Liver Iron Concentration Values Research Articles

Can Automated 3-Dimensional Dixon-Based Methods Be Used in Patients With Liver Iron Overload?

Accurate quantification of liver iron concentration (LIC) can be achieved via magnetic resonance imaging (MRI). Maps of liver T2*/R2* are provided by commercially available, vendor-provided, 3-dimensional (3D) multiecho Dixon sequences and allow automated, inline postprocessing, which removes the need for manual curve fitting associated with conventional 2-dimensional (2D) gradient echo (GRE)-based postprocessing. The main goal of our study was to investigate the relationship among LIC estimates generated by 3D multiecho Dixon sequence to values generated by 2D GRE-based R2* relaxometry as the reference standard. A retrospective review of patients who had undergone MRI scans for estimation of LIC with conventional T2* relaxometry and 3D multiecho Dixon sequences was performed. A 1.5 T scanner was used to acquire the magnetic resonance studies. Acquisition of standard multislice multiecho T2*-based sequences was performed, and R2* values with corresponding LIC were estimated. The comparison between R2* and corresponding LIC estimates obtained by the 2 methods was analyzed via the correlation coefficients and Bland-Altman difference plots. This study included 104 patients (51 male and 53 female patients) with 158 MRI scans. The mean age of the patients at the time of scan was 15.2 (SD, 8.8) years. There was a very strong correlation between the 2 LIC estimation methods for LIC values up to 3.2 mg/g (LIC quantitative multiecho Dixon [qDixon; from region of interest R2*] vs LIC GRE [in-house]: r = 0.83, P < 0.01; LIC qDixon [from segmentation volume R2*] vs LIC GRE [in-house]: r = 0.92, P < 0.01); and very weak correlation between the 2 methods at liver iron levels >7 mg/g. Three-dimensional-based multiecho Dixon technique can accurately measure LIC up to 7 mg/g and has the potential to replace 2D GRE-based relaxometry methods.

Pancreatic iron in pediatric transfusion-dependent beta-thalassemia patients: A longitudinal MRI study.

In pediatric transfusion-dependent thalassemia (TDT) patients, we evaluated the prevalence, pattern, and clinical associations of pancreatic siderosis and the changes in pancreatic iron levels and their association with baseline and changes in total body iron balance. We considered 86 pediatric TDT patients consecutively enrolled in the Extension-Myocardial Iron Overload in Thalassemia Network. Iron overload (IO) was quantified by R2* magnetic resonance imaging (MRI). Sixty-three (73%) patients had pancreatic IO (R2*>38Hz). Global pancreas R2* values were significantly correlated with mean serum ferritin levels, MRI liver iron concentration (LIC) values, and global heart R2* values. Global pancreas R2* values were significantly higher in patients with altered versus normal glucose metabolism. Thirty-one patients also performed the follow-up MRI at 18±3months. Higher pancreatic R2* values were detected at the follow-up, but the difference versus the baseline MRI was not significant. The 20% of patients with baseline pancreatic IO showed no pancreatic IO at the follow-up. The 46% of patients without baseline pancreatic IO developed pancreatic siderosis. The changes in global pancreas R2* between the two MRIs were not correlated with baseline serum ferritin levels, baseline, final, and changes in MRI LIC values, or baseline pancreatic iron levels. In children with TDT, pancreatic siderosis is a frequent finding associated with hepatic siderosis and represents a risk factor for myocardial siderosis and alterations of glucose metabolism. Iron removal from the pancreas is exceptionally challenging and independent from hepatic iron status.

Diagnostic Accuracy of a Fully Automated Method of Analysing MR Images for Evaluation of Liver Iron Concentration in a Population of Thalassemia Major Patients Following Curative Stem Cell Transplantation in Lebanon

Background Measurement of liver iron concentration (LIC) by MRI is recommended in several guidelines on the management of iron overload in patients with thalassemia. However, a key barrier to adoption of such methods in resource poor countries is access to expertise and training in the associated image data analysis [Padeniya, et al. (2020) Orphanet Journal of Rare Diseases, 15: 26]. A new software system, DLA R2-MRI, based on deep-learning trained neural networks, (FerriSmart®, Resonance Health Analysis Services Pty Ltd, Australia) has become available that automatically carries out both input data quality assurance and data analysis of suitable MR images, increasing the possibility of more widespread adoption of reliable MRI based LIC measurement. Aims The aim of this study was to assess the diagnostic accuracy of the index DLA R2-MRI method on MR images acquired as part of a previous study comparing phlebotomy with deferasirox for the treatment of iron overload in pediatric patients with thalassemia major following curative stem cell transplantation [Inati, et al. (2017) Pediatric Blood &amp; Cancer, 64: 188]. LIC values from MR scans obtained with the spin-density-projection-assisted R2 MRI method (FerriScan®) were to be used as the reference values for the diagnostic accuracy study. Methods Archived MR data from the previous study were retrieved and analysed using the fully automated DLA R2-MRI software to generate LIC values. No human input was required in the analysis process and results were generated in seconds. The methods of Bland and Altman were used to determine the bias and 95% limits of agreement between the index and reference method. None of the image datasets in the study had been used to train the DLA R2-MRI neural networks. The sensitivities and specificities (with 95% CIs) of the index method for predicting LIC values by the reference method above the clinically relevant thresholds of 3, 5, 7, and 15 mg Fe/g dw were calculated using the Wilson-Brown method. Results Sixty nine (69) evaluations of LIC were carried out in the original study using the reference method. Sixty eight (68) datasets were retrieved from archives with one dataset missing. The 68 datasets were analysed by the DLA R2-MRI software. Six were rejected by the input quality control module owing to an absent date of birth in the DICOM images. The remaining 62 datasets yielded an LIC value. The 62 successful analyses represented evaluations on 32 patients with 8 patients being scanned 3 times, 14 patients being scanned twice, and 10 patients being scanned once. Patients (18 male, 14 female) ranged in age from 3.2 to 19.7 years at first scan (mean 13.1 SD 4.1 years). Twenty six (26) patients underwent iron reduction therapy during the study (14 phlebotomy and 12 chelation); 5 patients did not receive iron reduction therapy (4 not meeting eligibility criteria, and one was not treated due to parental refusal); one patient withdrew from the study after only 2 months of iron reduction therapy. A plot of the 62 LIC values by the index method plotted against the values from the reference method is shown in Figure 1. The bias between the index and reference results represented as the geometric mean ratio of the index LIC to the reference LIC was statistically insignificant being 1.00 [95% CI 0.96 - 1.05]. The sensitivities and specificities of the index method for predicting reference LIC values above clinically relevant thresholds are shown in Table 1. Conclusions The data show a negligible bias between the fully automated index DLA R2-MRI method and the manual expert-dependent reference SDPA R2-MRI method. The diagnostic accuracy is sufficient to guide iron reduction therapy in thalassemia major patients. The ability of the software both to provide input data quality assessment and LIC results within seconds without the need for data analyst training or outsourced analysis offers the opportunity for lower cost and more widespread availability of reliable LIC measurement by MRI for thalassemia major patients in Lebanon and beyond.

