Accurate simultaneous quantification of liver steatosis and iron overload in diffuse liver diseases with MRI

State-of-the-Art Quantification of Liver Iron With MRI-Vendor Implementation and Available Tools

The role of MRI to estimate liver iron concentration (LIC) for identifying patients with iron overload and guiding the titration of chelation therapy is increasingly established for routine clinical practice. However, the existence of multiple MRI-based LIC quantification techniques limits standardization and widespread clinical adoption. In this article, we review the existing and widely accepted MRI-based LIC estimation methods at 1.5 T and 3 T: signal intensity ratio (SIR) and relaxometry (R2 and R2*) and discuss the basic principles, acquisition and analysis protocols, and MRI-LIC calibrations for each technique. Further, we provide an up-to-date information on MRI vendor implementations and available offline commercial and free software for each MRI-based LIC quantification approach. We also briefly review the emerging and advanced MRI techniques for LIC estimation and their current limitations for clinical use. Lastly, we discuss the implications of MRI-based LIC measurements on clinical use and decision-making in the management of patients with iron overload. Some of the key highlights from this review are as follows: 1) Both R2 and R2* can estimate accurate and reproducible LIC, when validated acquisition parameters and analysis protocols are applied, 2) Although the Ferriscan R2 method has been widely used, recent consensus and guidelines endorse R2*-MRI as the most accurate and reproducible method for LIC estimation, 3) Ongoing efforts aim to establish R2*-MRI as the standard approach for quantifying LIC, and 4) Emerging R2*-MRI techniques employ radial sampling strategies and offer improved motion compensation and broader dynamic range for LIC estimation. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

PBCS-ConvNeXt: Convolutional Network-Based Automatic Diagnosis of Non-alcoholic Fatty Liver in Abdominal Ultrasound Images

Non-alcoholic fatty liver disease (NAFLD) is a highly prevalent chronic liver condition characterized by excessive hepatic fat accumulation. Early diagnosis is crucial as NAFLD can progress to more severe conditions like steatohepatitis, fibrosis, cirrhosis, and hepatocellular carcinoma without timely intervention. While liver biopsy remains the gold standard for NAFLD assessment, abdominal ultrasound (US) imaging has emerged as a widely adopted non-invasive modality due to convenience and low cost. However, the subjective interpretation of US images is challenging and unpredictable. This study proposes a deep learning-based computer-aided diagnosis (CAD) model, termed potent boosts channel-aware separable intent - ConvNeXt (PBCS-ConvNeXt), for automated NAFLD classification using B-mode US images. The model architecture comprises three key components: The potent stem cell, an advanced trainable preprocessing module for robust feature extraction; Enhanced ConvNeXt Blocks that amplify channel-wise features to refine processing; and the boosting block that integrates multi-stage features for effective information extraction from US data. Utilizing fatty liver gradings from attenuation imaging (ATI) as the ground truth, the PBCS-ConvNeXt model was evaluated using 5-fold cross-validation, achieving an accuracy of 82%, sensitivity of 81% and specificity of 83% for identifying fatty liver on abdominal US. The proposed CAD system demonstrates high diagnostic performance in NAFLD classification from US images, enabling early detection and informing timely clinical management to prevent disease progression.

Reproducibility of liver iron concentration measured by R2* method based on 1.5-T MRI: a meta-analysis

OBJECTIVES

To explore the reproducibility of the 1.5-T MR imaging (MRI)-based R2* method in measuring the liver iron concentration (LIC) across different MRI scanners, scan parameters, and postprocessing techniques.

MATERIALS AND METHODS

We performed a systematic search of the PubMed, Embase, Medline, Cochrane Library, and Web of Science databases and identified studies that used the 1.5-T MRI-based R2* method to measure the LIC. The original data were extracted from the selected studies. Reproducibility was assessed in terms of the ability to replicate the measured LIC with the 1.5-T MRI-based R2* method across different scanning instruments, scan parameters, and postprocessing techniques. We used the scanner equipment, scan parameters, and postprocessing technique as random effects to determine whether the R2* values obtained in the different studies were significantly different after the effects of the measured LIC were excluded. The calibration curve that best fit the R2* value to the LIC was estimated via univariate regression.

RESULTS

Twenty-one studies (1147 participants) were included. The seven studies (435 participants) in which the initial TE was ≤ 1.0 ms and the TE spacing was ≤ 1.4 ms did not have significant differences in the measured R2* value in pairwise comparisons (p > 0.05). Calibration of R2* to LIC was as follows: LIC (mg/g) = 0.042 + 2.85 × 10-2 R2* (s-1) (R2 = 0.79).

CONCLUSION

The 1.5-T MRI-based R2* method in estimating LIC was reproducible across different MRI scanners, scan parameters, and postprocessing techniques.

KEY POINTS

Question The R2* method is widely used to quantify LIC, but the reproducibility of R2*-based LIC estimation remains unknown. Findings In scan sequences with an initial echo time (TE) ≤ 1.0 ms and a TE spacing ≤ 1.4 ms, the R2*-based LIC quantification at 1.5 T achieved good reproducibility. Clinical relevance The 1.5-T MRI-based R2* method enables reproducible quantification of the LIC; its reproducibility spares patients from unnecessary trauma and economic burdens while promoting the extensive clinical dissemination of R2*-based LIC quantification methods.

Impact of particle size on R 2 * and fat fraction estimation for accurate assessment of hepatic iron overload and steatosis using MRI

PURPOSE

To investigate the impact of iron particle size onR 2 * $$ {R}_2^{\ast } $$ and fat fraction (FF) estimations for coexisting hepatic iron overload and steatosis condition using Monte Carlo simulations and phantoms.

