Liver MRI is more precise than liver biopsy for assessing total body iron balance: a comparison of MRI relaxometry with simulated liver biopsy results

Abstract Introduction Liver iron concentration (LIC) represents the best surrogate of total body iron balance for guiding iron chelation therapy. Liver biopsy was formerly used to determine LIC, but has gradually been replaced by magnetic resonance imaging (MRI) relaxometry because relaxometry is noninvasive and has lower sampling variability. Since neither liver biopsy nor MRI relaxometry can be considered a “gold standard”, there is a need for an independent mechanism to validate their accuracy and reproducibility. In this study, we use serial estimates of iron chelation efficiency calculated by R2 and R2* MRI as well as simulated liver biopsy results to demonstrate that MRI is fundamentally more accurate that liver biopsy in determining iron balance. Methods All patients were participating in a phase 2 clinical trial of SPD602 (formerly known as FBS0701) and had strict documentation of iron chelator and blood intake. MRI R2 and R2* LIC estimates were performed at baseline, 12, 24, 48, 72, and 96 weeks. Forty-nine patients completed 24 weeks, 39 completed 48 weeks, and 26 completed 96 weeks of the trial. Liver biopsy LIC results were simulated (by Monte Carlo simulation) using sampling errors having a coefficient of variation (CoV) of 0%, 10%, 20%, 30%, and 40%, and iron assay variability of 12%. LIC estimates by R2, R2*, and simulated biopsy were used to calculate chelation efficiency estimates over time. Bland–Altman limits of agreement were compared across observation timescales of 12, 24, and 48 weeks. Results Table 1 summarizes the standard deviation for chelation efficiency estimates performed at 12, 24, and 48 week intervals. For 48 week intervals, R2, R2*, and “perfect” liver biopsy exhibited statistically identical variance (indicated by italic type), and were superior to any “realistic” sampling error for liver biopsy (CoV 10–40%). At shorter measurement intervals, R2* produced the lowest variance estimates. For 12 week intervals, R2* efficiency estimates were confounded by two outliers; exclusion of these two points reduced the standard deviation of 12 week R2* efficiency estimates to 15.6% (p < 0.01). Figure 1 (top row) demonstrates simulated efficiency estimates by “perfect” liver biopsy performed on 12, 24, and 48 week timescales. While “perfect” liver biopsy approaches ideal behavior at 48 week intervals, many non-physiologic estimates (> 100%, < 0%) are produced during shorter term observations. Figure 1 (middle and bottom row) compares the identical relationships for chelation efficiency estimates generated by R2 and R2*, respectively. R2 demonstrates similar scatter as observed for liver biopsy. R2* efficiency estimates are better, with a slope near unity and all points residing in the upper right hand quadrant for 24 and 48 week timescales. Thus both R2 and R2* produce chelation efficiency estimates at least as good as “perfect” liver biopsy and better than biopsy performed with any reasonable estimate of sampling variability. Discussion Even if liver biopsy is assumed to have no sampling variation, which is unrealistic in clinical practice, MRI relaxometry is superior for tracking of total body iron balance. R2 and R2* are equally robust on annual evaluations, but R2* more closely tracks iron balance on shorter timescales. We conclude that MRI relaxometry should replace liver biopsy for the determination of LIC for both clinical and regulatory purposes. Disclosures: Wood: Shire: Consultancy, Research Funding; Apopharma: Honoraria, Patents & Royalties; Novartis: Honoraria. Zhang:Shire: Employment. Rienhoff:Shire: Consultancy, Milestone Payments Other. Abi-Saab:Shire: Employment, Equity Ownership, Patents & Royalties; AbbVie: Equity Ownership, Patents & Royalties; Novartis: Equity Ownership, Patents & Royalties; Abbott: Equity Ownership, Patents & Royalties; Pfizer: Equity Ownership, Patents & Royalties. Neufeld:Shire: Consultancy.

