Liver iron overload and fat content analyzed by magnetic resonance contribute to evaluatingthe progression of chronic hepatitis B

Chronic hepatitis B (CHB) and its complications still have a major role in liver-related mortality. It has been indicated that hepatic iron and steatosis may influence liver fibrosis and carcinogenesis. The present study aimed to assess the liver iron and fat in patients with CHB by MRI in order to estimate the associations among liver iron, fat and the severity and progression of liver fibrosis. In the present retrospective study, consecutive patients with CHB examined from August 2018 to August 2020 were analyzed. Liver iron and fat content were assessed by MRI, which was measured as liver iron content (LIC) and proton density fat fraction (PDFF). A total of 340 patients were included in the current study. For LIC, the median value was 1.68 mg/g and elevated LIC was seen in 122 patients (35.9%). For liver fat content, the median value of PDFF was 3.1%, while only 15.0% of patients had liver steatosis (PDFF ≥5%). Age, total bilirubin and sex were independent predictive factors of liver iron overload [odds ratio (OR)=1.036, 1.005 and 8.834, respectively]. A higher platelet count (OR=1.005) and no portal hypertension (OR=0.381) independently predicted liver steatosis. The areas under the receiver operating characteristic curves of PDFF for the identification of liver cirrhosis estimated by different non-invasive tools ranged from 0.629 to 0.704. It was concluded that iron overload was common in patients with CHB, particularly in those with older age, male sex and high total bilirubin level, and liver steatosis was less common in CHB. Liver iron and fat content analyzed by MRI may contribute to the evaluation of the severity and progression of CHB.

Simulation of a virtual liver iron overload model and R2 * estimation using multispectral fat-water models for GRE and UTE acquisitions at 1.5 T and 3 T

R2 *-MRI has emerged as a noninvasive alternative to liver biopsy for assessment of hepatic iron content (HIC). Multispectral fat-water R2 * modeling techniques such as the nonlinear least squares (NLSQ) fitting and autoregressive moving average (ARMA) models have been proposed for the accurate assessment of iron overload by also considering fat, which can otherwise confound R2 *-based HIC measurements in conditions of coexisting iron overload and steatosis. However, the R2 * estimation by these multispectral models has not been systematically investigated for various acquisition methods in iron overload only conditions and across the full clinically relevant range of HICs (0-40 mg Fe/g dry liver weight). The purpose of this study is to evaluate the R2 * accuracy and precision of multispectral models for various multiecho gradient echo (GRE) and ultrashort echo time (UTE) imaging acquisitions by constructing virtual iron overload models based on true histology and synthesizing MRI signals via Monte Carlo simulations at 1.5 T and 3 T, and comparing their results with monoexponential model and published in vivo R2 *-HIC calibrations. The signals were synthesized with TE1  = 1.0 ms for GRE and TE1  = 0.1 ms for UTE acquisition for varying echo spacing, ΔTE (0.1, 0.5, 1, 2 ms), and maximum echo time, TEmax (2, 4, 6, 10 ms). An iron-doped phantom study is also conducted to validate the simulation results in experimental GRE (TE1  = 1.2 ms, ΔTE  = 0.72 ms, TEmax  = 6.24 ms) and UTE (TE1  = 0.1 ms, ΔTE  = 0.5 ms, TEmax  = 6.1 ms) acquisitions. For GRE acquisitions, the multispectral ARMA and NLSQ models produced higher slopes (0.032-0.035) compared with the monoexponential model and published in vivo R2 *-HIC calibrations (0.025-0.028). However, for UTE acquisition for shorter echo spacing (≤0.5 ms) and longer maximum echo time, TEmax (≥6 ms), the multispectral and monoexponential signal models produced similar R2 *-HIC slopes (1.5 T, 0.028-0.032; 3 T, 0.014-0.016) and precision values (coefficient of variation < 25%) across the full clinical spectrum of HICs at both 1.5 T and 3 T. The phantom analysis also showed that all signal models demonstrated a significant improvement in R2 * estimation for UTE acquisition compared with GRE, confirming our simulation findings. Future work should investigate the performance of multispectral fat-water models by simulating liver models in coexisting conditions of iron overload and steatosis for accurate R2 * and fat quantification.