METHODS

Three iron particle sizes (0.38, 0.52, and 0.71 μm) were studied using simulations and phantoms. Virtual liver models mimicking in vivo spatial distribution of fat droplets and iron deposits were created, and MRI signals were synthesized using Monte Carlo simulations for FF 1%-30% and liver iron concentration (LIC) 1-20 mg/g. Seventy-five fat-iron phantoms with varying iron (0-8 μg/mL) and fat (0%-40%) concentrations and particle sizes were constructed. Three-way analysis of variance was used to assess the effect of iron particle size onR 2 * $$ {R}_2^{\ast } $$ and FF estimations.

RESULTS

In simulations, estimated and true FF were in excellent agreement (slope: 0.93-1.09) for liver iron concentration ≤ 13 mg/g. For both simulations and phantoms, FF estimation bias increased as iron concentration increased and particle size decreased, with 0.71μm iron particle having the lowest bias (≤ 20%), and 0.52 μm and 0.38 μm iron particles producing higher bias (≥ 20%) for higher iron concentrations and lower FFs. Additionally,R 2 * $$ {R}_2^{\ast } $$ increased linearly with increasing iron concentration (r ≥ 0.87) and decreasing particle size. Iron particle size significantly influenced the estimated versus true FF (simulations: p = 0.04; phantoms: p = 0.03) andR 2 * $$ {R}_2^{\ast } $$ -iron concentration (simulations: p < 0.001; phantoms: p < 0.01) relationships. Heatmap demonstrated broader region with higher FF estimation bias as iron particle size decreased, especially at higher iron concentration.

CONCLUSION

R 2 * $$ {R}_2^{\ast } $$ and FF estimations are affected by iron particle size, with smaller particles leading to higherR 2 * $$ {R}_2^{\ast } $$ values and increased FF estimation bias.

Practical approach to quantitative liver and pancreas MRI in children

Quantitative abdominal magnetic resonance imaging (MRI) offers non-invasive, objective assessment of diseases in the liver, pancreas, and other organs and is increasingly being used in the pediatric population. Certain quantitative MRI techniques, such as liver proton density fat fraction (PDFF), R2* mapping, and MR elastography, are already in wide clinical use. Other techniques, such as liver T1 mapping and pancreas quantitative imaging methods, are emerging and show promise for enhancing diagnostic sensitivity and treatment monitoring. Quantitative imaging techniques have historically required a breath-hold, making them more difficult to implement in the pediatric population. However, technological advances, including free-breathing techniques and compressed sensing imaging, are making these techniques easier to implement. The purpose of this article is to review current liver and pancreas quantitative techniques and to provide a practical guide for implementing these techniques in pediatric practice. Future directions of liver and pancreas quantitative imaging will be briefly discussed.

Computed Tomography and Magnetic Resonance Imaging in Liver Iron Overload: From Precise Quantification to Prognosis Assessment

Liver iron overload is associated with conditions such as hereditary hemochromatosis, thalassemia major, and chronic liver diseases. The liver-related outcomes, patient outcomes, and treatment recommendations of these patients differ depending on the cause and extent of iron overload. Accurate quantification of the liver iron concentration (LIC) is critical for effective patient management. This review focuses on the application of computed tomography (CT) and magnetic resonance imaging (MRI) for the precise quantification and prognostic assessment of liver iron overload. In recent years, the use of dual-energy CT and the emergence of MRI-based sequences (such as UTE, QSM, Dixon, and CSE technologies) have significantly increased the potential for noninvasive liver iron quantification. However, the establishment of internationally standardized imaging parameters, postprocessing procedures, and reporting protocols is urgently needed for better management of patients with liver iron overload.

Recent Trends in Liver Cancer: Epidemiology, Risk Factors, and Diagnostic Techniques

Liver cancer, particularly hepatocellular carcinoma (HCC), poses a significant global health challenge due to its high mortality rate. Hepatocellular carcinoma and intrahepatic cholangiocarcinoma (ICC) are the two main types of primary liver cancer (PLC), each with its own set of complexities. Secondary or metastatic liver cancer is more common than PLC. It is frequently observed in malignancies such as colorectal, pancreatic, melanoma, lung, and breast cancer. Liver cancer is often diagnosed at an advanced stage, making it difficult to treat. This highlights the need for focused research on early detection and effective treatment strategies. This review explores the epidemiology, risk factors, and diagnostic techniques for HCC. The development of HCC involves various risk factors, including chronic liver diseases, hepatitis B and C infections, alcohol consumption, obesity, smoking, and genetic predispositions. Various invasive and non-invasive diagnostic techniques, such as biopsy, liquid biopsy, and imaging modalities like ultrasonography, computed tomography scans (CT scans), magnetic resonance imaging (MRI), and positron emission tomography (PET) scans, are utilized for HCC detection and monitoring. Advances in imaging technology and biomarker research have led to more accurate and sensitive methods for early HCC detection. We also reviewed advanced research on emerging techniques, including next-generation sequencing, metabolomics, epigenetic biomarkers, and microbiome analysis, which show great potential for advancing early diagnosis and personalized treatment strategies. This literature review provides insights into the current state of liver cancer diagnosis and promising future advancements. Ongoing research and innovation in these areas are essential for improving early diagnosis and reducing the global burden of liver cancer.

Multiparametric magnetic resonance imaging of the liver and spleen in Gaucher disease

PURPOSE

To assess liver and spleen characteristics of a population with Gaucher disease (GD) using multiparametric MRI and MR elastography (MRE) for evaluation of diffuse liver and spleen disease, which includes liver fat fraction, liver and spleen volume and iron deposition, and liver and spleen stiffness correlated with DS3 Severity Scoring System for Gaucher disease (GD-DS3).

