Value of liver iron concentration in healthy volunteers assessed by MRI

Correlation between plasma biochemical parameters and cardio-hepatic iron deposition in thalassemia major patients

INTRODUCTION

Major Thalassemia patients suffer from iron overload and organ damage, especially heart and liver damage. Early diagnosis and treatment with a chelator can reduce the complications and mortality of iron overload. Therefore, we aimed to investigate the biochemical and hematological predictors as an alternative and indirect indicator of iron deposition in heart and liver cells in comparison with the MRI T2* method as the gold standard.

MATERIAL AND METHOD

MRI T2* was evaluated in the heart and liver tissues of 62 major beta-thalassemia patients undergoing regular transfusion and chelator therapy. Biochemical and hematological factors were also measured, including serum ferritin, serum electrolytes, liver enzymes, hemoglobin, blood glucose, and serum magnesium. The correlation between these factors was assessed using statistical evaluations.

RESULT

Serum ferritin had a positive and significant correlation with liver siderosis based on MRI T2* (p-value = .015), and no significant association was observed with cardiac siderosis (p-value = .79). However, there was a significant positive correlation between cardiac iron deposition and fasting blood sugar level (p-value = -.049), and plasma level of liver enzymes (alanine aminotransferase (ALT) (p-value = .001), aspartate aminotransferase (AST ((p-value = .01)). Moreover, there was a significant negative correlation between cardiac iron overload and plasma magnesium level (p-value = .014). According to MRI T2*, there was no significant correlation between cardiac and hepatic iron overload (p value = .36).

CONCLUSION

An increase in blood sugar or liver enzymes and a decrease in serum magnesium was associated with an increase in cardiac iron overload based on MRI T2*. Liver iron overload based on MRI T2* had a significant correlation with serum ferritin.

R2* Impact on Hepatic Fat Quantification With a Commercial Single Voxel Technique at 1.5 and 3.0 T

Rationale and Objectives: Fat quantification accuracy using a commercial single-voxel high speed T2-corrected multi-echo (HISTO) technique and its robustness to R2* variations at 3.0 T, such as those introduced by iron in liver, has not been fully established. This study evaluated HISTO at 3.0 T and sought to reproduce results at 1.5 T. Methods: Phantoms were prepared with a range of fat content and R2*. Data were acquired at 1.5 T and 3.0 T, using HISTO and a Dixon technique. Fat quantification accuracy was evaluated as a function of R2*. The patient study included 239 consecutive patients. Data were acquired at 1.5 T or 3.0 T, using HISTO and Dixon techniques. The techniques were compared using Bland-Altman plots. Bias significance was evaluated using a one-sample t-test. Results: In phantoms, HISTO was accurate within 10% up to a R2* of 100 s-1 at both field strengths, while Dixon was accurate within 10% where R2* was accurately quantified (up to 350 s-1 at 1.5 T, and 550 s-1 at 3.0 T). In patients, where R2* was <100 s-1, fat quantification from both techniques agreed at 1.5 T (P = .71), but not at 3.0 T (P = .007), with a bias <1%. Conclusion: Results suggest that HISTO is reliable when R2* is <100 s-1, corresponding to patients with at most mild liver iron overload, and that it should be used with caution when R2* is >100 s-1. Dixon should be preferred for hepatic fat quantification due to its robustness to R2* variations.

Liver Iron Overload Drives COVID-19 Mortality: a Two-Sample Mendelian Randomization Study