Free-breathing high isotropic resolution quantitative susceptibility mapping (QSM) of liver using 3D multi-echo UTE cones acquisition and respiratory motion-resolved image reconstruction

PURPOSE

To enable free-breathing and high isotropic resolution liver quantitative susceptibility mapping (QSM) using 3D multi-echo UTE cones acquisition and respiratory motion-resolved image reconstruction.

METHODS

Using 3D multi-echo UTE cones MRI, a respiratory motion was estimated from the k-space center of the imaging data. After sorting the k-space data with estimated motion, respiratory motion state-resolved reconstruction was performed for multi-echo data followed by nonlinear least-squares fitting for proton density fat fraction (PDFF),R 2 * $$ {\mathrm{R}}_2^{\ast } $$ , and fat-corrected B0 field maps. PDFF and B0 field maps were subsequently used for QSM reconstruction. The proposed method was compared with motion-averaged (gridding) reconstruction and conventional 3D multi-echo Cartesian MRI in moving gadolinium phantom and in vivo studies. Region of interest (ROI)-based linear regression analysis was performed on these methods to investigate correlations between gadolinium concentration and QSM in the phantom study and betweenR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and QSM in in vivo study.

RESULTS

Cones with motion-resolved reconstruction showed sharper image quality compared to motion-averaged reconstruction with a substantial reduction of motion artifacts in both moving phantom and in vivo studies. For ROI-based linear regression analysis of the phantom study, susceptibility values from cones with motion-resolved reconstruction (QSM ppm $$ {\mathrm{QSM}}_{\mathrm{ppm}} $$  = 0.31 × gadolinium mM + $$ \times {\mathrm{gadolinium}}_{\mathrm{mM}}+ $$ 0.05,R 2 $$ {R}^2 $$  = 0.999) and Cartesian without motion (QSM ppm $$ {\mathrm{QSM}}_{\mathrm{ppm}} $$  = 0.32× gadolinium mM + $$ \times {\mathrm{gadolinium}}_{\mathrm{mM}}+ $$ 0.04,R 2 $$ {R}^2 $$  = 1.000) showed linear relationships with gadolinium concentrations and showed good agreement with each other. For in vivo, motion-resolved reconstruction showed higher goodness of fit (QSM ppm $$ {\mathrm{QSM}}_{\mathrm{ppm}} $$  = 0.00261 × R 2 s - 1 * - $$ \times {\mathrm{R}}_{2_{{\mathrm{s}}^{-1}}}^{\ast }- $$ 0.524,R 2 $$ {R}^2 $$  = 0.977) compared to motion-averaged reconstruction (QSM ppm $$ {\mathrm{QSM}}_{\mathrm{ppm}} $$ = 0.0021 × R 2 s - 1 * - $$ \times {\mathrm{R}}_{2_{{\mathrm{s}}^{-1}}}^{\ast }- $$ 0.572,R 2 $$ {R}^2 $$ = 0.723) in ROI-based linear regression analysis betweenR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and QSM.

CONCLUSION

Feasibility of free-breathing liver QSM was demonstrated with motion-resolved 3D multi-echo UTE cones MRI, achieving high isotropic resolution currently unachievable in conventional Cartesian MRI.