5613049 THE DIAGNOSTIC ACCURACY AND REPEATABILITY OF AN ARTIFICIAL INTELLIGENCE BASED SYSTEM TO OBTAIN AUTOMATED LIVER IRON CONCENTRATION MEASUREMENTS USING MAGNETIC RESONANCE IMAGING.

Background: Magnetic resonance imaging (MRI) methods have become routine for measuring liver iron concentration (LIC) for hemoglobinopathy patients in high income countries but require specialised training to analyse the image data1. While the cost of outsourcing data analysis is acceptable to many patients or providers in high income countries, the majority of hemoglobinopathy patients reside in low-income countries. Automated LIC measurements using artificial intelligence (AI) or deep-learning-assessed (DLA) algorithms could provide the solution for globally affordable and reliable patient monitoring of LIC. Here we update information presented at the EHA Annual Congress 2022. Aims: The aim of this study was to evaluate the diagnostic performance and repeatability of an automated deep-learning-based medical device (DLA R2-MRI) for measuring LIC from MRI. Methods: The DLA R2-MRI device was assessed prospectively on 1395 eligible consecutive MRI datasets from 63 different scanners submitted for expert manual analysis using spin-density projection assisted (SDPA) R2-MRI (the reference standard) between August 2017 and July 2020. Informed consent was waived by the Human Research Ethics Committee. The aetiologies for iron overload reported by the radiologists submitting the image data were thalassemias (477), hereditary hemochromatosis (168), sickle cell disease (152), MDS (11), other (316), unknown (271). The bias and limits of agreement between the automated and manual measurements of LIC were assessed. In addition, the diagnostic performance was assessed using sensitivity and specificity analysis. The repeatability of the DLA R2-MRI device was assessed by recruiting 60 participants with informed consent (50 patients and 10 healthy controls) each being measured twice with DLA R2-MRI (time between visits: min:1 hour max:7 days). Limits of agreement, bias, and repeatability coefficients were determined using Bland Altman statistics2. Results: The distribution of LIC values measured by the reference method was 31.6% (LIC<3 mg Fe/g); 17.3% (3≤ LIC <5 mg Fe/g); 11.4% (5≤ LIC <7 mg Fe/g); 18.7% (7≤ LIC <15 mg Fe/g); 21.0% (LIC > 15 mg Fe/g). The automated LIC results from the DLA R2-MRI are plotted against the results from the reference standard in the Figure where the solid line is the line of equivalence.The geometric mean ratios of the automated LIC results from the DLA R2-MRI to the manually derived results from SDPA R2-MRI were 0.98 (95% CI 0.94 - 1.01) below 3 mg Fe/g dry tissue and 0.93 (95% CI 0.92 - 0.95) above 3 mg Fe/g dry tissue. The sensitivities and specificities of the automated DLA R2-MRI system for predicting LIC values by the SDPA R2-MRI method above clinically relevant thresholds3 of 3.0, 5.0, 7.0, and 15.0 mg Fe/g dry tissue are shown in the Table. 95% of the repeat measures of LIC by DLA R2-MRI had ratios that fall between 0.79 and 1.26 above 3 mg Fe/g dw and between 0.64 and 1.57 below 3 mg Fe/g dry tissue. - Clinically relevant threshold3(mg Fe/g dry tissue) Sensitivity [95% CI](%) Specificity [95% CI](%) 3.0 96 [94-97] 95 [92-98] 5.0 91 [89-94] 97 [95-99] 7.0 92 [90-95] 97 [95-98] 15.0 89 [85-93] 98 [98-99] Summary/Conclusion: The repeatability of the DLA R2-MRI method for LIC measurement is significantly better than that for liver biopsy methods4-6. While there is an overall bias between DLA R2-MRI and SDPA R2-MRI, the bias does not result in unacceptable sensitivities and specificities of DLA R2-MRI for predicting SDPA R2-MRI results above the clinically relevant LIC thresholds. However, the bias between the automated and manual methods indicates that the two techniques should not be used interchangeably.