Iron overload has been associated with an increased risk of COVID-19 severity and mortality in observational studies, but it remains unclear whether these associations represent causal effects. We performed a two-sample Mendelian randomization (MR) to determine associations between genetic liability to iron overload and the risk of COVID-19 severity and mortality. From genome-wide association studies of European ancestry, single-nucleotide polymorphisms associated with liver iron (n = 32,858) and ferritin (n = 23,986) were selected as exposure instruments, and summary statistics of the hospitalization (n = 16,551) and mortality (n = 15,815) of COVID-19 were utilized as the outcome. We used the inverse-variance weighted (IVW) method as the primary analysis to estimate causal effects, and other alternative approaches as well as comprehensive sensitivity analysis were conducted for estimating the robustness of identified associations. Genetically predicted high liver iron levels were associated with an increased risk of COVID-19 mortality based on the results of IVW analysis (OR = 1.38, 95% CI: 1.05-1.82, P = 0.02). Likewise, sensitivity analyses showed consistent and robust results in general (all P > 0.05). A higher risk of COVID-19 hospitalization trend was also observed in patients with high liver iron levels without statistical significance. This study suggests that COVID-19 mortality might be partially driven by the iron accumulation in the liver, supporting the classification of iron overload as one of the independent death risk factors. Therefore, avoiding iron overload and maintaining normal iron levels may be a powerful measure to reduce COVID-19 mortality.

Radiomics analysis of R2* maps to predict early recurrence of single hepatocellular carcinoma after hepatectomy

Objectives

This study aimed to evaluate the effectiveness of radiomics analysis with R2* maps in predicting early recurrence (ER) in single hepatocellular carcinoma (HCC) following partial hepatectomy.

Methods

We conducted a retrospective analysis involving 202 patients with surgically confirmed single HCC having undergone preoperative magnetic resonance imaging between 2018 and 2021 at two different institutions. 126 patients from Institution 1 were assigned to the training set, and 76 patients from Institution 2 were assigned to the validation set. A least absolute shrinkage and selection operator (LASSO) regularization was conducted to operate a logistic regression, then features were identified to construct a radiomic score (Rad-score). Uni- and multi-variable tests were used to assess the correlations of clinicopathological features and Rad-score with ER. We then established a combined model encompassing the optimal Rad-score and clinical-pathological risk factors. Additionally, we formulated and validated a predictive nomogram for predicting ER in HCC. The nomogram's discrimination, calibration, and clinical utility were thoroughly evaluated.

Results

Multivariable logistic regression revealed the Rad-score, microvascular invasion (MVI), and α fetoprotein (AFP) level > 400 ng/mL as significant independent predictors of ER in HCC. We constructed a nomogram based on these significant factors. The areas under the receiver operator characteristic curve of the nomogram and precision-recall curve were 0.901 and 0.753, respectively, with an F1 score of 0.831 in the training set. These values in the validation set were 0.827, 0.659, and 0.808.

Conclusion

The nomogram that integrates the radiomic score, MVI, and AFP demonstrates high predictive efficacy for estimating the risk of ER in HCC. It facilitates personalized risk classification and therapeutic decision-making for HCC patients.

Kidney R2* Mapping for Noninvasive Evaluation of Iron Overload in Paroxysmal Nocturnal Hemoglobinuria

PURPOSE

The kidney iron deposition can cause kidney damage and renal insufficiency in paroxysmal nocturnal hemoglobinuria (PNH) patients. Assessment of iron deposition in the kidney is essential for the early diagnosis of renal damage in PNH patients. The purpose of this study was to evaluate kidney R2* (T2* reciprocals) values in PNH patients using the iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL-IQ).

METHODS

Two radiologists measured the R2* values of the renal cortex in 14 PNH patients and 13 healthy volunteers using IDEAL-IQ. Lactate dehydrogenase (LDH), a reliable marker of intravascular hemolysis, was also measured in all participants.

RESULTS

The kidney R2* values were significantly higher in PNH patients compared with those in healthy volunteers (P < 0.001). High inter-operator reproducibility of the measurements was also acquired using IDEAL-IQ. LDH levels were also significantly higher in PNH patients compared with those in healthy volunteers (P < 0.001). Kidney R2* values strongly correlated with LDH levels in PNH patients.

CONCLUSION

IDEAL-IQ has a possibility of becoming a useful method for the noninvasive evaluation of renal iron overload in PNH patients.

Radiomics nomograms based on R2* mapping and clinical biomarkers for staging of liver fibrosis in patients with chronic hepatitis B: a single-center retrospective study

OBJECTIVES

To investigate the value of R2* mapping-based radiomics nomograms in staging liver fibrosis in patients with chronic hepatitis B.