Cascade of Denoising and Mapping Neural Networks for MRI R2* Relaxometry of Iron-Loaded Liver

MRI of effective transverse relaxation rate (R2*) measurement is a reliable method for liver iron concentration quantification. However, R2* mapping can be degraded by noise, especially in the case of iron overload. This study aimed to develop a deep learning method for MRI R2* relaxometry of an iron-loaded liver using a two-stage cascaded neural network. The proposed method, named CadamNet, combines two convolutional neural networks separately designed for image denoising and parameter mapping into a cascade framework, and the physics-based R2* decay model was incorporated in training the mapping network to enforce data consistency further. CadamNet was trained using simulated liver data with Rician noise, which was constructed from clinical liver data. The performance of CadamNet was quantitatively evaluated on simulated data with varying noise levels as well as clinical liver data and compared with the single-stage parameter mapping network (MappingNet) and two conventional model-based R2* mapping methods. CadamNet consistently achieved high-quality R2* maps and outperformed MappingNet at varying noise levels. Compared with conventional R2* mapping methods, CadamNet yielded R2* maps with lower errors, higher quality, and substantially increased efficiency. In conclusion, the proposed CadamNet enables accurate and efficient iron-loaded liver R2* mapping, especially in the presence of severe noise.

Hepatic Iron Quantification Using a Free-Breathing 3D Radial Gradient Echo Technique and Validation With a 2D Biopsy-Calibrated R2* Relaxometry Method

BACKGROUND

Hepatic iron content (HIC) is an important parameter for the management of iron overload. Non-invasive HIC assessment is often performed using biopsy-calibrated two-dimensional breath-hold Cartesian gradient echo (2D BH GRE) R2* -MRI. However, breath-holding is not possible in most pediatric patients or those with respiratory problems, and three-dimensional free-breathing radial GRE (3D FB rGRE) has emerged as a viable alternative.

PURPOSE

To evaluate the performance of a 3D FB rGRE and validate its R2* and fat fraction (FF) quantification with 3D breath-hold Cartesian GRE (3D BH cGRE) and biopsy-calibrated 2D BH GRE across a wide range of HICs.

STUDY TYPE

Retrospective.

SUBJECTS

Twenty-nine patients with hepatic iron overload (22 females, median age: 15 [5-25] years).

FIELD STRENGTH/SEQUENCE

Three-dimensional radial and 2D and 3D Cartesian multi-echo GRE at 1.5 T.

ASSESSMENT

R2* and FF maps were computed for 3D GREs using a multi-spectral fat model and 2D GRE R2* maps were calculated using a mono-exponential model. Mean R2* and FF values were calculated via whole-liver contouring and T2* -thresholding by three operators.

STATISTICAL TESTS

Inter- and intra-observer reproducibility was assessed using Bland-Altman and intraclass correlation coefficient (ICC). Linear regression and Bland-Altman analysis were performed to compare R2* and FF values among the three acquisitions. One-way repeated-measures ANOVA and Wilcoxon signed-rank tests, respectively, were used to test for significant differences between R2* and FF values obtained with different acquisitions. Statistical significance was assumed at P < 0.05.

RESULTS

The mean biases and ICC for inter- and intra-observer reproducibility were close to 0% and >0.99, respectively for both R2* and FF. The 3D FB rGRE R2* and FF values were not significantly different (P > 0.44) and highly correlated (R2  ≥ 0.98) with breath-hold Cartesian GREs, with mean biases ≤ ±2.5% and slopes 0.90-1.12. In non-breath-holding patients, Cartesian GREs showed motion artifacts, whereas 3D FB rGRE exhibited only minimal streaking artifacts.

DATA CONCLUSION

Free-breathing 3D radial GRE is a viable alternative in non-breath-hold patients for accurate HIC estimation.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Interrelationship between liver T2*-weighted magnetic resonance imaging and acoustic radiation force impulse elastography measurement results and plasma ferritin levels in children with β-thalassemia major

PURPOSE

To evaluate correlation and agreement between T2*-weighted magnetic resonance imaging (T2*-wMRI), acoustic radiation force impulse elastography (ARFI-e) measurement results of liver and plasma ferritin levels (PFLs) in children with β-thalassemia major (β-TM).

