, was significantly associated with the presence of mutations. In 167 patients (93%), no monogenic cause of hepatic iron overload could be identified.ConclusionsIn patients without homozygosity for p.Cys282Tyr, coincident pathogenic variants in HFE and non‐HFE genes could explain hyperferritinemia with hepatic iron overload in a subset of patients. Unlike HFE hemochromatosis, this type of polygenic hepatic iron overload presents with variable TSAT. High ferritin in blood is an indicator of the iron storage disease, hemochromatosis. A simple genetic test establishes this diagnosis in the majority of patients affected. MRI of the abdomen can guide further genetic testing.

Simultaneous hepatic iron and fat quantification with dual-energy CT in a rabbit model of coexisting iron and fat.

Liver iron and fat are often co-deposited, synergistically aggravating the progression of chronic liver disease. Accurate determination of liver iron and fat content is helpful for patient management. To assess the accuracy of hepatic iron/fat decomposition using dual-energy computed tomography (DECT) for simultaneously quantifying hepatic iron and fat when both are present. Sixty-eight New Zealand rabbits on a high-fat/cholesterol diet plus iron injections were used to establish a model of coexisting hepatic iron/fat. Abdominal imaging was performed using dual-source DECT. The iron and fat fractions (Iron-CT and Fat-CT, respectively) were calculated using a 3-material decomposition algorithm. The spectroscopic liver iron concentration (LIC) grading (normal, mild, moderate, severe, and massive iron overload) and the histopathological fat fraction (Fat-ref) grading (normal, mild, moderate, severe steatosis) were used as references. Correlations between the DECT parameters and the references were analyzed. Hepatic iron/fat quantification equations were established and validated. Analysis of covariance was used to assess the influence of fat on iron measurements and vice versa. Iron-CT highly correlated with LIC (r=0.94, P<0.001), and Fat-CT highly correlated with Fat-ref (r=0.88, P<0.001). Both the Iron-CT- and Fat-CT-derived LIC and fat fraction showed good agreement with spectroscopy/histology. The linear relationship between Iron-CT and spectroscopic LIC was not affected by the grade of hepatic fat (F=1.93, P=0.16). The linear relationship between Fat-CT and Fat-ref was unaffected by hepatic iron grades from normal to severe (F=0.18, P=0.91). However, with massive iron overload [>15.0 mg Fe/g (270 µmol/g)] the regression began to deviate, causing fat underestimation (F=5.50, P=0.04). Our DECT-based iron/fat decomposition algorithm accurately measured hepatic iron and fat when both were present in a rabbit model. Hepatic fat may be underestimated when there is massive iron overload.

Evaluation of liver iron overload with R2* relaxometry with versus without fat suppression: both are clinically accurate but there are differences.

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 = 0.99ms). 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.

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.

Clinical Implementation of a Focused MRI Protocol for Hepatic Fat and Iron Quantification.

OBJECTIVE. The purpose of this article is to describe our institutional experience with the clinical implementation of a novel focused rapid chemical shift-encoded MRI protocol specifically intended to detect and quantify hepatic steatosis and iron overload, highlighting usage statistics and issues related to cost. CONCLUSION. Focused MRI examinations for specific clinical indications, such as this protocol for detection and quantification of hepatic steatosis and iron overload, are feasible in a busy clinical practice and add value for patients and referring providers.

Autoregressive moving average modeling for hepatic iron quantification in the presence of fat.