METHODS

We prospectively evaluated 41 patients with type 1 Gaucher disease using a 3.0 T MRI and MRE between January 2019 and February 2020. Clinical, laboratory, and imaging data was collected. Mann-Whitney, Kruskal-Wallis, and Spearman's correlation were applied to evaluate liver and spleen MRI and MRE, clinical and laboratory variables, and GD-DS3. ERT and SRT treatment groups were compared.

RESULTS

Hepatomegaly was seen in 15% and splenomegaly in 42% of the population. Moderate and strong and correlations were found between liver and spleen iron overload (rho = 0.537; p = 0.002); between liver and spleen volume (rho = 0.692, p < 0.001) and between liver and spleen stiffness (rho = 0.453, p = 0.006). Moderate correlations were found between liver stiffness and GD-DS3 (rho = 0.559; p < 0.001) and between splenic volume and GD-DS3 (rho = 0.524; p = 0.001).

CONCLUSION

The prevalence of hepatosplenomegaly, liver fibrosis, and liver iron overload in treated patients with GD is low, which may be related to the beneficial effect of treatment. Liver MRE and splenic volume correlate with severity score and may be biomarkers of disease severity.

Application of the magnetic resonance 3D multiecho Dixon sequence for quantifying hepatic iron overload and steatosis in patients with thalassemia

OBJECTIVE

To investigate the feasibility and diagnostic efficacy of a 3D multiecho Dixon (qDixon) research application for simultaneously quantifying the liver iron concentration (LIC) and steatosis in thalassemia patients.

MATERIALS AND METHODS

This prospective study enrolled participants with thalassemia who underwent 3 T MRI of the liver for the evaluation of hepatic iron overload. The imaging protocol including qDixon and conventional T2* mapping based on 2D multiecho gradient echo (ME GRE) sequences respectively. Regions of interest (ROIs) were drawn in the liver on the qDixon maps to obtain R2* and proton density fat fraction (PDFF). The reference R2* value was measured and calculated on conventional T2* mapping using the CMRtools software. Correlation analysis, Linear regression analysis, and Bland-Altman analysis were performed.

RESULTS

84 patients were finally included in this study. The median R2*-ME-GRE was 366.97 (1/s), range [206.68 (1/s), 522.20 (1/s)]. 8 patients had normal hepatic iron deposition, 16 had Insignificant, 42 had mild, 18 had moderate. The median of R2*-qDixon was 376.88 (1/s) [219.33 (1/s), 491.75 (1/s)]. A strong correlation was found between the liver R2*-qDixon and the R2*-ME-GRE (r = 0.959, P < 0.001). The median value of PDFF was 1.76% (1.10%, 2.95%). 8 patients had mild fatty liver, and 1 had severe fatty liver.

CONCLUSION

MR qDixon research sequence can rapidly and accurately quantify liver iron overload, that highly consistent with the measured via conventional GRE sequence, and it can also simultaneously detect hepatic steatosis, this has great potential for clinical evaluation of thalassemia patients.

Liver disease in patients with transfusion-dependent β-thalassemia: The emerging role of metabolism dysfunction-associated steatotic liver disease

In this Editorial, we highlight the possible role that metabolism dysfunction-associated steatotic liver disease (MASLD) may play in the future, regarding liver disease in patients with transfusion-dependent β-thalassemia (TDBT). MASLD is characterized by excessive accumulation of fat in the liver (hepatic steatosis), in the presence of cardiometabolic factors. There is a strong correlation between the occurrence of MASLD and insulin resistance, while its increased prevalence parallels the global epidemic of diabetes mellitus (DM) and obesity. Patients with TDBT need regular transfusions for life to ensure their survival. Through these transfusions, a large amount of iron is accumulated, which causes saturation of transferrin and leads to the circulation of free iron molecules, which cause damage to vital organs (primarily the liver and myocardium). Over the past, the main mechanisms for the development of liver disease in these patients have been the toxic effect of iron on the liver and chronic hepatitis C, for which modern and effective treatments have been found, resulting in successful treatment. Additional advances in the treatment and monitoring of these patients have led to a reduction in deaths, and an increase in their life expectancy. This increased survival makes them vulnerable to the onset of diseases, which until recently were mainly related to the non-thalassemic general population, such as obesity and DM. There is insufficient data in the literature regarding the prevalence of MASLD in this population or on the risk factors for its occurrence. However, it was recently shown by a study of 45 heavily transfused patients with beta-thalassemia (Padeniya et al, BJH), that the presence of steatosis is a factor influencing the value of liver elastography and thus liver fibrosis. These findings suggest that future research in the field of liver disease in patients with TDBT should be focused on the occurrence, the risk factors, and the effect of MASLD on these patients.

User Engagement, Acceptability, and Clinical Markers in a Digital Health Program for Nonalcoholic Fatty Liver Disease: Prospective, Single-Arm Feasibility Study

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) has become the most common chronic liver disease in the world. Common comorbidities are central obesity, type 2 diabetes mellitus, dyslipidemia, and metabolic syndrome. Cardiovascular disease is the most common cause of death among people with NAFLD, and lifestyle changes can improve health outcomes.

OBJECTIVE

This study aims to explore the acceptability of a digital health program in terms of engagement, retention, and user satisfaction in addition to exploring changes in clinical outcomes, such as weight, cardiometabolic risk factors, and health-related quality of life.