Mitapivat Improves Iron Overload in Patients with Pyruvate Kinase Deficiency

Background: Pyruvate kinase (PK) deficiency is a rare hereditary disease resulting in chronic hemolytic anemia. Iron overload is highly prevalent in patients (pts) with PK deficiency regardless of transfusion requirements, suggesting dyserythropoietic features. Iron overload can lead to serious complications including liver cirrhosis, cardiomyopathy, arrhythmia, sudden cardiac death, and endocrine dysfunction. In pts with PK deficiency, ineffective erythropoiesis combined with chronic hemolysis contributes to the manifestation of iron overload. Increased erythropoietic drive leading to erythroferrone-induced hepcidin suppression results in increased iron absorption and abnormal iron metabolism in PK deficiency. Furthermore, transfusions increase the existing burden of iron overload in PK deficiency. Mitapivat (AG-348) is a first-in-class, oral, allosteric activator of the red blood cell wildtype and mutant PK enzyme (PKR) that is approved by the US Food and Drug Administration for the treatment of hemolytic anemia in adults with PK deficiency, which has been shown to improve ineffective erythropoiesis and hemolysis. Previously reported data from ACTIVATE (NCT03548220) and its long-term extension (LTE) study (NCT03853798) also showed that treatment with mitapivat improved markers of iron homeostasis in adults with PK deficiency (up to 72 weeks [wks]). Here, we provide longer-term data from the LTE study on the impact of mitapivat on iron homeostasis and iron overload, and also assess liver iron concentration (LIC) changes in pts with iron overload at baseline (BL). Methods: In ACTIVATE (double-blind, placebo [PBO]-controlled study), pts with PK deficiency who were not regularly transfused were randomized 1:1 to receive mitapivat or PBO. Pts who had demonstrated clinical benefit from mitapivat on completion of the fixed-dose period for ACTIVATE (24 wks), or who were assigned to the PBO arm in ACTIVATE, were eligible to continue in the LTE. All pts enrolled in the LTE received mitapivat. Pts from ACTIVATE who continued in the LTE were categorized into the mitapivat-to-mitapivat arm (M/M) or PBO-to-mitapivat arm (P/M). The ACTIVATE/LTE analysis assessed changes from BL over time (up to 96 wks), for both study arms, in markers related to iron homeostasis and overload, including erythroferrone, soluble transferrin receptor (sTfR), hepcidin, and LIC by magnetic resonance imaging. LIC changes over time in pts with evidence of iron overload at BL, were also assessed; pts were considered to have iron overload at BL if they met at least 1 of 3 criteria: BL ferritin >1000 mg/L, BL average LIC >3 mg Fe/g dry weight (dw), or chelation therapy within the last year before study start. For this calculation, BL was defined as the last assessment before start of treatment with mitapivat, and LIC data from pts in the M/M arm were pooled together with data from pts in the P/M arm and summarized over the time they were treated with mitapivat. Results: 80 pts were included in the ACTIVATE/LTE analysis (M/M=40; P/M=40). Meaningful improvements in hepcidin, erythroferrone, sTfR, and LIC values were observed with mitapivat treatment previously; here, we confirm these meaningful improvements are continued up to 96 wks (Table). These measurements were improved early-on, within 24 wks of starting treatment in the M/M arm, but remained relatively unchanged in the P/M arm while on PBO. Similar improvements to the M/M arm were seen in the P/M arm after switching to mitapivat in the LTE. Among pts treated with mitapivat (N=78), 55.1% (n=43) met the criteria for iron overload at BL. These pts showed clinically meaningful and continued improvements in iron overload over time as measured by LIC (median [Q1, Q3] decrease from BL to Wk 96 of mitapivat treatment of -1.95 [-4.85, -0.70] mg Fe/g dw) (Figure). Conclusions: Activation of PKR with mitapivat was associated with meaningful long-term improvements in iron homeostasis and overload. Mitapivat is the first disease-modifying pharmacotherapy shown to have beneficial effects on iron overload in pts with PK deficiency. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Modern management of iron overload in thalassemia major patients guided by MRI techniques: real-world data from a long-term cohort study.

Monitoring liver and cardiac iron stores by magnetic resonance imaging (MRI) enables identifying patients at risk of organ-specific morbidity and better tailoring of iron chelation therapy in thalassemia. Nevertheless, serum ferritin (SF) remains the only tool for monitoring iron status in most resource-poor regions. In this study, we assessed the impact of using MRI techniques to guide iron chelation therapy on iron overload outcomes in a cohort of 99 patients with thalassemia major (TM, mean age at baselines 20.7 ± 6.9years) followed from 2006 to 2019. We also assessed the ability of SF trends to predict changes in consecutive liver iron concentration (LIC) and cardiac T2* (cT2*) measurements. The most commonly used chelator was deferasirox at baseline (65%) and final (72%) assessments. Overall, patients with safe LIC values (< 7mg/g dw) increased from 57 to 77%, and safe cT2* values (> 20ms) increased from 72 to 86%. We obtained the most significant improvement in patients with severe and moderate liver (p = 0.006 and p < 0.001) and cardiac (p < 0.0013 and p < 0.0001) iron overload at baseline. SF trends were in the same direction in 64% of changes in LIC, but only 42% of changes were proportional. Most of the changes in SF (64%) and LIC (61%) could not predict changes in cT2*. Moreover, downward trends in SF and LIC were associated with worsening cardiac iron in 29% and 23.5% of consecutive cT2* measurements. Liver and cardiac MRI-driven oral iron chelation improved the iron status of subjects with TM and demonstrated the importance of using validated MRI techniques in critical clinical decisions.

Iron overload status in patients with non-transfusion-dependent thalassemia in China.

Background:Iron overload is one of the main factors that increase morbidity and mortality in patients with non-transfusion dependent thalassemia (NTDT).Aim:This study aimed at investigating the prevalence and severity of iron overload in Chinese NTDT patients.Methods:we analyzed serum ferritin (SF), liver iron concentration (LIC) and cardiac T2* in 178 Chinese NTDT in this cross-sectional study.Results:The median SF level was 996.00(27.15–19704.00) ng/ml and the median LIC value was 8.90(0.60–43.00) mg Fe/g dry weight (dw). The youngest patient with liver iron overload was 5 years old with 5.6 mg Fe/g dw in LIC. The median cardiac T2* was 33.06(7.46–75.08) ms. 6 patients had cardiac T2*⩽20ms. The patients with β thalassemia intermedia and HbE/β thalassemia showed a statistically significant lower Hb and higher values of SF and LIC than those of hemoglobin H disease patients. On multivariate logistic regression analysis, patients in ⩾ age 30-year old had a significant higher risk for iron overload (OR: 77.75, 95% CI: 8.76–690.49) in the age group. The detailed analysis of proportions of different LIC indicate in > 30-year old group, 76.8% patients suffered from moderate and severe LIC.Conclusion:Our study provides a strong support for the novel findings that Chinese NTDT patients have a high prevalence of iron overload. The first assessment of MRI LIC should be performed as early as 5 years old. Then, NTDT patients > 30 years old may suffer with a high burden of iron overload.