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A study of the iron requirement in infants, using changes in total body iron determined by hemoglobin, serum ferritin and bodyweight

Pediatrics International ◽

10.1111/j.1442-200x.1994.tb03152.x ◽

1994 ◽

Vol 36 (2) ◽

pp. 153-155 ◽

Cited By ~ 4

Author(s):

TOMIKO HOKAMA

Keyword(s):

Serum Ferritin ◽

Body Iron ◽

Iron Requirement ◽

Total Body

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Hepatic iron concentration and total body iron burden in genetic hemochromatosis (GH)

Journal of Hepatology ◽

10.1016/0168-8278(91)91183-h ◽

1991 ◽

Vol 13 ◽

pp. S49

Author(s):

C. Mandelli ◽

L. Cesarini ◽

A. Pipemo ◽

S. Fargion ◽

A.L. Fracanzani ◽

...

Keyword(s):

Iron Concentration ◽

Hepatic Iron ◽

Body Iron ◽

Total Body ◽

Hepatic Iron Concentration ◽

Genetic Hemochromatosis

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Two types of hepatic iron overload in patients with genetic hemochromatosis (GH): Linear and non-linear relationship with total body iron stores

Hepatology ◽

10.1016/0270-9139(93)92617-9 ◽

1993 ◽

Vol 18 (4) ◽

pp. A273

Author(s):

J OLYNYK

Keyword(s):

Iron Overload ◽

Linear Relationship ◽

Hepatic Iron ◽

Body Iron ◽

Iron Stores ◽

Hepatic Iron Overload ◽

Non Linear ◽

Total Body ◽

Genetic Hemochromatosis

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Association of Iron Storage Markers with Metabolic Syndrome and Its Components in Chinese Rural 6–12 Years Old Children: The 2010–2012 China National Nutrition and Health Survey

Nutrients ◽

10.3390/nu12051486 ◽

2020 ◽

Vol 12 (5) ◽

pp. 1486 ◽

Cited By ~ 1

Author(s):

Huidi Zhang ◽

Lijuan Wang ◽

Siran Li ◽

Xiaobing Liu ◽

Yuqian Li ◽

...

Keyword(s):

Metabolic Syndrome ◽

Health Survey ◽

Whole Blood ◽

Multivariate Logistic Regression Analysis ◽

Density Lipoprotein ◽

Nutrition And Health ◽

Iron Storage ◽

Body Iron ◽

Total Body ◽

The Relationship

Background: Elevated ferritin, which is often used to represent iron storage, is known to increase the risk of metabolic syndrome (MetS) or its components, but its increase is affected by many factors. Therefore, it is necessary to analyze the relationship between other indicators of iron storage, and MetS and its components in order to fully understand the role of iron in the occurrence and development of these diseases. Although there are many studies to analyze the relationship involved in adults and adolescents, in children there is limited research. In this study, we aim to estimate the association of whole blood iron, ferritin, and total body iron with metabolic syndrome, and especially its components in Chinese rural children aged 6–12 years old. Method: A total of 1333 children aged 6–12 years old were enrolled from the 2010–2012 China National Nutrition and Health Survey in this study. Markers of iron storage (whole blood iron, ferritin, and total body iron (TBI)) and MetS component parameters (waist, blood pressure, high-density lipoprotein cholesterol (HDL-C), triglyceride (TG), and fast glycose) were collected. A multivariate logistic regression analysis was performed to confirm the independent relationship between iron storage markers, and the incident of metabolic syndrome and its components. Results: After adjusting for age, gender, C-reactive protein (CRP), and body mass index (BMI), a negative association was found between whole blood iron, ferritin, and TBI and incidence of reduced HDL-C (odds ratio (OR) = 0.63, 0.49, and 0.57, respectively). The highest tertile of whole blood iron increased the risk of the incidence of hyperglycemia (OR = 1.74), while TBI decreased the risk by 61%. No significant association was found between ferritin tertiles and the incidence of hyperglycemia. Conclusion: An iron storage level within the normal range in children is associated with a risk of MetS components, especially in hyperglycemia and reduced HDL-C. The relationship between the three iron indexes and metabolic syndrome and its components is not completely consistent, which suggests that the underlying mechanism is complex and needs to be further explored.