Measuring hepatic R2* by fitting a monoexponential model to the signal decay of a multigradient-echo (mGRE) sequence noninvasively determines hepatic iron content (HIC). Concurrent hepatic steatosis introduces signal oscillations and confounds R2* quantification with standard monoexponential models. To evaluate an autoregressive moving average (ARMA) model for accurate quantification of HIC in the presence of fat using biopsy as the reference. Phantom study and in vivo cohort. Twenty iron-fat phantoms covering clinically relevant R2* (30-800 s-1 ) and fat fraction (FF) ranges (0-40%), and 10 patients (four male, six female, mean age 18.8 years). 2D mGRE acquisitions at 1.5 T and 3 T. Phantoms were scanned at both field strengths. In vivo data were analyzed using the ARMA model to determine R2* and FF values, and compared with biopsy results. Linear regression analysis was used to compare ARMA R2* and FF results with those obtained using a conventional monoexponential model, complex-domain nonlinear least squares (NLSQ) fat-water model, and biopsy. In phantoms and in vivo, all models produced R2* and FF values consistent with expected values in low iron and low/high fat conditions. For high iron and no fat phantoms, monoexponential and ARMA models performed excellently (slopes: 0.89-1.07), but NLSQ overestimated R2* (slopes: 1.14-1.36) and produced false FFs (12-17%) at 1.5 T; in high iron and fat phantoms, NLSQ (slopes: 1.02-1.16) outperformed monoexponential and ARMA models (slopes: 1.23-1.88). The results with NLSQ and ARMA improved in phantoms at 3 T (slopes: 0.96-1.04). In patients, mean R2*-HIC estimates for monoexponential and ARMA models were close to biopsy-HIC values (slopes: 0.90-0.95), whereas NLSQ substantially overestimated HIC (slope 1.4) and produced false FF values (4-28%) with very high SDs (15-222%) in patients with high iron overload and no steatosis. ARMA is superior in quantifying R2* and FF under high iron and no fat conditions, whereas NLSQ is superior for high iron and concurrent fat at 1.5 T. Both models give improved R2* and FF results at 3 T. 2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:1620-1632.

State of the art in magnetic resonance imaging of hepatocellular carcinoma.

BackgroundLiver cancer is the sixth most common cancer worldwide and the second leading cause of cancer mortality. Chronic liver disease caused by viral infection, alcohol abuse, or other factors can lead to cirrhosis. Cirrhosis is the most important clinical risk factor for hepatocellular carcinoma (HCC) whereby the normal hepatic architecture is replaced by fibrous septa and a spectrum of nodules ranging from benign regenerative nodules to HCC, each one of them with different imaging features.ConclusionsFurthermore, advanced techniques including the quantification of hepatic and intralesional fat and iron, magnetic resonance elastography, radiomics, radiogenomics, and positron emission tomography (PET)-MRI are highly promising for the extraction of new imaging biomarkers that reflect the tumor microenvironment and, in the future, may add decision-making value in the management of patients with HCC.

Corrigendum to "Hepatic Iron Quantification on 3 Tesla (3 T) Magnetic Resonance (MR): Technical Challenges and Solutions".

[This corrects the article DOI: 10.1155/2013/628150.].

Hepatic iron is the major determinant of serum ferritin in NAFLD patients.

Elevated serum ferritin is common in NAFLD, and is associated with more advanced disease and increased mortality. Hyperferritinaemia in NAFLD is often attributed to inflammation, while in other conditions ferritin closely reflects body iron stores. The aim of this study was to clarify the underlying cause of hyperferritinaemia in NAFLD. Ferritin levels were examined with markers of iron status, inflammation and liver injury across the clinical spectrum of NAFLD using blood, tissue and magnetic resonance (MR) imaging. A separate larger group of NAFLD patients with hepatic iron staining and quantification were used for validation. Serum ferritin correlated closely with the iron regulatory hormone hepcidin, and liver iron levels determined by MR. Furthermore, ferritin levels reflected lower serum adiponectin, a marker of insulin resistance, and liver fat, but not cytokine or CRP levels. Ferritin levels differed according to fibrosis stage, increasing from early to moderate disease, and declining in cirrhosis. A similar pattern was found in the validation cohort of NAFLD patients, where ferritin levels were highest in those with macrophage iron deposition. Multivariate analysis revealed liver iron and hepcidin levels as the major determinants of serum ferritin. While hyperferritinaemia is associated with markers of liver injury and insulin resistance, serum hepcidin and hepatic iron are the strongest predictors of ferritin levels. These findings highlight the role of disordered iron homeostasis in the pathogenesis of NAFLD, suggesting that therapies aimed at correcting iron metabolism may be beneficial.

3D Multiecho Dixon for the Evaluation of Hepatic Iron and Fat in a Clinical Setting.