Rusfertide (PTG-300), a Hepcidin Mimetic, Maintains Liver Iron Concentration in the Absence of Phlebotomies in Patients with Hereditary Hemochromatosis

▪Introduction: Patients with hereditary hemochromatosis (HH) require continued phlebotomies to limit end-organ damage. Approximately 25% of patients in maintenance felt receiving phlebotomies was “inconvenient” or “very inconvenient” (Brisott et al, 2011). Patient compliance with phlebotomies generally declines with time (Hicken et al, 2003), and therapeutic phlebotomies may not be medically suitable for some HH patients. Rusfertide, a peptide mimetic of hepcidin, is an effective regulator of iron distribution and utilization that has demonstrated control of iron in an animal model of HH.Methods: We conducted an open-label, dose-finding efficacy study that investigated subcutaneous rusfertide in HH patients on a stable phlebotomy regimen of 0.25 to 1 phlebotomy per month for at least 6 months. Patients with clinical laboratory abnormalities and those receiving iron chelation therapy or erythrocytapheresis were excluded. Subjects received individually titrated rusfertide doses once or twice a week to maintain transferrin saturation (TSAT) below 45% and were followed for 6 months. Study measures included TSAT, serum iron, transferrin and ferritin, liver iron concentration (LIC) measured by MRI, and adverse events (AEs).Results: Sixteen subjects (10 male/6 female) were enrolled. Mean age and weight were 62.5 years and 88.1 kg, respectively. LIC values were maintained at pre-study levels, with minimal use of phlebotomies during the duration of the study (Figure 1A). Average pre-study phlebotomy rate was 0.27 phlebotomies/month compared to 0.03 phlebotomies/month during the study (p<0.0001; Figure 1B). There was a dose- and concentration-dependent decrease in serum iron and TSAT (Figure 2A and 2B). Transferrin levels were relatively constant over the course of the study. There were no notable changes in hematological parameters such as hematocrit, erythrocytes, leucocytes, or platelets. Rusfertide was generally well tolerated. Adverse events reported in 2 or more subjects included diarrhea, fatigue, injection site reactions (erythema, induration, pain, pruritis), dizziness, and headache.Conclusions: Rusfertide demonstrated a pharmacodynamic effect in reducing TSAT and serum iron, with corresponding significant reduction in the number of phlebotomies, and with LIC maintained at pre-study levels with minimal use of phlebotomies. These data indicate rusfertide was well tolerated in patients with HH and controls LIC, supporting development of rusfertide as a potential treatment for HH. [Display omitted] DisclosuresKowdley: PTG: Consultancy, Research Funding. Modi: Protagonist Therapeutics: Current Employment. Valone: Protagonist Therapeutics: Current Employment, Current equity holder in publicly-traded company. Gupta: Protagonist Therapeutics: Current Employment.

Prospective Changes of Pancreatic Iron in Thalassemia Major

Introduction. Pancreatic iron deposition is a common finding in thalassemia major, being detected in more than one third of patients undergoing their first T2* Magnetic Resonance Imaging scan (MRI) for this purpose. However, no longitudinal studies on pancreatic iron are available in literature.Aim: The aim of this multicenter study was to evaluate the changes in pancreatic iron overload in TM patients enrolled in the Extension-Myocardial Iron Overload in Thalassemia (E-MIOT) Network who performed a baseline and a follow-up (FU) MRI scan at 18 months.Methods. We considered 416 TM patients (37.77±10.46 years; 220 females) consecutively enrolled. Iron overload was quantified by the T2* technique. T2* measurements were performed over pancreatic head, body and tail and global value was the mean.Results. Pancreatic iron overload (global pancreas T2*<26 ms) was detected in 367 (88.2%) patients. Of them, only 14 (3.8%) improved at the FU. Out of the 49 (11.8%) patients without baseline pancreatic iron overload, 15 (30.6%) showed pancreatic iron overload at the FU MRI.A significant inverse association was detected between % change in global pancreas T2*and baseline global pancreas T2* values (R=-0.369; P<0.0001). Patients with baseline pancreatic iron overload showed significantly higher % changes in global pancreas T2* values (see Figure).Changes (%) in global pancreas T2* were not associated with baseline serum ferritin levels or MRI liver iron concentration (LIC) values but were inversely correlated with % changes in serum ferritin levels (R=-0.199; P<0.0001) and % changes in MRI LIC values (R=-0.255; P<0.0001). A significant positive association was found between % changes in global pancreas and global heart T2* values (R=0.133; P=0.007).At baseline MRI, 169 patients showed an alteration of glucidic metabolism: 32 had impaired fasting glucose, 65 impaired glucose tolerance, and 72 diabetes mellitus. These patients showed significantly higher % changes in global pancreas T2* than patients with a normal glucidic metabolism (33.06±79.48% vs 11.93±59.47%; P=0.003).Conclusions. Our data showed that it is difficult to remove the iron from the pancreas and higher improvements were detected in more heavily loaded patients, with alterations of glucidic metabolism. The reduction in pancreatic iron was paralleled by a decrease in hepatic and cardiac iron. [Display omitted] DisclosuresPepe: Bayer S.p.A.: Other: no profit support; Chiesi Farmaceutici S.p.A: Other: no profit support. Maggio: Bluebird Bio: Membership on an entity's Board of Directors or advisory committees; Celgene Corp: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees.

Guidelines for the monitoring and management of iron overload in patients with haemoglobinopathies and rare anaemias.

Guidelines for the monitoring and management of iron overload in patients with haemoglobinopathies and rare anaemias.

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

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 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 estimates to LIC in both simulated and in-vivo human data. CPMG 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 served as the reference standard. The observed calibration between CPMG values and LIC were compared to results predicted from a previously validated Monte Carlo model. The sensitivity of CPMG-derived triples when a proton density constraint is applied. When compared with -LIC estimates, both monoexponential and nonexponential models were unbiased but demonstrated broad 95% confidence intervals particularly for LIC values below 12mg/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.

Measurement of Liver Iron Concentration in a Population of Non-Transfusion Dependent Thalassemia Patients Using a Trained Artificial Neural Network to Analyse Magnetic Resonance Images