METHODS

Between January 2020 and December 2020, 151 patients with chronic hepatitis B were randomly divided into training (n = 103) and validation (n = 48) cohorts. From January to February 2021, 58 patients were included in a test cohort. Radiomics features were selected using the interclass correlation coefficient and least absolute shrinkage and selection operator method. Three radiomics nomograms, combining the radiomics score (Radscore) derived from R2* mapping and clinical variables, were used for staging significant and advanced fibrosis, and cirrhosis. Performance of the model was evaluated using the AUC. The utility and clinical benefits were evaluated using the continuous net reclassification index (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA).

RESULTS

The Radscore calculated by 12 radiomics features and independent factors (laminin and platelet) of advanced fibrosis were used to construct the radiomics nomograms. In the test cohort, the AUCs of the radiomics nomograms for staging significant fibrosis, advanced fibrosis, and cirrhosis were 0.738 (95% confidence interval [CI]: 0.604-0.872), 0.879 (95% CI: 0.779-0.98), and 0.952 (95% CI: 0.878-1), respectively. NRI, IDI, and DCA confirmed that radiomics nomograms demonstrated varying degrees of clinical benefit and improvement for advanced fibrosis and cirrhosis, but not for significant fibrosis.

CONCLUSIONS

Radiomics nomograms combined with R2* mapping-based Radscore, laminin, and platelet have value in staging advanced fibrosis and cirrhosis but limited value for staging significant fibrosis.

KEY POINTS

• Laminin and platelets were independent predictors of advanced fibrosis. • Radiomics analysis based on R2* mapping was beneficial for evaluating advanced fibrosis and cirrhosis. • It was difficult to distinguish significant fibrosis using a radiomics nomogram, which is possibly due to the complex pathological microenvironment of chronic liver diseases.

Quantifying Liver Heterogeneity via R2*-MRI with Super-Paramagnetic Iron Oxide Nanoparticles (SPION) to Characterize Liver Function and Tumor

Simple Summary

Super-paramagnetic iron oxide nanoparticles (SPIONs) are phagocytized by the hepatic Kupffer cells (KC) in the liver and shorten MRI signals within the volume of functional liver parenchyma (FLP) where KCs are found. However, malignant tumors lacking KCs exhibit minimal signal change, resulting in increasing liver heterogeneity. This study investigates whether SPIONs improve liver heterogeneity on R2*-MRI to characterize FLP and non-FLP (i.e., tumor, hepatic vessels, liver fibrosis and scarring associated with hepatic cirrhosis, prior liver-directed therapies or hepatic resection). By using SPIONs, liver heterogeneity was improved across two MRI sessions with and without an intravenous SPION injection, and the volume of FLP was identified in our auto-contouring tool. This is a desirable technique for achieving more accurate characterizations of liver function and tumors during radiation treatment planning.

Abstract

The use of super-paramagnetic iron oxide nanoparticles (SPIONs) as an MRI contrast agent (SPION-CA) can safely label hepatic macrophages and be localized within hepatic parenchyma for T2*- and R2*-MRI of the liver. To date, no study has utilized the R2*-MRI with SPIONs for quantifying liver heterogeneity to characterize functional liver parenchyma (FLP) and hepatic tumors. This study investigates whether SPIONs enhance liver heterogeneity for an auto-contouring tool to identify the voxel-wise functional liver parenchyma volume (FLPV). This was the first study to directly evaluate the impact of SPIONs on the FLPV in R2*-MRI for 12 liver cancer patients. By using SPIONs, liver heterogeneity was improved across pre- and post-SPION MRI sessions. On average, 60% of the liver [range 40–78%] was identified as the FLPV in our auto-contouring tool with a pre-determined threshold of the mean R2* of the tumor and liver. This method performed well in 10 out of 12 liver cancer patients; the remaining 2 needed a longer echo time. These results demonstrate that our contouring tool with SPIONs can facilitate the heterogeneous R2* of the liver to automatically characterize FLP. This is a desirable technique for achieving more accurate FLPV contouring during liver radiation treatment planning.