METHODS

The study included 40 pediatric patients (aged 64-216 months; 14 girls, 26 boys) receiving blood transfusion and chelation therapy. To detect the severity of liver iron overload (LIO) and concomitant parenchymal fibrosis, T2*-wMRI and ARFI-e measurements were performed from the right lobe segments. Student's t-test, Mann-Whitney U, ANOVA, Spearman's test and ICC were used for statistical analysis.

RESULTS

After the measurements of T2*-wMRI, patients were grouped as normal in 4 (10%), mild in 11 (27.5%), moderate in 21 (52.5%), and severe in 4 (10%) cases in terms of LIO. Combined moderate and severe groups had significantly higher ARFI-e and PFL values than the combination of other groups (p = .001, p = .040). The ARFI-e measurements of boys were found to be significantly higher than those of girls (p = .023). A strong negative correlation between T2*-wMRI and ARFI-e and a moderate negative correlation between T2*-wMRI and PFL were detected (p;r = 0.001;-0.606, p;r = 0.009; -0.407). A strong positive correlation was found between ARFI-e values and PFL (p;r = 0.001; 0.659). The optimal cut-off value of ARFI-e to predict liver fibrosis because of moderate&severe LIO was determined to be 1.29 M/s (80% sensitivity and 88% specificity). A moderate agreement was observed between the T2*-wMRI and ARFI-e methods [ICC: 0.680, 95% CI: (0.470 to 0.817)].

CONCLUSION

Given the strong correlation and moderate agreement between ARFI-e and T2*-wMRI, ARFI -e could be used to monitor LIO in children with β-TM.

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.

Rapid automated liver quantitative susceptibility mapping

BACKGROUND

Accurate measurement of the liver iron concentration (LIC) is needed to guide iron-chelating therapy for patients with transfusional iron overload. In this work, we investigate the feasibility of automated quantitative susceptibility mapping (QSM) to measure the LIC.

PURPOSE

To develop a rapid, robust, and automated liver QSM for clinical practice.

STUDY TYPE

Prospective.

POPULATION

13 healthy subjects and 22 patients.

FIELD STRENGTH/SEQUENCES

1.5 T and 3 T/3D multiecho gradient-recalled echo (GRE) sequence.

ASSESSMENT

Data were acquired using a 3D GRE sequence with an out-of-phase echo spacing with respect to each other. All odd echoes that were in-phase (IP) were used to initialize the fat-water separation and field estimation (T₂ *-IDEAL) before performing QSM. Liver QSM was generated through an automated pipeline without manual intervention. This IP echo-based initialization method was compared with an existing graph cuts initialization method (simultaneous phase unwrapping and removal of chemical shift, SPURS) in healthy subjects (n = 5). Reproducibility was assessed over four scanners at two field strengths from two manufacturers using healthy subjects (n = 8). Clinical feasibility was evaluated in patients (n = 22).

STATISTICAL TESTS

IP and SPURS initialization methods in both healthy subjects and patients were compared using paired t-test and linear regression analysis to assess processing time and region of interest (ROI) measurements. Reproducibility of QSM, R₂ *, and proton density fat fraction (PDFF) among the four different scanners was assessed using linear regression, Bland-Altman analysis, and the intraclass correlation coefficient (ICC).

RESULTS

Liver QSM using the IP method was found to be ~5.5 times faster than SPURS (P < 0.05) in initializing T₂ *-IDEAL with similar outputs. Liver QSM using the IP method were reproducibly generated in all four scanners (average coefficient of determination 0.95, average slope 0.90, average bias 0.002 ppm, 95% limits of agreement between -0.06 to 0.07 ppm, ICC 0.97).

DATA CONCLUSION

Use of IP echo-based initialization enables robust water/fat separation and field estimation for automated, rapid, and reproducible liver QSM for clinical applications.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:725-732.