Background: Measurements of liver iron concentration (LIC) by magnetic resonance imaging (MRI) have become established and validated in several research intensive centers. However, challenges remain with translating these measurement methodologies for routine clinical use. Current methods involve many steps presenting multiple opportunities for human error and can lead to systematic severe measurement error. Artificial neural networks (ANNs) can be trained to replace human input into image processing and may have a role in providing a simple, robust, and low cost solution for LIC measurement.Aims: The aim of the study wasto determine the limits of agreement between measurements of LIC by a reference standard spin-density-projection-assisted (SDPA) R2-MRI method (FerriScan) and a method using trained ANNs to analyse image data. MR image datasets (400) previously acquired from Siemens scanners were pre-processed and then, together with their corresponding SDPA R2-MRI LIC values, were filtered through publically available ANNs. The ANNs had been pre-trained on large image sets (ImageNet). Relevant features were extracted and then used to train a machine learning (gradient boosting) algorithm to predict LIC values from previously unseen MR image datasets.Methods: Thalassemia patients (N=100) referred by the National Institute of Haematology and Blood Transfusion, Hanoi, Vietnam for routine LIC measurement by MRI were prospectively recruited with informed consent. Patients were randomised to be scanned in either a Philips Ingenia or a Siemens Avanto 1.5T scanner. Image data were acquired using the FerriScan protocol. Images were then processed (1) using a quality controlled core laboratory data analysis service using the SDPA R2-MRI method and (2) by a non-radiologically-trained technician using the trained artificial neural network to generate LIC values. The technician was required to trace the outline of the torso and then click a mouse button. The technician using the ANN was blinded from the SDPA R2-MRI results and the analysts generating the SDPA R2-MRI results were blinded from the ANN results. Reported data were analysed using the statistical methods of Bland and Altman.Results: A plot of the ANN-predicted LIC values against the SDPA R2-MRI LIC values (Figure) shows the data scattered about the line of equivalence indicating that the ANN method is generating results that correlate with the validated SDPA R2-MRI reference standard. The geometric mean ratio of ANN LIC to SDPA R2-MRI LIC was 0.93 (95% CI 0.91 -0.96) indicating a small but statistically significant systematic underestimation of LIC by the ANN. The geometric mean ratios of the two LIC measurements were significantly different for the two scanners (0.98 for Philips and 0.90 for Siemens, p = 0.006) indicating that the bias of the ANN method against the reference standard is not universal but is dependent on scanner. Bland Altman analysis indicates that 95% of pairs of measurements are predicted to have ratios between 1.23 and 0.69 indicating a modest random variability between the ANN method and the reference standard that is better than that between biopsy and the reference standard. The performance of the ANN method in predicting SDPA R2-MRI LIC values above the clinically relevant thresholds of 7 and 15 mg Fe/g dw is characterized in Table 1 showing positive predictive values (PPVs) and negative predictive values (NPVs) together with their 95% CIs.Conclusion: The data indicate that the ANN method of measurement of LIC has potential to be used as a fast and robust method of analysing MR image data to generate LIC values. Further testing is required on a wider range of scanner types and with more patients with lower LICs. The performance of the ANN will also likely be improved through training on a larger number of datasets. [Display omitted] DisclosuresSt Pierre:Resonance Health Ltd: Consultancy, Equity Ownership, Speakers Bureau. Cooper:Resonance Health Ltd: Consultancy. Boulos:Resonance Health Ltd: Employment. House:Resonance Health Ltd: Employment. Pang:Resonance Health Ltd: Employment. Bangma:Resonance Health Ltd: Employment. Taher:Novartis Pharmaceuticals: Honoraria, Research Funding; Celgene: Research Funding.

Comparison of Inline R2* MRI versus FerriScan for liver iron quantification in patients on chelation therapy for iron overload: preliminary results.

MRI quantification of liver iron concentration (LIC) using R2 or R2* relaxometry requires offline post-processing causing reporting delays, administrative overhead, and added costs. A prototype 3D multi-gradient-echo pulse sequence, with inline post-processing, allows immediate calculation of LIC from an R2* map (inline R2*-LIC) without offline processing. We compared inline R2*-LIC to FerriScan and offline R2* calibration methods. Forty patients (25 women, 15 men; age 18-82 years), prospectively underwent FerriScan and the prototype sequence, which produces two R2* maps, with and without fat modeling, as well as an inline R2*-LIC map derived from the R2* map with fat modeling, with informed consent. For each map, the following contours were drawn: ROIs, whole-axial-liver contour, and an exact copy of contour utilized by FerriScan. LIC values from the FerriScan report and those calculated using an alternative R2 calibration were the reference standards. Results were compared using Pearson and interclass correlation coefficients (PCC, ICC), linear regression, Bland-Altman analysis, and estimation of area under the receiver operator curve (ROC-AUC). Inline R2*-LIC demonstrated good agreement with the reference standards. Compared to FerriScan, inline R2*-LIC with whole-axial-liver contour, ROIs, and FerriScan contour demonstrated PCC of 94.8%, 94.8%, and 92%; ICC 93%, 92.7%, and 90.2%; regression slopes 1.004, 0.974, and 1.031; mean bias 5.54%, 10.91%, and 0.36%; and ROC-AUC estimates 0.903, 0.906, and 0.890 respectively. Agreement was maintained when adjusted for sex, age, diagnosis, liver fat content, and fat-water swap. Inline R2*-LIC provides robust and comparable quantification of LIC compared to FerriScan, without the need for offline post-processing. • In patients being treated for iron overload with chelation therapy, liver iron concentration (LIC) is regularly assessed in order to monitor and adjust therapy. • Magnetic resonance imaging (MRI) is commonly used to quantify LIC. Several R2 and R2* methods are available, all of which require offline post-processing. • A novel R2* MRI method allows for immediate calculation of LIC and provides comparable quantification of LIC to the FerriScan and recently published alternative R2* methods.

Correlation Between Serum Ferritin and Viral Hepatitis in Thalassemia Patients

Serum ferritin is an acute phase protein; importantly, its level is noticeably increased in response to iron overload and systemic inflammation. The iron overload status in thalassemia patients has been recognized as a potential way to measure liver iron concentration (LIC) levels using magnetic resonance imaging (MRI). The aim of this study was to investigate the effect of chronic viral hepatitis on the level of serum ferritin in patients with thalassemia. A cross-sectional study was conducted involving chronic viral hepatitis infection. Mean serum ferritin and LIC levels were recorded. The LIC values were used to divide the patients into two groups; a higher LIC group (>5 mg Fe/g) and a lower LIC group (<5 mg Fe/g). Mean serum ferritin levels were then compared between the two LIC groups. We identified 32 thalassemia patients comprising of 13 chronic viral hepatitis patients, seven patients with hepatitis B virus (HBV), and six patients with hepatitis C virus (HCV). With regard to the group with higher LIC values, the mean serum ferritin levels in the hepatitis group were significantly higher than for those in the non hepatitis group (1776 ± 488 vs. 967 ± 860 ng/mL, p = 0.03). Furthermore, the linear correlation between the mean serum ferritin levels and the viral load in the non transfusion-dependent thalassemia (NTDT) group were found to be significantly correlated (r = 0.7, p = 0.04). Chronic viral hepatitis was determined to be a possible casualty of disproportionately high ferritin levels in the NTDT group.