METHODS

We conducted a prospective, open-label, single-arm, 12-week study including 38 individuals with either a BMI >30, metabolic syndrome, or type 2 diabetes mellitus and NAFLD screened by FibroScan. An NAFLD-specific digital health program focused on disease education, lowering carbohydrates in the diet, food logging, increasing activity level, reducing stress, and healthy lifestyle coaching was offered to participants. The coach provided weekly feedback on food logs and other in-app activities and opportunities for participants to ask questions. The coaching was active throughout the 12-week intervention period. The primary outcome was feasibility and acceptability of the 12-week program, assessed through patient engagement, retention, and satisfaction with the program. Secondary outcomes included changes in weight, liver fat, body composition, and other cardiometabolic clinical parameters at baseline and 12 weeks.

RESULTS

In total, 38 individuals were included in the study (median age 59.5, IQR 46.3-68.8 years; n=23, 61% female). Overall, 34 (89%) participants completed the program and 29 (76%) were active during the 12-week program period. The median satisfaction score was 6.3 (IQR 5.8-6.7) of 7. Mean weight loss was 3.5 (SD 3.7) kg (P<.001) or 3.2% (SD 3.4%), with a 2.2 (SD 2.7) kg reduction in fat mass (P<.001). Relative liver fat reduction was 19.4% (SD 23.9%). Systolic blood pressure was reduced by 6.0 (SD 13.5) mmHg (P=.009). The median reduction was 0.14 (IQR 0-0.47) mmol/L for triglyceride levels (P=.003), 3.2 (IQR 0.0-5.4) µU/ml for serum insulin (s-insulin) levels (P=.003), and 0.5 (IQR -0.7 to 3.8) mmol/mol for hemoglobin A1c (HbA1c) levels (P=.03). Participants who were highly engaged (ie, who used the app at least 5 days per week) had greater weight loss and liver fat reduction.

CONCLUSIONS

The 12-week-long digital health program was feasible for individuals with NAFLD, receiving high user engagement, retention, and satisfaction. Improved liver-specific and cardiometabolic health was observed, and more engaged participants showed greater improvements. This digital health program could provide a new tool to improve health outcomes in people with NAFLD.

TRIAL REGISTRATION

Clinicaltrials.gov NCT05426382; https://clinicaltrials.gov/study/NCT05426382.

Quantitative MRI of diffuse liver diseases: techniques and tissue-mimicking phantoms

Quantitative magnetic resonance imaging (MRI) techniques are emerging as non-invasive alternatives to biopsy for assessment of diffuse liver diseases of iron overload, steatosis and fibrosis. For testing and validating the accuracy of these techniques, phantoms are often used as stand-ins to human tissue to mimic diffuse liver pathologies. However, currently, there is no standardization in the preparation of MRI-based liver phantoms for mimicking iron overload, steatosis, fibrosis or a combination of these pathologies as various sizes and types of materials are used to mimic the same liver disease. Liver phantoms that mimic specific MR features of diffuse liver diseases observed in vivo are important for testing and calibrating new MRI techniques and for evaluating signal models to accurately quantify these features. In this study, we review the liver morphology associated with these diffuse diseases, discuss the quantitative MR techniques for assessing these liver pathologies, and comprehensively examine published liver phantom studies and discuss their benefits and limitations.

Comparing magnetic resonance liver fat fraction measurements with histology in fibrosis: the difference between proton density fat fraction and tissue mass fat fraction

OBJECTIVE

Magnetic resonance spectroscopy (MRS) provides a powerful method of measuring fat fraction. However, previous studies have shown that MRS results give lower values compared with visual estimates from biopsies in fibrotic livers. This study investigated these discrepancies and considered whether a tissue water content correction, as assessed by MRI relaxometry, could provide better agreement.

MATERIALS AND METHODS

110 patients were scanned in a 1.5 T Philips scanner and biopsies were obtained. Multiple echo MRS (30 × 30 ×  30 mm volume) was used to determine Proton Density Fat Fraction (PDFF). Biopsies were assessed by visual assessment for fibrosis and steatosis grading. Digital image analysis (DIA) was also used to quantify fat fraction within tissue samples. T1 relaxation times were then used to estimate tissue water content to correct PDFF for confounding factors.

RESULTS

PDFF values across the four visually assessed steatosis grades were significantly less in the higher fibrosis group (F3-F4) compared to the lower fibrosis group (F0-F2). The slope of the linear regression of PDFF vs DIA fat fraction was ~ 1 in the low fibrosis group and 0.77 in the high fibrosis group. Correcting for water content based on T1 increased the gradient but it did not reach unity.

DISCUSSION

In fibrotic livers, PDFF underestimated fat fraction compared to DIA methods. Values were improved by applying a water content correction, but fat fractions were still underestimated.

Quantification of Liver Iron Overload with MRI: Review and Guidelines from the ESGAR and SAR

Accumulation of excess iron in the body, or systemic iron overload, results from a variety of causes. The concentration of iron in the liver is linearly related to the total body iron stores and, for this reason, quantification of liver iron concentration (LIC) is widely regarded as the best surrogate to assess total body iron. Historically assessed using biopsy, there is a clear need for noninvasive quantitative imaging biomarkers of LIC. MRI is highly sensitive to the presence of tissue iron and has been increasingly adopted as a noninvasive alternative to biopsy for detection, severity grading, and treatment monitoring in patients with known or suspected iron overload. Multiple MRI strategies have been developed in the past 2 decades, based on both gradient-echo and spin-echo imaging, including signal intensity ratio and relaxometry strategies. However, there is a general lack of consensus regarding the appropriate use of these methods. The overall goal of this article is to summarize the current state of the art in the clinical use of MRI to quantify liver iron content and to assess the overall level of evidence of these various methods. Based on this summary, expert consensus panel recommendations on best practices for MRI-based quantification of liver iron are provided.