Association of Habitual Dietary Intake with Liver Iron-A Population-Based Imaging Study

Iron-related disorders of the liver can result in serious health conditions, such as liver cirrhosis. Evidence on the role of modifiable lifestyle factors like nutrition in liver iron storage is lacking. Thus, we aimed to assess the association of habitual diet with liver iron content (LIC). We investigated 303 participants from the population-based KORA-MRI study who underwent whole-body magnetic resonance imaging (MRI). Dietary habits were evaluated using repeated 24 h food lists and a food frequency questionnaire. Sex-stratified multiple linear regression models were applied to quantify the association between nutrition variables of interest and LIC, adjusting for liver fat content (LFC), energy intake, and age. Mean age of participants was 56.4 ± 9.0 years and 44.2% were female. Mean LIC was 1.23 ± 0.12 mg/g dry weight, with higher values in men than in women (1.26 ± 0.13 and 1.20 ± 0.10 mg/g, p < 0.001). Alcohol intake was positively associated with LIC (men: β = 1.94; women: β = 4.98, p-values < 0.03). Significant negative associations with LIC were found for fiber (β = −5.61, p < 0.001) and potassium (β = −0.058, p = 0.034) for female participants only. Furthermore, LIC was highly correlated with liver fat content in both sexes. Our findings suggests that there are sex-specific associations of habitual dietary intake and LIC. Alcohol, fiber, and potassium may play a considerable role in liver iron metabolism.

Distribution and Associated Factors of Hepatic Iron-A Population-Based Imaging Study

Hepatic iron overload can cause severe organ damage; therefore, an early diagnosis and the identification of potential risk factors is crucial. We aimed to investigate the sex-specific distribution of hepatic iron content (HIC) in a population-based cohort and identify relevant associated factors from a panel of markers. We analyzed N = 353 participants from a cross-sectional sample (KORA FF4) who underwent whole-body magnetic resonance imaging. HIC was assessed by single-voxel spectroscopy with a high-speed T2-corrected multi-echo technique. A large panel of markers, including anthropometric, genetic, and laboratory values, as well as behavioral risk factors were assessed. Relevant factors associated with HIC were identified by variable selection based on LASSO regression with bootstrap resampling. HIC in the study sample (mean age at examination: 56.0 years, 58.4% men) was significantly lower in women (mean ± SD: 39.2 ± 4.1 s^-1) than in men (41.8 ± 4.7 s^-1, p < 0.001). Relevant factors associated with HIC were HbA1c as well as prediabetes for men and visceral adipose tissue as well as age for women. Hepatic fat, alcohol consumption, and genetic risk score for iron levels were associated with HIC in both sexes. In conclusion, there are sex-specific associations of HIC with markers of body composition, glucose metabolism, and alcohol consumption.

Evaluation of Hepatic Iron Overload Using a Contemporary 0.55 T MRI System

BACKGROUND

MRI T2* and R2* mapping have gained clinical acceptance for noninvasive assessment of iron overload. Lower field MRI may offer increased measurement dynamic range in patients with high iron concentration and may potentially increase MRI accessibility, but it is compromised by lower signal-to-noise ratio that reduces measurement precision.

PURPOSE

To characterize a high-performance 0.55 T MRI system for evaluating patients with liver iron overload.

STUDY TYPE

Prospective.

POPULATION

Forty patients with known or suspected iron overload (sickle cell anemia [n = 5], ß-thalassemia [n = 3], and hereditary spherocytosis [n = 2]) and a liver iron phantom.

FIELD STRENGTH/SEQUENCE

A breath-held multiecho gradient echo sequence at 0.55 T and 1.5 T.

ASSESSMENT

Patients were imaged with T2*/R2* mapping 0.55 T and 1.5 T within 24 hours, and 16 patients returned for follow-up exams within 6-16 months, resulting in 56 paired studies. Liver T2* and R2* measurements and standard deviations were compared between 0.55 T and 1.5 T and used to validate a predictive model between field strengths. The model was then used to classify iron overload at 0.55 T.