Value of liver iron concentration in healthy volunteers assessed by MRI

Iron overload is a relatively common clinical condition resulting from disorders such as hereditary hemochromatosis, thalassemia, sickle cell disease, and myelodysplasia that can lead to progressive fibrosis and eventually cirrhosis of the liver. Therefore, it is essential to recognize the disease process at the earliest stage. Liver biopsy is the reference test for the assessment of liver fibrosis. It also allows for quantifying liver iron concentration (LIC) in patients. However, this is an invasive method with significant limitations and possible risks. Magnetic resonance imaging (MRI) and evaluation of the R2* relaxation rate can be an alternative to biopsy for assessing LIC. However, it causes a need for accurate R2* data corresponding to standard value for further comparison with examined patients. This study aimed to assess the normative values of liver R2* in healthy individuals. A total of 100 volunteers that met established criteria were enrolled in the study: 36 (36%) men and 64 (64%) women. The mean age was 22.9 years (range 20 to 32 years). R2* was estimated by an MRI exam with a 1.5 T clinical magnetic resonance scanner. Images for measuring the LIC and liver fat concentration were obtained using the IDEAL-IQ technique for liver imaging. The Mean (SD) liver R2* was 28.34 (2.25) s−1 (95% CI, 27.78–28.90, range 23.67–33.00 s−1) in females, 29.57 (3.20) s−1 (95% CI, 28.49–30.66, range 23.93–37.77 s−1) in males, and 28.72 (2.69) s−1 (range 23.67–37.77 s−1) in the whole group. R2* value in this particular population with a high proportion of young women did not exceed 38 s−1. In the absence of fibrosis or steatosis, liver stiffness and fat fraction did not show any relationship with R2*.

Channel width optimized neural networks for liver and vessel segmentation in liver iron quantification

IntroductionMRI T2* relaxometry protocols are often used for Liver Iron Quantification in patients with hemochromatosis. Several methods exist to semi-automatically segment parenchyma and exclude vessels for this calculation. PurposeTo determine if inclusion of multiple echoes inputs to Convolutional Neural Networks (CNN) improves automated liver and vessel segmentation in MRI T2* relaxometry protocols and to determine if the resultant segmentations agree with manual segmentations for liver iron quantification analysis. MethodsMulti echo Gradient Recalled Echo (GRE) MRI sequence for T2* relaxometry was performed for 79 exams on 31 patients with hemochromatosis for iron quantification analysis. 275 axial liver slices were manually segmented as ground truth masks. A batch normalized U-Net with variable input width to incorporate multiple echoes is used for segmentation, using DICE as the accuracy metric. ANOVA is used to evaluate significance of channel width changes in segmentation accuracy. Linear regression is used to model the relationship of channel width on segmentation accuracy. Liver segmentations are applied to relaxometry data to calculate liver T2* yielding liver iron concentration(LIC) derived from literature based calibration curves. Manual and CNN based LIC values are compared with Pearson correlation. Bland altman plots are used to visualize differences between manual and CNN based LIC values. ResultsPerformance metrics are tested on 55 hold out slices. Linear regression indicates that there is a monotonic increase of DICE with increasing channel depth (p = 0.001) with a slope of 3.61e-3. ANOVA indicates a significant increase segmentation accuracy over single channel starting at 3 channels. Incorporation of all channels results in an average DICE of 0.86, an average increase of 0.07 over single channel. The calculated LIC from CNN segmented livers agrees well with manual segmentation (R = 0.998, slope = 0.914, p«0.001), with an average absolute difference 0.27 ± 0.99 mg Fe/g or 1.34 ± 4.3%. ConclusionMore input echoes yields higher model accuracy until the noise floor. Echos beyond the first three echo times in GRE based T2* relaxometry do not contribute significant information for segmentation of liver for LIC calculation. Deep learning models with three channel width allow for generalization of model to protocols of more than three echoes, effectively a universal requirement for relaxometry. Deep learning segmentations achieve a good accuracy compared with manual segmentations with minimal preprocessing. Liver iron values calculated from hand segmented liver and Neural network segmented liver were not statistically different from each other.

Evaluating the Volumetric Liver Fat Fraction in Patients Referred for Investigation of Hyperferritinemia

Introduction Elevated serum ferritin (hyperferritinemia, HF) can result from increased iron load, increased inflammation or from liver damage. In the most common forms of hereditary hemochromatosis (HH), elevated ferritin is usually seen with elevated transferrin saturations, [1,2]. In patients with HF but without raised liver iron concentration (LIC, mg/g dry wt [dw]), increased liver fat (hepatic steatosis, HS), either in isolation or as part of a metabolic syndrome, needs to be considered. HS is important to identify as it may progress to chronic liver damage and is potentially reversible with lifestyle interventions. Hepatic fat can now be quantified with magnetic resonance imaging (Hepafat-Scan®)[3]. Here, we evaluate the usefulness of this method in the diagnosis and subsequent management of patients referred with HF. Methods A total of 132 patients (median age 48 years, range 21-86 ; female: male ratio 1:2.5) referred for investigation of HF and who underwent estimation of liver iron concentration (LIC) by R2-MRI (FerriScan®) over a four-year period (January 2015 - December 2018) are included in this analysis. Data on patient demographics, presenting serum ferritin (SF) and transferrin saturation were obtained. Genetic testing for C282Y and H63D was also performed. Genetic testing for rarer forms of haemochromatosis was confined to patients with unexplained raised LIC. Patients with iron overload secondary to chronic iron ingestion or blood transfusion were excluded from this analysis. Results Patients were subdivided by genetic diagnosis: C282Y homozygote (26, 19.7%), C282Y/H63D (18, 13.6%), H63D homozygote (10, 7.6%), C282Y heterozygote (8, 6.1%), H63D heterozygote (18, 13.6%), autosomal dominant ferroportin disease (4, 3%) and negative HFE gene testing (48, 36.4%). There was no statistical difference between mean presenting SF (p= 0.307) between the different groups. C282Y homozygotes, and those with autosomal ferroportin disease had a significantly higher LIC than others (p&amp;lt;0.001). C282Y homozygotes and compound heterozygotes had a significantly higher transferrin saturation than other groups (p&amp;lt;0.001). SF positively correlated with LIC (p&amp;lt;0.001). After genetic testing and LIC quantification, 32 patients underwent a HepaFat-Scan®. Median age was 63 years, range 23 - 74 years; female: male ratio 1:3.5. 54.5% had a volumetric liver fat fraction (VLFF) &amp;gt; 5%. 7.4% of patients, who did not undergo Hepafat-Scan®, had HS based on sonographic findings. Patients with definitive evidence of HS as defined by VLFF &amp;gt;5% had mean LIC of 1.36mg/g dw, and a higher mean presenting SF of 926 µg/L than those with HS &amp;lt;5% (NS, p= 0.47). Those with VLFF &amp;lt;5% had a mean presenting SF of 783 mg/ml and mean LIC of 2.2 mg/g dw. In patients with LIC ≤3mg/g dw (n= 91, mean 1.6), mean presenting SF was 728 mg/ml. 28 of these patients went onto have a Hepafat-Scan®, 16 of which (57.1%) had confirmed steatosis with VLFF &amp;gt;5%. In patients with LIC &amp;gt;3mg/g dw (n= 41, mean LIC 6.9), mean presenting SF was significantly higher at 1056 mg/ml (p=0.021). 4 patients with LIC &amp;gt;3mg/g dw also had a Hepafat-Scan®, with 1 patient having VLFF &amp;gt;5%. Patients with confirmed steatosis were referred for specialist hepatology consultation. Conclusion In patients referred for investigation of HF, demonstrable steatosis (VLFF &amp;gt;5%) by Hepafat-Scan® is remarkably high (13.3% of all referred patients and 54% of patients who received Hepafat-Scan®). The Hepafat-Scan® data show that HS is generally confined to patients with low LIC (≤3mg/g dw) (Figure 1) reflecting the selective decision pathway adopted of excluding hepatic siderosis before proceeding to Hepafat-Scan®. SF is significantly higher in non-iron overloaded patients with HS (VLFF &amp;gt;5%) than those without HS (Figure 1). Estimation of HS should be considered in the diagnostic pathway of patients referred for investigation of HF, particularly when LIC values are not found to be meaningfully increased.