Water-Fat Separated T1 Mapping in the Liver and Correlation to Hepatic Fat Fraction

(1) Background: T1 mapping in magnetic resonance imaging (MRI) of the liver has been proposed to estimate liver function or to detect the stage of liver disease, among others. Thus far, the impact of intrahepatic fat on T1 quantification has only been sparsely discussed. Therefore, the aim of this study was to evaluate the potential of water-fat separated T1 mapping of the liver. (2) Methods: A total of 386 patients underwent MRI of the liver at 3 T. In addition to routine imaging techniques, a 3D variable flip angle (VFA) gradient echo technique combined with a two-point Dixon method was acquired to calculate T1 maps from an in-phase (T1_in) and water-only (T1_W) signal. The results were correlated with proton density fat fraction using multi-echo 3D gradient echo imaging (PDFF) and multi-echo single voxel spectroscopy (PDFF_MRS). Using T1_in and T1_W, a novel parameter FF_T1 was defined and compared with PDFF and PDFF_MRS. Furthermore, the value of retrospectively calculated T1_W (T1_W_calc) based on T1_in and PDFF was assessed. Wilcoxon test, Pearson correlation coefficient and Bland-Altman analysis were applied as statistical tools. (3) Results: T1_in was significantly shorter than T1_W and the difference of both T1 values was correlated with PDFF (R = 0.890). FF_T1 was significantly correlated with PDFF (R = 0.930) and PDFF_MRS (R = 0.922) and yielded only minor bias compared to both established PDFF methods (0.78 and 0.21). T1_W and T1_W_calc were also significantly correlated (R = 0.986). (4) Conclusion: T1_W acquired with a water-fat separated VFA technique allows to minimize the influence of fat on liver T1. Alternatively, T1_W can be estimated retrospectively from T1_in and PDFF, if a Dixon technique is not available for T1 mapping.

Diagnostic value of T2 relaxation time for hepatic iron grading in rat model of fatty and fibrotic liver

The objective of this study was to assess the quantitative diagnostic value of T2 relaxation time for determining liver iron grades in the presence of fat and fibrosis. Sixty Sprague-Dawley (SD) male rats were randomly divided into control (10 rats) and model (50 rats) groups. The model group of coexisting iron, steatosis, and liver fibrosis was induced by intraperitoneal injection of carbon tetrachloride (CCl4) dissolved in edible vegetable oil (40% v/v). The control group received an intraperitoneal injection of 0.9% saline. All rats underwent multi-echo gradient and spin echo (M-GRASE) magnetic resonance imaging, and the T2 relaxation time of the liver was measured. The rats were killed immediately after imaging, and liver specimens were extracted for histological evaluation of steatosis, iron, and fibrosis. The relationship and differences between T2 relaxation time and liver fibrosis stage, as well as the pathological grade of hepatic steatosis, were assessed by Spearman's rank correlation coefficient, non-parametric Mann-Whitney test, and the Kruskal-Wallis test. The area under the receiver operating characteristic curve and interaction analysis were used to quantify the diagnostic performance of T2 relaxation time for detecting different degrees of liver iron grades. Six normal control rats and 34 model rats were included in this study. Fibrosis stages were F0 (n = 6), F1 (n = 6), F2 (n = 8), F3 (n = 10), and F4 (n = 10). Steatosis grades were S0 (n = 5), S1 (n = 8), S2 (n = 12), and S3 (n = 15). Hepatocyte or Kupffer cell iron grades were 0 (n = 7), 1 (n = 9), 2 (n = 12), 3 (n = 10), and 4 (n = 2). The liver fibrosis stages were positively correlated with the iron grades (P < 0.01), and the iron grades and fibrosis stages were negatively correlated with the T2 relaxation time (P < 0.01). The T2 relaxation times exhibited strongly significant differences among rats with different histologically determined iron grades (P < 0.01). Pairwise comparisons between each grade of liver iron indicated significant differences between all iron grades, except between grades 0 and 1, and between grades 1 and 2 (P > 0.05). The T2 relaxation time of the liver had an area under the receiving operating characteristic curve (AUC) of 0.965 (95% CI 0.908-0.100, P < 0.001) for distinguishing rats with a pathological grade of hepatic iron (grade ≥ 1) from those without, an AUC of 0.871 (95% CI 0.757-0.985, P < 0.001) for distinguishing rats with no iron overload (grade ≤ 1) from rats with moderate or severe iron overload (grade ≥ 2), and an AUC of 0.939 (95% CI 0.865-1.000, P < 0.001) for distinguishing rats with no to moderate iron overload (grade ≤ 2) from rats with severe iron overload (grade 3). The interaction of different pathological grades of iron, steatosis, and fibrosis has a negligible influence on the T2 relaxation time (P > 0.05). In conclusion, T2 relaxation time can assess histologically determined liver iron grades, regardless of coexisting liver steatosis or fibrosis; therefore, it is suitable for distinguishing between the presence and absence of iron deposition and it is more accurate for higher iron grading.

MRI Appearance of Focal Lesions in Liver Iron Overload

Liver iron overload is defined as an accumulation of the chemical element Fe in the hepatic parenchyma that exceeds the normal storage. When iron accumulates, it can be toxic for the liver by producing inflammation and cell damage. This can potentially lead to cirrhosis and hepatocellular carcinoma, as well as to other liver lesions depending on the underlying condition associated to liver iron overload. The correct assessment of liver iron storage is pivotal to drive the best treatment and prevent complication. Nowadays, magnetic resonance imaging (MRI) is the best non-invasive modality to detect and quantify liver iron overload. However, due to its superparamagnetic properties, iron provides a natural source of contrast enhancement that can make challenging the differential diagnosis between different focal liver lesions (FLLs). To date, a fully comprehensive description of MRI features of liver lesions commonly found in iron-overloaded liver is lacking in the literature. Through an extensive review of the published literature, we aim to summarize the MRI signal intensity and enhancement pattern of the most common FLLs that can occur in liver iron overload.