To prospectively evaluate a new 3D-multiecho-Dixon (3D-ME-Dixon) sequence for the quantification of hepatic iron and fat in a clinical setting. In all, 120 patients underwent 1.5T magnetic resonance imaging of the liver between December 2013 and June 2015 including the following three sequences: 3D-ME-Dixon with inline calculation of R2* and proton-density fat-fraction (PDFF) maps, single-voxel-spectroscopy (SVS), 2D multigradient-echo sequence (2D-ME-GRE). SVS and 2D-ME-GRE were used as reference for PDFF and R2*, respectively. R2*- and PDFF-values from 3D-ME-Dixon were compared with those of the reference. Linear regression analysis, Bland-Altman plots, and agreement parameters were calculated. In total, 103 patients were finally included (87 men and 16 women; mean age, 50.51 years); 17/120 were excluded due to fat/water-swaps or R2*-values exceeding the constraint of 400 1/s for 3D-ME-Dixon. A strong correlation (r = 0.992, P < 0.001) between R2* of 3D-ME-Dixon and the reference 2D-ME-GRE was found. Bland-Altman analysis revealed systematically lower values for 3D-ME-Dixon (16.499%). Using an adapted threshold of 57 1/s, 3D-ME-Dixon obtained a positive/negative percentage agreement (PPA/NPA) of 84.4%/91.4% for detecting hepatic iron overload. For hepatic fat the correlation between 3D-ME-Dixon and the reference SVS was strong (r = 0.957, P < 0.001); PPA/NPA was 88.3%/91.4%. The 3D-ME-Dixon sequence is a valuable tool for the evaluation of hepatic iron and fat in a clinical setting. Fat/water-swaps remain a drawback requiring improvements to the implementation and making it necessary to have proven conventional sequences at hand in case of an eventual occurrence. 1. Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:793-800.

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

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

Diagnostic accuracy of dual-echo (in- and opposed-phase) T1-weighted gradient recalled echo for detection and grading of hepatic iron using quantitative and visual assessment.

Detection and quantification of hepatic iron with dual-echo gradient recalled echo (GRE) has been proposed as a rapid alternative to other magnetic resonance imaging (MRI) techniques. Co-existing steatosis and T1 weighting are limitations. This study assesses the accuracy of routine dual-echo GRE. Between 2010 and 2013, 109 consecutive patients underwent multi-echo (ME) MRI and dual-echo GRE for quantification of hepatic iron. Liver iron concentration (LIC) was calculated from ME-MRI. Relative signal intensity (RSI) and fat signal fraction (FSF) were calculated from dual-echo GRE. Four radiologists subjectively evaluated dual-echo GRE (±subtraction). Diagnostic accuracy was compared between techniques and correlated with biopsy using Fisher's exact test, Spearman correlation and regression. The sensitivity of visual detection of iron ranged from 48 to 55%. Subtraction did not increase sensitivity (p < 0.001). Inter-observer variability was substantial (κ = 0.72). The specificity of visual detection of iron approached 100% with false-positive diagnoses observed using subtraction. LIC showed a higher correlation with histopathological iron grade (r = 0.94, p < 0.001) compared with RSI (r = 0.65, p = 0.02). Univariate regression showed an association between RSI and LIC (B = 0.98, p < 0.001, CI 0.73-1.23); however, the association was not significant with multi-variate regression including FSF (p = 0.28). Dual-echo GRE has low sensitivity for hepatic iron. Subtraction imaging can result in false-positive diagnoses. • Routine liver MRI studies cannot effectively screen patients for iron overload. • Concomitant hepatic steatosis and iron limits diagnostic accuracy of routine liver MRI. • Dual-echo GRE subtraction imaging causes false-positive diagnoses of iron overload. • Dedicated MRI techniques should be used to diagnose and quantify iron overload.

Hepatic Iron Quantification on 3 Tesla (3 T) Magnetic Resonance (MR): Technical Challenges and Solutions.

MR has become a reliable and noninvasive method of hepatic iron quantification. Currently, most of the hepatic iron quantification is performed on 1.5 T MR, and the biopsy measurements have been paired with R 2 and R 2* values for 1.5 T MR. As the use of 3 T MR scanners is steadily increasing in clinical practice, it has become important to evaluate the practicality of calculating iron burden at 3 T MR. Hepatic iron quantification on 3 T MR requires a better understanding of the process and more stringent technical considerations. The purpose of this work is to focus on the technical challenges in establishing a relationship between T 2* values at 1.5 T MR and 3 T MR for hepatic iron concentration (HIC) and to develop an appropriately optimized MR protocol for the evaluation of T 2* values in the liver at 3 T magnetic field strength. We studied 22 sickle cell patients using multiecho fast gradient-echo sequence (MFGRE) 3 T MR and compared the results with serum ferritin and liver biopsy results. Our study showed that the quantification of hepatic iron on 3 T MRI in sickle cell disease patients correlates well with clinical blood test results and biopsy results. 3 T MR liver iron quantification based on MFGRE can be used for hepatic iron quantification in transfused patients.