Correlation between Changes in Cardiac Iron and Hepatic Iron in Pediatric Patients with Thalassemia Major

Introduction. A prospective magnetic resonance imaging (MRI) study demonstrated a good control of myocardial iron overload (MIO) in terms of prevention and treatment in children with thalassemia major (TM). The aim of the present study was to evaluate if changes in MIO were related to baseline hepatic iron or changes in hepatic iron overload (HIO). Methods. We considered 68 TM patients enrolled in the MIOT (Myocardial Iron Overload in Thalassemia) project with less than 18 years at the first MRI scan and who performed a follow-up (FU) study at 18±3 months. Myocardial and hepatic iron burdens were quantified by the T2* technique. The value of 20 ms was used as conservative normal value for the global T2* value. Liver T2* values were converted into liver iron concentration (LIC) values. A LIC&lt;3 mg/g/dw indicated significant no HIO, between 3 and 7 mg/g/dw mild HIO, between 7 and 15 mg/g/dw moderate HIO, and ≥15 mg/g/dw severe HIO. Results. Thirty-six patients were females and mean age at the time of the baseline MRI was 13.74±3.09 years. Baseline global heart T2* values were 29.72±11.21 ms and 16 (23.5%) patients showed significant baseline MIO. The percentage changes in global heart T2* values per month in the whole patient population were 0.66±1.70 and they resulted significantly higher in the 16 patients with significant baseline MIO versus the patients with no baseline MIO (1.99±2.53% vs 0.25±1.09% ms; P=0.002). Percentage changes in global heart T2* values per month were not influenced by initial MRI LIC values (R=0.048; P=0.695) (Figure 1A) and were comparable among the 4 groups of patients identified on the basis of baseline MRI LIC values (14 no HIO: 0.29±1.12% vs 21 mild HIO: 0.75±1.56% vs 15 moderate HIO: 0.82±2.03% vs 18 severe HIO: 0.71±2.00%; P=0.876). Percentage changes in global heart T2* values per month were not associated to final MRI LIC values (R=-0.134; P=0.277) (Figure 1B). The correlation between % changes in global heart T2* and MRI LIC values did not reach the statistical significance (R=-0.244; P=0.067) (Figure 1C). In patients with baseline MIO no correlation was found between % changes in global heart T2* values per month and initial MRI LIC values (R=-0.325; P=0.219) or % changes in MRI LIC values per month (R=-0.353; P=0.180). Conclusion. In pediatric TM patients changes in cardiac iron are not correlated to baseline MRI LIC values and changes in hepatic iron. So, our data seem not supporting the hypothesis for which it is necessary to clean the liver before removing iron from the heart. Figure 1 Disclosures Pepe: Chiesi Farmaceutici S.p.A., ApoPharma Inc., and Bayer: Other: No profit support.