Multi-echo Dixon and breath-hold T2-corrected multi-echo single-voxel MRS for quantifying hepatic iron overload in rabbits

BACKGROUND

Three-dimensional (3D) multi-echo-Dixon (ME-Dixon) and breath-hold T2-corrected multi-echo single-voxel MR spectroscopy (HISTO) can simultaneously quantify liver fat and liver iron. However, their diagnostic efficacy and application scope for quantitative iron in co-existing fatty liver have not been adequately evaluated.

PURPOSE

To evaluate the accuracy of ME-Dixon and HISTO for quantitative analysis of hepatic iron in rabbits with iron deposition and fatty liver using liver-iron concentration (LIC) as a reference standard.

MATERIAL AND METHODS

ME-Dixon, HISTO, and conventional two-dimensional multi-echo gradient echo (GRE) sequences were performed on 42 rabbits. The following parameters were calculated: R2* from ME-Dixon and GRE; proton density fat fraction (PDFF) from the ME-Dixon, HISTO (normal TE range), and HISTO-H (extended TE range); and R2_water from HISTO and HISTO-H. The LIC and liver-fat concentration (LFC) were measured through chemical analysis, and their relationship with the MRI parameters were assessed. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were used to evaluate the diagnostic efficiency.

RESULTS

LIC was significantly correlated with R2_HISTO-H, R2*_Dixon, and R2*_GRE (r = 0.858, 0.910, 0.931, respectively; P < 0.001) and weakly with R2_HISTO (r = 0.424; P = 0.008). A strong correlation was also observed between the LFC and PDFF obtained from HISTO, HISTO-H, and ME-Dixon (r = 0.776, 0.811, 0.888, respectively; P < 0.001). ME-Dixon showed the best performance with moderate iron overload (AUC = 0.983).

CONCLUSION

3D ME-Dixon is useful for quantifying the LIC, especially with co-existing fatty liver. Its diagnostic performance is also superior to that of the HISTO sequence.

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

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

Free-breathing 3D stack-of-radial MRI quantification of liver fat and R2* in adults with fatty liver disease

PURPOSE

To investigate the agreement, intra-session repeatability, and inter-reader agreement of liver proton-density fat fraction (PDFF) and R₂* quantification using free-breathing 3D stack-of-radial MRI, with and without self-gated motion compensation, compared to reference breath-hold techniques in subjects with fatty liver disease (FLD).

METHODS

In this institutional review board-approved prospective study, thirty-eight adults with FLD and/or iron overload (24 male, 58 ± 12 years) were imaged at 3T using free-breathing stack-of-radial MRI, breath-hold 3D Cartesian MRI, and breath-hold single-voxel MR spectroscopy (SVS). Each sequence was acquired twice in random order. To assess agreement compared to reference breath-hold techniques, the dependency of liver PDFF and/or R₂* quantification on the sequence, radial sampling factor, and radial self-gating temporal resolution was assessed by calculating the Bayesian mean difference (MD_B) of the posteriors. Intra-session repeatability and inter-reader agreement (two independent readers) were assessed by the coefficient of repeatability (CR) and intraclass correlation coefficient (ICC), respectively.

RESULTS

Thirty-five participants (21 male, 57 ± 12 years) were included for analysis. Both free-breathing radial MRI techniques (with and without self-gating) achieved ICC ≥ 0.92 for quantifying PDFF and R₂*, and quantified PDFF with MD_B < 1.2% compared to breath-hold techniques. Free-breathing radial MRI required self-gating to accurately quantify R₂* (MD_B < 10s^-1 with self-gating; MD_B < 50s^-1 without self-gating). The radial sampling factor affected PDFF and R₂* quantification while the radial self-gating temporal resolution only affected R₂* quantification. Repeated self-gated free-breathing radial MRI scans achieved CR < 3% and CR < 27 s^-1 for PDFF and R₂*, respectively.

CONCLUSION

A free-breathing stack-of-radial MRI technique with self-gating demonstrated agreement, repeatability, and inter-reader agreement compared to reference breath-hold techniques for quantification of liver PDFF and R₂* in adults with FLD.

Precise whole liver automatic segmentation and quantification of PDFF and R2* on MR images

OBJECTIVE

To automate the segmentation of whole liver parenchyma on multi-echo chemical shift encoded (MECSE) MR examinations using convolutional neural networks (CNNs) to seamlessly quantify precise organ-related imaging biomarkers such as the fat fraction and iron load.

METHODS

A retrospective multicenter collection of 183 MECSE liver MR examinations was conducted. An encoder-decoder CNN was trained (107 studies) following a 5-fold cross-validation strategy to improve the model performance and ensure lack of overfitting. Proton density fat fraction (PDFF) and R2* were quantified on both manual and CNN segmentation masks. Different metrics were used to evaluate the CNN performance over both unseen internal (46 studies) and external (29 studies) validation datasets to analyze reproducibility.

RESULTS

The internal test showed excellent results for the automatic segmentation with a dice coefficient (DC) of 0.93 ± 0.03 and high correlation between the quantification done with the predicted mask and the manual segmentation (rPDFF = 1 and rR2* = 1; p values < 0.001). The external validation was also excellent with a different vendor but the same magnetic field strength, proving the generalization of the model to other manufacturers with DC of 0.94 ± 0.02. Results were lower for the 1.5-T MR same vendor scanner with DC of 0.87 ± 0.06. Both external validations showed high correlation in the quantification (rPDFF = 1 and rR2* = 1; p values < 0.001). In both internal and external validation datasets, the relative error for the PDFF and R2* quantification was below 4% and 1% respectively.