Sensitivity analysis for liver iron measurement through neutron stimulated emission computed tomography: a Monte Carlo study in GEANT4

Neutron stimulated emission computed tomography (NSECT) is being developed as a non-invasive imaging modality to detect and quantify iron overload in the human liver. NSECT uses gamma photons emitted by the inelastic interaction between monochromatic fast neutrons and iron nuclei in the body to detect and quantify the disease. Previous simulated and physical experiments with phantoms have shown that NSECT has the potential to accurately diagnose iron overload with reasonable levels of radiation dose. In this work, we describe the results of a simulation study conducted to determine the sensitivity of the NSECT system for hepatic iron quantification in patients of different sizes. A GEANT4 simulation of the NSECT system was developed with a human liver and two torso sizes corresponding to small and large patients. The iron concentration in the liver ranged between 0.5 and 20 mg g−1, corresponding to clinically reported iron levels in iron-overloaded patients. High-purity germanium gamma detectors were simulated to detect the emitted gamma spectra, which were background corrected using suitable water phantoms and analyzed to determine the minimum detectable level (MDL) of iron and the sensitivity of the NSECT system. These analyses indicate that for a small patient (torso major axis = 30 cm) the MDL is 0.5 mg g−1 and sensitivity is ∼13 ± 2 Fe counts/mg/mSv and for a large patient (torso major axis = 40 cm) the values are 1 mg g−1 and ∼5 ± 1 Fe counts/mg/mSv, respectively. The results demonstrate that the MDL for both patient sizes lies within the clinically significant range for human iron overload.

Superior Vena Cava Occlusion by Cardiovascular Magnetic Resonance

A 30-year-old man was referred for cardiac and hepatic iron quantification by cardiovascular magnetic resonance. He was known to have β-thalassemia major and was heavily transfusion dependent, requiring intensive intravenous chelation therapy. However, after nonadherence to anticoagulation and parenteral therapy, his Portacath had thrombosed, necessitating removal. Cardiovascular magnetic …

Quantification of Hepatic Iron Deposition in Patients With Liver Disease: Comparison of Chemical Shift Imaging With Single-Echo T2*-Weighted Imaging

The purpose of this study was to determine the diagnostic performance of chemical shift imaging, compared with that of single-echo T2*-weighted imaging, for hepatic iron quantification in patients with liver disease, and to examine the confounding effect of steatosis. Sixty-three patients who underwent liver MRI and who had concomitant liver histopathologic analysis were retrospectively assessed. Chemical shift imaging and T2*-weighted imaging (n = 49) of the liver were reviewed by two independent observers. An iron index for each sequence (I(Fe-CSI) and I(Fe-T2*), respectively) was correlated with pathologic iron grade (0-4). Receiver operating characteristic curve analysis was performed to assess the accuracy of both sequences for the diagnosis of iron deposition (grades >or= 1, >or= 2, and >or= 3), and the impact of steatosis on accuracy was evaluated. Forty-seven (74.6%) patients had hepatic siderosis. There was a significant correlation between both I(Fe-CSI) and I(Fe-T2*) with pathologic iron grade (r = 0.65 and -0.61, respectively; p < 0.0001 for both). I(Fe-CSI) and I(Fe-T2*) were significantly higher or lower in iron grades 2-4 versus grades 0-1 and in grades 3-4 versus grades 0-2 (p < 0.001). Area under the curve values for detecting iron grade >or= 1, >or= 2, and >or= 3 were 0.75, 0.88, and 0.90 for I(Fe-CSI) and 0.72, 0.81, and 0.98 for I(Fe-T2*). Accuracy was lower for both sequences in steatotic patients for detection of iron grades >or= 1 and >or= 2, without reaching significance. Routine chemical shift imaging and single-echo T2*-weighted imaging have excellent diagnostic performance for detection of significant hepatic siderosis (grade >or= 2). Concomitant steatosis lowers the diagnostic performance of both sequences without reaching significance.