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Iron management in renal anaemia

10.1093/med/9780199592548.003.0126 ◽

2015 ◽

Author(s):

Iain C. Macdougall

Keyword(s):

Bone Marrow ◽

Iron Status ◽

Transferrin Saturation ◽

Intravenous Route ◽

Iron Release ◽

Renal Anaemia ◽

Body Iron ◽

Iron Stores ◽

Iv Iron ◽

Total Body

Although erythropoiesis-stimulating agent therapy is the mainstay of renal anaemia management, maintenance of an adequate iron supply to the bone marrow is also pivotal in the process of erythropoiesis. Thus, it is important to be able to detect iron insufficiency, and to treat this appropriately. Iron deficiency may be absolute (when the total body iron stores are exhausted) or functional (when the total body iron stores are normal or increased, but there is an inability to release iron from the stores rapidly enough to provide a ready supply of iron to the bone marrow). Several markers of iron status have been tested, but those of the greatest utility are the serum ferritin, transferrin saturation, and percentage of hypochromic red cells. Measurement of serum hepcidin, which is the master regulator of iron homoeostasis, has to date proved disappointing as a means of detecting iron insufficiency, and none of the available iron markers reliably exclude the need for supplemental iron. Iron may be replaced by either the oral or the intravenous route. In the advanced stages of chronic kidney disease, however, hepcidin is upregulated, and this powerfully inhibits the absorption of iron from the gut. Thus, such patients often require intravenous iron, particularly those on dialysis. Several intravenous (IV) iron preparations are available, and they have in common a core containing an iron salt, surrounded by a carbohydrate shell. The IV iron preparations differ in their kinetics of iron release from the iron–carbohydrate complex. In recent times, several new IV iron preparations have become available, and these allow a greater amount of iron to be given more rapidly as a single administration, without the need for a test dose.

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Liver Iron Concentration Estimates by R2* Are More Robust Than by Ferriscan During Rapid Changes in Iron Burden

Blood ◽

10.1182/blood.v118.21.5296.5296 ◽

2011 ◽

Vol 118 (21) ◽

pp. 5296-5296

Author(s):

John C Wood ◽

Amber Jones ◽

Hugh Y Rienhoff ◽

Ellis J. Neufeld

Keyword(s):

Liver Biopsy ◽

Research Funding ◽

Iron Concentration ◽

Drug Consumption ◽

Dose Titration ◽

Outcome Variable ◽

Gradient Echo ◽

Liver Iron ◽

Body Iron ◽

Tissue Iron

Abstract Abstract 5296 Introduction: MRI assessment of LIC concentration is increasing utilized as the primary outcome variable of clinical trials for iron chelation. The MRI parameters R2 and R2* can both be used for this purpose but have slightly different sensitivities to the scale and distribution of tissue iron deposits. As a result, these techniques may provide significantly disparate results in any given patient and may diverge following abrupt changes in chelation therapy. It is not practical, nor ethical, to use liver biopsy to validate R2 and R2* LIC measures on a short time scale. Thus, we used calculations of chelator molar efficiency to determine whether predicted changes in LIC were consistent with the known iron balance assessed by transfusional burden and drug consumption. Methods: The Phase II trial of FBS701, a novel oral iron chelator, measured LIC by both R2 and R2* at screening, 12 weeks, and 24 weeks of therapy; nine thalassemia centers participated in 7 countries. 51 individuals completed 24 weeks of treatment. Liver R2 was collected and analyzed using a FDA-approved protocol and a commercial vendor (Ferriscan Resonance Health, Australia). Liver R2* was measured using gradient echo sequences with minimum echo times ranging from 1.0–1.2 ms. All gradient echo images were transferred to a central core laboratory for R2* calculation using a three component decay model (exponential + offset). Only patients with LIC values between 3 and 30 mg/g by Ferriscan LIC were allowed to participate. Transfusional iron burden was calculated from transfusional volumes documented for six months prior to entering the study and corrected for hematocrit. Change in total body iron was calculated using the Angelucci equation. Chelator efficiency was calculated using the net change in body iron concentration by drug consumption, calculated on a molar basis, to yield a unit-less number; drug concentration was divided by two to account for the chelator-iron stoichiometry. Observed changes in LIC were judged to be erroneous if they produced an estimated chelator efficiency greater than one or less than zero. We also assume that the efficiency between 0–12 weeks and 12–24 weeks should be comparable; the variance between these two values was used as an independent metric of Ferriscan, robustness for LIC measurement. Results: Figure 1 demonstrates the calculated chelator efficiency from 12–24 weeks versus 0–12 weeks, using LIC values calculated by Ferriscan(open circles) and by R2* (solid dots). The solid line indicates the line of identity and the inset box represents the physiologically possible range. 19/95 Ferriscan LIC measurements were physiologically impossible compared with 5/95 R2* LIC measurements (p=0.004 by Fischer's exact test). Ferriscan 12–24 week efficiency measurements were uncorrelated with Ferriscan 0–12 week measurements and generally strayed a greater distance from the line of identity, with a three-fold larger mean-squared error (0.375 versus 0.126) than for efficiencies calculated using R2*. Discussion: Both R2 and R2* are biopsy-validated, clinically accepted tools for noninvasive LIC estimation and can be used to track liver iron on a long-term basis. However, the ability of these techniques to accurately track short-term changes (below 1 year) has never been studied; such changes may be important for rapid dose-titration. In this study, Ferriscan LIC estimates were inconsistent with measured iron-balance, producing many nonphysiologic estimates of chelator efficiency and poor consistency between observations at three-month intervals. It is not known whether this represents an intrinsic property of R2 measurements, caused by undue sensitivity to microscopic iron particle distribution, or a limitation specific to the Ferriscan processing. However, given the previously published success of the Ferriscan technique with respect to liver biopsy when assessed on longer time-scales, we believe that these data represent a disequilibrium phenomenon, i.e., that R2 measurements are transiently inaccurate following an abrupt chelation change. Longer-term studies will be necessary to test this hypothesis. Nonetheless, caution should be used in trying to interpret Ferriscan results at intervals of six months or less. R2* LIC measurements are intrinsically less sensitive to changes in tissue iron distribution and more accurate reflections of iron balance at shorter time intervals. Disclosures: Wood: Novartis: Research Funding; Ferrokin Biosciences: Consultancy; Cooleys Anemia Foundation: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Jones:Ferrokin BioSciences: Employment. Rienhoff:Ferrokin BioSciences: Employment, Equity Ownership. Neufeld:Ferrokin BioSciences: Research Funding; Novartis: Research Funding.