Prevalence of abnormal glucose homeostasis in Chinese patients with non-transfusion-dependent thalassemia

Purpose: To determine the prevalence and underlying pathology of abnormal glucose homeostasis in Chinese patients with non-transfusion-dependent thalassemia (NTDT). Patients and methods: In this study, we enrolled 211 patients aged 4-63 years with NTDT, including 79 β thalassemia intermedia patients, 114 Hb H disease patients and 18 Hb E/β thalassemia patients. All had oral glucose tolerance test, serum ferritin (SF), homeostasis model assessment (HOMA) and liver iron concentration (LIC) measurement. One hundred and twenty healthy age-matched controls were also used for the comparative purpose. Iron load was assessed by using SF and hepatic load by LIC using validated MRI techniques. Results: The 211 patients were divided into three groups according to their fasting and 2 hrs postprandial blood glucose levels: hypoglycemic, normal glucose tolerance (NGT) and hyperglycemic groups. In this study, 149 patients had NGT, 33 had hypoglycemia, 4 had diabetes and 25 had impaired glucose tolerance (IGT). None had impaired fasting glucose. There was a significant correlation between 2 hrs postprandial blood glucose levels and age, PINS120, HOMA-IR, alanine aminotransferase and LIC (P<0.05). Risk factors for IGT in NTDT patients were older age (≥24 years) and SF concentration of ≥2,500 ng/mL. Conclusion: Age ≥24 years and SF ≥2,500 ng/mL of NTDT patients were at a greater risk for impaired glucose tolerance.

Iron deposition quantification: Applications in the brain and liver

Iron has long been implicated in many neurological and other organ diseases. It is known that over and above the normal increases in iron with age, in certain diseases there is an excessive iron accumulation in the brain and liver. MRI is a noninvasive means by which to image the various structures in the brain in three dimensions and quantify iron over the volume of the object of interest. The quantification of iron can provide information about the severity of iron-related diseases as well as quantify changes in iron for patient follow-up and treatment monitoring. This article provides an overview of current MRI-based methods for iron quantification, specifically for the brain and liver, including: signal intensity ratio, R₂ , R2*, R2', phase, susceptibility weighted imaging and quantitative susceptibility mapping (QSM). Although there are numerous approaches to measuring iron, R₂ and R2* are currently preferred methods in imaging the liver and QSM has become the preferred approach for imaging iron in the brain.

LEVEL OF EVIDENCE

5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018. J. MAGN. RESON. IMAGING 2018;48:301-317.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Quantitative analysis of hepatic iron in patients suspected of coexisting iron overload and steatosis using multi-echo single-voxel magnetic resonance spectroscopy: Comparison with fat-saturated multi-echo gradient echo sequence

BACKGROUND

The coexistence of hepatic iron and fat is common in patients with hyperferritinemia, which plays an interactive and aggressive role in the progression of diseases (fibrosis, cirrhosis, and hepatocellular carcinomas).

PURPOSE

To evaluate a modified high-speed T₂ -corrected multi-echo, single voxel spectroscopy sequence (HISTOV) for liver iron concentration (LIC) quantification in patients with hyperferritinemia, with simultaneous fat fraction (FF) estimation.

STUDY TYPE

Retrospective cohort study.

POPULATION

Thirty-eight patients with hyperferritinemia were enrolled.

FIELD STRENGTH/SEQUENCE

HISTOV, a fat-saturated multi-echo gradient echo (GRE) sequence, and a spin echo sequence (FerriScan) were performed at 1.5T.

ASSESSMENT

R₂ of the water signal and FF were calculated with HISTOV, and R2* values were derived from the GRE sequence, with R₂ and LIC from FerriScan serving as the references.

STATISTICAL TESTS

Linear regression, correlation analyses, receiver operating characteristic analyses, and Bland-Altman analyses were conducted.