STATISTICAL TESTS

Linear regression and Bland-Altman analysis were used for comparisons, and measurement precision was assessed using the coefficient of variation. A P-value < 0.05 was considered statistically significant.

RESULTS

R2* was significantly lower at 0.55 T in our cohort (488 ± 449 s^-1 at 1.5 T vs. 178 ± 155 s^-1 at 0.55 T, n = 56 studies) and in the patients with severe iron overload (937 ± 369 s^-1 at 1.5 T vs. 339 ± 127 s^-1 at 0.55 T, n = 23 studies). The coefficient of variation indicated reduced precision at 0.55 T (3.5 ± 2.2% at 1.5 T vs 6.9 ± 3.9% at 0.55 T). The predictive model accurately predicted 1.5 T R2* from 0.55 T R2* (Bland Altman bias = -6.6 ± 20.5%). Using this model, iron overload at 0.55 T was classified as: severe R2* > 185 s^-1 , moderate 81 s^-1  < R2* < 185 s^-1 , and mild 45 s^-1  < R2* < 91 s^-1 .

DATA CONCLUSION

We demonstrated that 0.55 T provides T2* and R2* maps that can be used for the assessment of liver iron overload in patients.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Quantifying Bone Marrow Fat Fraction and Iron by MRI for Distinguishing Aplastic Anemia from Myelodysplastic Syndromes

Background

Bone marrow of patients with aplastic anemia (AA) is different from that of patients with myelodysplastic syndrome (MDS) and is difficult to identify by blood examination. IDEAL‐IQ (iterative decomposition of water and fat with echo asymmetry and least‐squares estimation) imaging might be able to quantify fat fraction (FF) and iron content in bone tissues.

Purpose

To determine if IDEAL‐IQ measurements of bone marrow FF and iron content can distinguish between patients with AA and MDS.

Study Type

Retrospective.

Population

Fifty‐seven patients with AA, 21 patients with MDS, and 24 healthy controls.

Field Strength/Sequence

3.0 T, IDEAL‐IQ sequence.

Assessment

Three independent observers evaluated the IDEAL‐IQ images and measured FF and R2* in the left posterior superior iliac spine.

Statistical Tests

Kruskal–Wallis test, linear correlations, and Bland–Altman analysis were used. A P‐value of <0.05 was considered statistically significant.

Results

The FF in patients with AA (79.46% ± 15.00%) was significantly higher than that in patients with MDS (42.78% ± 30.09%) and control subjects (65.50% ± 14.73%). However, there was no significant difference in FF between control subjects and patients with MDS (P = 0.439). The R2* value of AA, MDS, and controls was 145.38 ± 53.33, (171.13 ± 100.89, and 135.99 ± 32.41/second, respectively, with no significant difference between the three groups (P = 0.553).

Data Conclusion

Quantitative IDEAL‐IQ magnetic resonance imaging may facilitate the diagnosis of AA and distinguish it from MDS.

Level of Evidence

3

Technical Efficacy Stage

2

Optimisation of T2 and T2* sequences in MRI for better quantification of iron on transfused dependent sickle cell patients

This work aimed to investigate the effect of different shim techniques, voxel sizes, and repetition time (TR) on using theT2 and T2* sequences to determine their optimum settings to investigate the quantification of iron in transfused dependent sickle cell patients. The effect of each of these parameters was investigated on phantoms of different Gadolinium (Gd) concentrations, on 10 volunteers and 25 patients using a1 5T MRI Philips scanner. No significant difference between the three shim techniques was noticed in either T2 or T2* sequence measurements. Pixel sizes of 1 × 1 and 2 × 2 mm provided optimum results for T2 measurements. At 1 × 1 mm pixel size the T2* measurements experienced less error in measurements than the size of 2.5 × 2.5 mm used in the literature. Even though the slice thickness variation did not provide any changes in T2 measurements, the 12 mm provided optimum T2* measurements. TR variation did not yield significant changes on either T2 or T2* measurements. These results indicate that both T2 and T2* sequences can be further improved by providing more reliable measurements and reducing acquisition time.