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Effect Of Maternal Cigarette Smoking On Newborn Iron Stores

Blood ◽

10.1182/blood.v122.21.4671.4671 ◽

2013 ◽

Vol 122 (21) ◽

pp. 4671-4671 ◽

Cited By ~ 1

Author(s):

Irina Pateva ◽

Elisabeth Kerling ◽

Susan Carlson ◽

Manju Reddy ◽

Dan Chen ◽

...

Keyword(s):

Birth Weight ◽

Conflicts Of Interest ◽

Smoking Status ◽

Newborn Infants ◽

Significant Negative Correlation ◽

Matched Pair ◽

Small Scale ◽

Body Iron ◽

Iron Stores ◽

Total Body

Objective Previous small-scale studies suggest that maternal smoking lowers neonatal body iron. Our objective was to study and compare the relationship between maternal and infants’ body iron in smokers and non-smokers in a large matched-pair cohort. Method This was a prospective cohort study involving 144 mothers – 72 smokers and 72 non-smokers and their respective infants. Samples were obtained from maternal blood and infants’ cord blood at delivery for serum transferrin receptor (sTfR) and ferritin levels. Serum TfR and ferritin levels were measured by RAMCO ELISA and RIA assays. The total body iron (TBI) was calculated using the sTfR/ferritin ratio. Results Maternal total body iron and smoking status Women who smoked had lower sTfR, higher ferritin and higher body iron compared to nonsmoking women. Infant’s total body iron, measurements at birth and smoking status In contrast to their respective mothers, we found a small but statistically significant negative correlation between smoking and infants’ total body iron. The number of PPD smoked was negatively correlated with infants’ ferritin and total body iron. The number of days smoked during pregnancy was also negatively correlated with infants’ ferritin and total body iron and positively correlated with infants' sTfR. Birth weight was lower in babies of smokers compared to nonsmokers (mean /- SD =3270 +/-475 vs. 3393 g +/- 475 g, p=0.03). Correlation studies revealed that birth weight in infants of smokers was negatively correlated with PPD smoked and number of days smoked. Birth length in the same infants was also negatively correlated with PPD smoked and number of days smoked. Conclusion Mothers who smoked during pregnancy had higher iron stores but their newborn infants had lower iron stores than those of non-smoking mothers. There may be a negative dose-dependent response between fetal smoke exposure and infant iron stores. Disclosures: No relevant conflicts of interest to declare.

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