RESULTS

Abnormal hepatic iron load was detected in 32/38 patients, of whom 10/32 had coexisting steatosis. Strong correlation was found between R2* and FerriScan-LIC (R² = 0.861), and between HISTOV-R_{2_} water and FerriScan-R₂ (R²  = 0.889). Furthermore, HISTOV-R_{2_} water was not correlated with HISTOV-FF. The area under the curve (AUC) for HISTOV-R_{2_} water was 0.974, 0.971, and 1, corresponding to clinical FerriScan-LIC thresholds of 1.8, 3.2, and 7.0 mg/g dw, respectively. No significant difference in the AUC was found between HISTOV-R_{2_} water and R2* at any of the LIC thresholds, with P-values of 0.42, 0.37, and 1, respectively. HISTOV-LIC showed excellent agreement with FerriScan-LIC, with a mean bias of 0.00 ± 1.18 mg/g dw, whereas the mean bias between GRE-LIC and FerriScan-LIC was 0.53 ± 1.49 mg/g dw.

DATA CONCLUSION

HISTOV is useful for the quantification and grading of liver iron overload in patients with hyperferritinemia, particularly in cases with coexisting steatosis. HISTOV-LIC showed no systematic bias compared with FerriScan-LIC, making it a promising alternative for iron quantification.

LEVEL OF EVIDENCE

3 Technical Efficacy Stage 2 J. Magn. Reson. Imaging 2018.

Serum Iron Levels Decreased in Patients with HBV-Related Hepatocellular Carcinoma, as a Risk Factor for the Prognosis of HBV-Related HCC

Background: Hepatocellular carcinoma (HCC) is common and the second leading causes of cancer-related deaths. HCC usually occurs on the basis of chronic liver diseases. At present, the study of iron metabolism in chronic liver diseases was limited to chronic HCV infection, nonalcoholic fatty liver disease, and alcoholic liver disease. This study aimed to investigate the effect of serum iron levels on the progression of chronic HBV infection and the relationship with the prognosis of HBV-related HCC. Methods: A respective study involving 277 healthy individuals as controls (HC), 295 patients with chronic hepatitis B (CHB), 224 patients with HBV-related liver cirrhosis (HBV-related LC), and 586 patients with HBV- related HCC were enrolled in this study. Hematological parameters, HBVDNA and liver biochemistry were analyzed. Child-Pugh grade and BCLC stage of the HBV-related HCC patients were calculated. Results: The serum iron levels were lowest in the HBV- related HCC group as compared with HC, CHB, and HBV-related LC groups (35.07 ± 6.97, 27.37 ± 10.26, 24.53 ± 10.36 vs. 17.90 ± 0.14, P < 0.001). Strikingly, serum iron levels were lowest in HBV- related HCC patients with tumor size more than 10 cm as compared with HBV- related HCC patients with tumor size smaller than 3, 3-5, and 5-10 cm by subgroup analysis (22.12 ± 0.94, 21.44 ± 1.41, 15.65 ± 0.98 vs. 13.36 ± 1.15, P < 0.001). Serum iron levels significantly decreased with worsening Child-Pugh grades and BCLC stages in HBV-related HCC group. In addition, serum iron levels was positively correlated with Retinol-Binding Protein, total bile acid, hemoglobin, and lymphocyte and negatively correlated with white blood cell (WBC) and platelet in HBV- related HCC group. ROC curve analysis showed serum iron levels at 15.1 μmol/L as the optimal cut-off point for determining the survival of HBV-related HCC. By the Cox regression model analysis, serum iron levels <15.1 μmol/l together with higher AFP levels, worse BCLC stages, and larger tumor size showed higher mortality of HBV-related HCC patients (hazard ratio = 2.280, 95% confidence interval, 1.815-2.865; P < 0.001). Conclusions: Serum iron levels affected the progression of chronic HBV infection. The prognosis of HBV- related HCC patients with serum iron levels <15.1 μmol/l together with higher AFP levels, worse BCLC stages, and larger tumor lesion were poor.