CONCLUSION

Liver parenchyma can be accurately segmented with CNN in a vendor-neutral virtual approach, allowing to obtain reproducible automatic whole organ virtual biopsies.

KEY POINTS

• Whole liver parenchyma can be automatically segmented using convolutional neural networks. • Deep learning allows the creation of automatic pipelines for the precise quantification of liver-related imaging biomarkers such as PDFF and R2*. • MR "virtual biopsy" can become a fast and automatic procedure for the assessment of chronic diffuse liver diseases in clinical practice.

Attenuation Imaging with Ultrasound as a Novel Evaluation Method for Liver Steatosis

In recent years, ultrasound attenuation imaging (ATI) has emerged as a new method to detect liver steatosis. However, thus far, no studies have confirmed the clinical utility of this technology. Using a retrospective database analysis of 28 patients with chronic liver disease who underwent ultrasound liver biopsy and ATI, we compared the presence and degree of steatosis measured by ATI with the results obtained through liver biopsy. The area under the receiver operating characteristic curve (AUROC) of the ATI for differentiating between normal and hepatic steatosis was 0.97 (95% confidence interval: 0.83–1.00). The AUROC of the ATI was 0.99 (95% confidence interval: 0.86–1.00) in grade ≥2 liver steatosis and 0.97 (95% confidence interval: 0.82–1.00) in grade 3. ATI showed good consistency and accuracy for the steatosis grading of liver biopsy. Therefore, ATI represents a novel diagnostic measurement to support the diagnosis of liver steatosis in non-invasive clinical practice.

MR imaging assessment and quantification of liver iron

Iron overload is a common clinical problem resulting from hereditary hemochromatosis or secondary hemosiderosis (mainly associated with transfusion therapy), being also associated with chronic liver diseases and metabolic disorders. Excess of iron accumulates in organs like the liver, pancreas and heart. Without treatment, patients with iron overload disorders will develop liver cirrhosis, diabetes and cardiomyopathy. Iron quantification is therefore crucial not only for diagnosis of iron overload but also to monitor iron-reducing therapies. Liver iron concentration is considered the surrogate marker of total body iron stores. Because liver biopsy is invasive and prone to high variability and sampling bias, MR imaging has emerged as a non-invasive method and gained wide acceptance, now being considered the standard of care for assessing iron overload. Nevertheless, there are different MR techniques for iron quantification and there is still no consensus about the best technique or postprocessing tool for hepatic iron quantification, with the choice of imaging technique depending mainly on the local expertise as well on the available equipment and software. Because different methods should not be used interchangeably, it is important to choose one method and use the same one when following up patients over time.

Magnetic Resonance imaging analysis of liver fibrosis and inflammation: overwhelming gray zones restrict clinical use

Magnetic resonance (MR) identification and grading of subjects with liver fibrosis and inflammation represents a clinical challenge. MR elastography plays a well-defined role in fibrosis estimation, but its use is not widely available in clinical settings. Given that liver MR is becoming the reference standard for fat and iron quantitation, there is a need to clarify whether there is any role for MR imaging in the concomitant evaluation of fibrosis and inflammation in this setting. This review summarizes the diagnostic estimations of different MR imaging parameters obtained from conventional non-contrast-enhanced multiple b values diffusion-weighted acquisitions, variable flip angles T1 relaxation maps and STIR images. Although some derived parameters have shown a significant correlation to histological scores, a small magnitude of effect with wide overlap across severity grades is the rule. Contrary to fat and iron quantification, the low precision and reproducibility of MR imaging metrics limits its clinical relevance in fibrosis and inflammation assessment. In a sequential clinical approach combining different methodologies, MR imaging has no applicability for ruling-out and low accuracy for ruling-in advanced fibrosis. Thereby, MR elastography remains as the only image method with high diagnostic accuracy for the detection of advanced fibrosis. Until date, inflammation remains in a gray zone where biopsy cannot be replaced, and further investigations are needed. The present review offers an in-depth discuss of the MR imaging diagnostic performance for the evaluation of liver fibrosis and inflammation, highlighting the need for scientific improvements.

Differences in multi-echo chemical shift encoded MRI proton density fat fraction estimation based on multifrequency fat peaks selection in non-alcoholic fatty liver disease patients

AIM

To compare the performance of multi-echo chemical-shift-encoded (MECSE) magnetic resonance imaging (MRI) proton density fat fraction (PDFF) estimation, considering three different fat frequency peak combinations, for the quantification of steatosis in patients with non-alcoholic fatty liver disease (NAFLD).

MATERIALS AND METHODS

The present study was a prospective cross-sectional research of 121 patients with metabolic syndrome and evidence of hepatic steatosis on ultrasound, who underwent a 3 T MRI examination. All patients were studied with a multifrequency MECSE sequence. The PDFF was calculated using six peaks (MECSE_p123456), three peaks (MECSE_p456), and a single peak (MECSE_p5) model. The two simpler fat peak models were compared to the six peaks model, which was considered the reference standard. Linearity was evaluated using linear regression while agreement was described using Bland-Altman analysis.

RESULTS

The mean age was 47 (±9) years and BMI was 29.9 (±2.9) kg/m². Steatosis distribution was 15%/31%/54% (S1/S2/S3, respectively). Compared to MECSE_p123456, both models provided linear PDFF measurements (R₂= 0.99 and 0.97, MECSE_p456 and MECSE_p5 respectively). Regression slope (0.92; p<0.001) and mean Bland-Altman bias (-1.5%; 95% limits of agreement: -3.19%, 0.22%) indicated minimal underestimation by using PDFF-MECSE_p456. Nonetheless, mean differences in PDFF estimations varied from -1.5% (MECSE_p456,p=0.006) to -2.2% (MECSE_p5,p<0.001) when compared to full six fat frequencies model.