Hepatic iron status and response to therapy in chronic viral hepatitis B and C: A preliminary report

Aim : To investigate if hepatic iron content influences the response to therapy in patients with chronic hepatitis C or B. Background : It seems that the presence of elevated body iron stores and, in particular, elevated hepatic iron levels, is one of the strongest predictors of resistance to interferon treatment for chronic hepatitis C or B. Patients and methods : Two hundred and one patients with chronic hepatitis C or B who were referred to Tehran Hepatitis Center were enrolled in this study. Histological quantification of hepatic iron was carried out by scoring iron separately within hepatocytes, sinusoidal cells, and portal triads. To estimate a cut off point for iron deposit as a predictor of response to treatment, Odd´s ratio with 95% confidence interval was calculated for each level of iron deposit. Results : Iron scores were divided into two levels of high and low at several cut-off points, but the most significant differences were found when score 2 was considered as the cut-off point. Odd's ratios were not significant in any of the hepatic zones. The lowest P-values were related to zone II sinusoidal cells and the total of sinusoidal cells and portal iron score (P= 0.08) in which the Odd's ratios were 6 (95% CI, 0.77 to 46.6) and 3.9 (95% CI, 0.88 to 17.4) respectively. Conclusion : In our society, liver iron content cannot be considered as an important risk factor of resistance to treatment in chronic hepatitis patients because of the very small prevalence. So, hepatic iron measurement and scoring do not seem cost-effective and valuable for all patients with chronic hepatitis in our population.

Iron Overload in Patients Receiving Allogeneic Hematopoietic Stem Cell Transplantation: Quantification of Iron Burden by a Superconducting Quantum Interference Device (SQUID) and Therapeutic Effectiveness of Phlebotomy

Iron overload (IO) is a known adverse prognostic factor in patients who undergo allogeneic hematopoietic stem cell transplantation (HSCT) for thalassemia and appears to play a similar role in patients with other hematologic disorders. The estimation of IO is based primarily on serum ferritin level; however, many confounding factors can result in ferritin overestimation, especially in HSCT recipients. The aim of the present study was to quantify IO after HSCT using a superconducting quantum interference device (SQUID), and to evaluate the impact of IO on hepatic function and infections. In addition, the feasibility of iron depletion was investigated. A total of 102 consecutive allogeneic HSCT recipients admitted to our outpatient department between December 2005, and December 2007, were analyzed. Primary diagnosis included acute leukemia/myelodysplastic syndrome in 61% of cases. Assessment of IO after HSCT included serum ferritin; in those with hyperferritinemia (ferritin>1000 ng/mL), liver iron concentration (LIC) was evaluated by SQUID magnetic susceptometry. Iron removal therapy was offered to patients with moderate IO (LIC 1000-2000 microg Fe/g wet weight [ww]) or severe IO (LIC >2,000 microg Fe/g ww). Fifty-seven patients had a ferritin level <1000 ng/mL: the median time between HSCT and assessment of ferritin level was 1006 days (range, 93-5239 days), significantly different from the median time of 183 days (range, 78-2957 days) in the 45 patients with a ferritin level >1000 ng/mL. Out of 42 patients evaluated by SQUID, 29 had moderate to severe IO (median LIC value, 1493 microg Fe/g ww [range, 1030-3253]). In a multivariate analysis, a significant correlation was found between a ferritin level >1000 ng/mL and the presence of at least one abnormal liver function test (LFT) ORo=6.8; 95% CI=2.2-20.6). In addition, the rate of proven/probable invasive fungal disease was significantly higher in the patients with hyperferritinemia (13% vs 0%; P=.006). Nineteen of the 24 patients considered eligible for iron-depletion therapy underwent regular phlebotomy; 13 completed the program in a median of 287 days (range, 92-779 days), reaching the target of a ferritin level<500 ng/mL; LIC was significantly reduced (median, 1419 microg Fe/g ww to 625 microg Fe/g ww; P < .001) in 8 of the 9 patients who were revaluated by SQUID at the end of the iron-depletion program. In conclusion, the measurement of LIC obtained by SQUID documented the presence of moderate/severe IO in 69% of the patients with a high ferritin level. Our data showed that in HSCT recipients, high ferritin level is an independent risk factor for abnormal LFTs, and IO may be considered a potential risk factor for fungal infections. A phlebotomy program may be feasible in two-thirds of the patients who might benefit from iron depletion.