Automated vessel exclusion technique for quantitative assessment of hepatic iron overload by R2*-MRI

BACKGROUND

Extraction of liver parenchyma is an important step in the evaluation of R2*-based hepatic iron content (HIC). Traditionally, this is performed by radiologists via whole-liver contouring and T2*-thresholding to exclude hepatic vessels. However, the vessel exclusion process is iterative, time-consuming, and susceptible to interreviewer variability.

PURPOSE

To implement and evaluate an automatic hepatic vessel exclusion and parenchyma extraction technique for accurate assessment of R2*-based HIC.

STUDY TYPE

Retrospective analysis of clinical data.

SUBJECTS

Data from 511 MRI exams performed on 257 patients were analyzed.

FIELD STRENGTH/SEQUENCE

All patients were scanned on a 1.5T scanner using a multiecho gradient echo sequence for clinical monitoring of HIC.

ASSESSMENT

An automated method based on a multiscale vessel enhancement filter was investigated for three input data types-contrast-optimized composite image, T2* map, and R2* map-to segment blood vessels and extract liver tissue for R2*-based HIC assessment. Segmentation and R2* results obtained using this automated technique were compared with those from a reference T2*-thresholding technique performed by a radiologist.

STATISTICAL TESTS

The Dice similarity coefficient was used to compare the segmentation results between the extracted parenchymas, and linear regression and Bland-Altman analyses were performed to compare the R2* results, obtained with the automated and reference techniques.

RESULTS

Mean liver R2* values estimated from all three filter-based methods showed excellent agreement with the reference method (slopes 1.04-1.05, R² > 0.99, P < 0.001). Parenchyma areas extracted using the reference and automated methods had an average overlap area of 87-88%. The T2*-thresholding technique included small vessels and pixels at the vessel/tissue boundaries as parenchymal area, potentially causing a small bias (<5%) in R2* values compared to the automated method.

DATA CONCLUSION

The excellent agreement between reference and automated hepatic vessel segmentation methods confirms the accuracy and robustness of the proposed method. This automated approach might improve the radiologist's workflow by reducing the interpretation time and operator dependence for assessing HIC, an important clinical parameter that guides iron overload management.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1542-1551.

MRI-based quantitative susceptibility mapping (QSM) and R2* mapping of liver iron overload: Comparison with SQUID-based biomagnetic liver susceptometry

PURPOSE

We aimed to determine the agreement between quantitative susceptibility mapping (QSM)-based biomagnetic liver susceptometry (BLS) and confounder-corrected R2* mapping with superconducting quantum interference device (SQUID)-based biomagnetic liver susceptometry in patients with liver iron overload.

METHODS

Data were acquired from two healthy controls and 22 patients undergoing MRI and SQUID-BLS as part of routine monitoring for iron overload. Magnetic resonance imaging was performed on a 3T system using a three-dimensional multi-echo gradient-echo acquisition. Both magnetic susceptibility and R2* of the liver were estimated from this acquisition. Linear regression was used to compare estimates of QSM-BLS and R2* to SQUID-BLS.

RESULTS

Both QSM-BLS and confounder-corrected R2* were sensitive to the presence of iron in the liver. Linear regression between QSM-BLS and SQUID-BLS demonstrated the following relationship: QSM-BLS = (-0.22 ± 0.11) + (0.49 ± 0.05) · SQUID-BLS with r²  = 0.88. The coefficient of determination between liver R2* and SQUID-BLS was also r²  = 0.88.

CONCLUSION

We determined a strong correlation between both QSM-BLS and confounder-corrected R2* to SQUID-BLS. This study demonstrates the feasibility of QSM-BLS and confounder-corrected R2* for assessing liver iron overload, particularly when SQUID systems are not accessible. Magn Reson Med 78:264-270, 2017. © 2016 International Society for Magnetic Resonance in Medicine.