Uncertainty in the R2 Calibration Curve for High Iron Concentration

Introduction: MRI assessment of liver iron concentration (LIC) has become the standard of care for monitoring iron chelation strategies. The Ferriscan R2 quantification of LIC has been validated against 338 biopsies in two large cohorts, demonstrates good interstudy reproducibility, and has strong quality control practices. However, its cost remains a challenge for many institutions, making iron measurements by R2* acquisitions more attractive. Several studies comparing LIC by R2* and by Ferriscan R2 have identified substantial bias between R2* and R2 LIC estimates. We postulated that the original Ferriscan R2 calibration overestimates LIC at high iron concentrations, causing the disagreement between the two techniques. Methods: We identified three studies comparing single echo R2 to liver biopsy (362 biopsies). We used a publicly available digital capture program(www.arizona-software.ch/graphclick) to capture the values of R2 for each liver iron concentration level. We fit the data to the existing FDA-approved calibration and compared Bland Altman agreement to liver biopsy against two other calibration curves. The first was data-derived from the aggregate liver biopsy results using a linear fit in log transformed LIC and R2 coordinates (resulting in a Power Law fit). The second was derived from a spline fit to data generated from previously published Monte Carlo simulation model from our laboratory. This model generates "synthetic" R2-iron pairs over the entire physiological range of iron overload, using ideal mathematical approximations to the MRI imaging physics. Results: Panel A demonstrates R2-LIC pairs for the aggregate liver biopsy data and the three evaluated R2-iron calibration curves. Using Bland-Altman analysis, both the Power Law (0.5 ± 4.9 mg/g) and Simulation (1.7 ± 5.1 mg/g) calibrations had 17-22% lower variance than the Ferriscan calibration (-1.1 ± 6.2 mg/g), p&amp;lt;0.0001 by two sample variance test. More importantly, the predicted LIC values diverge dramatically for R2 values greater than 155 Hz (roughly 14 mg/g) (Panel B). For example, a R2 value of 300 Hz will yield an estimated LIC of 48 mg/g by Ferriscan but only 34 mg/g and 32.5 mg/g by the Power Law and Simulation calibrations respectively. Discussion: These data suggest that Ferriscan overestimates true liver iron concentration for R2 values exceeding 155 Hz, with the differences growing geometrically. The calibration error is sufficient to completely explain the differences between LIC by R2* and Ferriscan R2 described in previously studies. Importantly, any future attempt to "calibrate" R2* or other MRI methods against Ferriscan need to account for this bias. Fortunately, the clinical impact of the observed calibration bias is manageable. Patients with LIC below 14 mg/g are being accurately risk stratified. Patients with LIC greater than 14 mg/g in their liver are universally at high risk and should be treated aggressively, regardless. Serial trends in LIC-R2 values also lessen the impact of calibration bias. Both Ferriscan and R2* LIC estimates and provide accurate estimates of chelator efficiency on an annual basis. Further, both Ferriscan and liver R2* LIC estimates are more accurate than liver biopsy in tracking changes in total body iron concentration. However, hematologists should treat Ferriscan predicted LIC values of more than 14 mg/g with appropriate caution and integrate the predicted LIC values with the patient's entire clinical picture to avoid over-reacting to large changes in predicted LIC. ACKNOWLEDGEMENTS This work supported by the National Institutes of Health, Diabetes, Digestive and Kidney Diseases (1R01DK097115-01A1). DISCLOSURES Dr. Wood serves as a consultant to Apopharma, Biomedinformatics, Bluebirdbio, Celgene, Ionis Pharmaceuticals, Imago Biosciences, Silence Therapeutics, and World Care Clinical. Figure Disclosures Wood: National Institutes of Health: Research Funding; Celgene: Consultancy; Apopharma: Consultancy; WorldcareClinical: Consultancy; BluebirdBio: Consultancy; Imago Biosciences: Consultancy; BiomedInformatics: Consultancy; Philips Healthcare: Research Funding. Coates:celgene: Consultancy, Honoraria, Other: steering committee of clinical study; vifor: Consultancy, Honoraria; apo pharma: Consultancy, Honoraria, Speakers Bureau; agios pharma: Consultancy, Honoraria.

Non Invasive Evaluation of Hepatic Iron Concentration By Fibroscan in Transfusion-Dependent Egyptian Patients with Chronic Hemolytic Anemia

Background: Transient elastography (Fibroscan®) is an ultrasound technique used to measure liver stiffness (LS), and thus assess for liver fibrosis, in patients with various chronic hepatic disorders. It can also be used to predict severity in multiple other diseases that might affect LS such as amyloidosis and possibly conditions associated with iron overload.Objectives: To assess the frequency of liver fibrosis in patients with chronic hemolytic anemia using Transient elastography (Fibroscan®), and to determine the reliability of this tool as a non-invasive method to predict hepatic iron content as compared to liver iron concentration (LIC) measured by magnetic resonance imaging (MRI).Patients and methods: Seventy-five transfusion dependent patients (50 β-thalassemia major;25 sickle cell disease) with a mean age of 13.4±5.2 years in addition to 75 -age and sex matched- healthy children were recruited. All subjects underwent assessment of LS in kilopascals (kPa), by Transient elastography measurement using FibroScan (Echosens, Paris, France І). Steady state serum ferritin (SF), and hepatitis B serologies (HBsAg and antiHB core antibodies) were assessed by enzyme linked immunoassay (ELISA). LIC values, within 6 months' duration, as identified by quantitative MRI of hepatic iron stores as a signal intensity ratio method based on T1 and T2* contrast imaging without gadolinium were retrieved. Informed consent was obtained from patients' legal guardians prior to enrollment in the study.Results: The median SF was 2280 ng/ml (84% had values exceeding 1000 ng/ml). The median LIC was 13.86 mg/g dw (78.7% patients showed LIC above 7 mg/g dw). The median cardiac T2* was 30.8 ms (3 patients had values below 20). Fifty-two (69.3%) patients were categorized as F0-1 and 21 (28%) were stage F2, 2 (1.3%) were stage F3, and 2 patients had severe fibrosis. The mean and median fibroscan (FS) values were 6.19 ±1.76 kPa and 5.9 kPa (range 3 to 14.1) respectively. Patients had significantly higher mean FS compared to control group (p ˂0.001). Patients with no or mild fibrosis (F0-1) had lower FS values (5.3kPa) compared to patients with fibrosis grades 2-4 (p ˂0.001). FS values were not affected by disease type (thalassemia or sickle cell disease), age (above 12 years), or HCV sero-positivity. FS values correlated with SF (r=0.410, p˂ 0.001). Simple regression analysis of the two variables suggested that changes in SF were associated with minimal but significant changes in FS values (p=0.04) with good agreement (kappa =0.324, p=0.003). LIC did not differ in relation to grade of fibrosis (p>0.05), did not correlate with FS values (r= 0.014, p=0.908), and no changes in FS were expected with LIC changes on regression analysis (p=0.466) with low agreement between LIC and FS at cutoff value 5.3 kPa (kappa = 0.015, p=0.9). Sensitivity and specificity of FS values to predict LIC were high at cutoff values ranging between 3.2 to 3.75 kPa but decreased markedly at higher cutoff values. On comparing sensitivity and specificity of FS values in prediction of iron overload at different cutoff values by ROC curve, it could not significantly predict iron overload (p=0.7). No correlations were found between LIC and other variables including SF (r=0.2), and changes in SF were not significantly associated with changes in LIC values (p =0.089). However, sensitivity and specificity of SF in predicting LIC were good at cutoff 1003.85 ng/ml but decreased markedly at higher cutoff values. Comparing its sensitivity and specificity to that of SF in the prediction of iron overload at different cutoff values by ROC curve, FS could not predict iron overload accurately (p=0.9) and the degree of agreement between these two variables as indicators of iron overload was low (kappa=0.063, p=0.478).Conclusion: Fibroscan could be a valuable tool to assess the degree of liver fibrosis in patients with elevated SF, but it does not appear to reliably predict LIC in such group of patients especially with severe iron overload. FS values were not affected by disease type, age above 12 years, or HCV sero-positivity. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.