CONCLUSION

Although simpler spectral fat MECSE analysis shows a linear relationship with the standard six peaks model, their variation in estimated PDFF values introduces a low but clinically significant bias in fat quantification and steatosis grading in NAFLD patients.

Accuracy of common proton density fat fraction thresholds for magnitude- and complex-based chemical shift-encoded MRI for assessing hepatic steatosis in patients with obesity

PURPOSE

MRI proton density fat fraction (PDFF) can be calculated using magnitude (MRI-M) or complex (MRI-C) MRI data. The purpose of this study was to identify, assess, and compare the accuracy of common PDFF thresholds for MRI-M and MRI-C for assessing hepatic steatosis in patients with obesity, using histology as reference.

METHODS

This two-center prospective study included patients undergoing MRI-C- and MRI-M-PDFF estimations within 3 days before weight loss surgery. Liver biopsy was performed, and histology-determined steatosis grades were used as reference standard. Using receiver operating characteristics (ROC) analysis on data pooled from both methods, single common thresholds for diagnosing and differentiating none or mild (0-1) from moderate to severe steatosis (2-3) were selected as the ones achieving the highest sensitivity while providing at least 90% specificity. Selection methods were cross-validated. Performances were compared using McNemar's tests.

RESULTS

Of 81 included patients, 54 (67%) had steatosis. The common PDFF threshold for diagnosing steatosis was 5.4%, which provided a cross-validated 0.88 (95% CI 0.77-0.95) sensitivity and 0.92 (0.75-0.99) specificity for MRI-M and 0.87 sensitivity (0.75-0.94) with 0.81 (0.61-0.93) specificity for MRI-C. The common PDFF threshold to differentiate steatosis grades 0-1 from 2 to 3 was 14.7%, which provided cross-validated 0.86 (95% CI 0.59-0.98) sensitivity and 0.95 (0.87-0.99) specificity for MRI-M and 0.93 sensitivity (0.68-0.99) with 0.97(0.89-0.99) specificity for MRI-C.

CONCLUSION

If independently validated, diagnostic thresholds of 5.4% and 14.7% could be adopted for both techniques for detecting and differentiating none to mild from moderate to severe steatosis, respectively, with high diagnostic accuracy.

Quantifying steatosis in the liver and pancreas with MRI in patient with chronic liver disease

AIM

To compare pancreatic and hepatic steatosis quantified by proton density fat fraction (PDFF) on magnetic resonance imaging (MRI) in patients with chronic liver disease.

MATERIAL AND METHODS

This cross-sectional study included 46 adult patients who underwent liver biopsy for chronic viral hepatitis (n=19) or other chronic non-alcoholic liver diseases (NALD) (n=27). Liver biopsy was used as the gold standard for diagnosing and grading hepatic steatosis. All patients underwent clinical evaluation and MRI with a multi-echo chemical shift-encoded (MECSE) gradient-echo sequence for liver and pancreas PDFF quantification. We used Spearman's correlation coefficient to determine the degree of association between hepatic PDFF and steatosis grade, and between pancreatic PDFF and steatosis grade and hepatic PDFF. To compare the chronic viral hepatitis group and the NALD group, we used t-tests for continuous or ordinal variables and chi-square tests for categorical variables.

RESULTS

Hepatic PDFF measurements correlated with steatosis grades (R_S=0.875, p<0.001). Pancreatic PDFF correlated with hepatic steatosis grades (R_S=0.573, p<0.001) and hepatic PDFF measurements (R_S=0.536, p<0.001). In the subgroup of patients with chronic NALD, the correlations remained significant between pancreatic PDFF and hepatic PDFF (R_S=0.632, p<0.001) and between pancreatic PDFF and liver steatosis (R_S=0.608, p<0.001); however, in the subgroup of patients with viral hepatitis these correlations were no longer significant.

CONCLUSION

Pancreatic fat deposition correlates with hepatic steatosis in patients with chronic NALD, but not in those with chronic viral hepatitis.

Detection of hepatic steatosis and iron content at 3 Tesla: comparison of two-point Dixon, quantitative multi-echo Dixon, and MR spectroscopy

PURPOSE

To compare qualitative results obtained from computer-aided dual-ratio analysis on T1-weighted two-point Dixon, with T2*-corrected multi-echo Dixon and T2-corrected multi-echo single-voxel MR spectroscopy sequence (MRS) for evaluation of liver fat and iron at 3T.

METHODS AND MATERIALS

This retrospective, HIPAA-compliant, IRB-approved study included 479 patients with known or suspected liver disease. Two-point Dixon, multi-echo Dixon, and MR spectroscopy sequences were performed for each patient at 3T. A receiver-operating characteristic analysis was performed to compare the diagnostic performance in 80 patients using biopsy as the standard. Sensitivity, specificity, PPV, and NPV of qualitative two-point Dixon results, multi-echo Dixon (PDFF and R2*), and MRS (fat fraction and R2 water) for detection of hepatic steatosis and siderosis were assessed.

RESULTS

Fat fractions obtained from MRS and multi-echo Dixon have equivalent accuracy for detection of hepatic steatosis (AUC, sensitivity and specificity: 0.90 vs 0.88, 0.77 vs. 0.82, and 0.90 vs. 0.82), but the optimal cutoff value is higher for MRS (6.05% vs. 3.4%). The dual-ratio Dixon discrimination technique showed high negative predictive value for detection of hepatic steatosis and siderosis (0.90 and 0.94, respectively). R2* from multi-echo Dixon and R2_water from MRS have equivalent accuracy for detection of iron overload at 3T (AUC 0.89 vs. 0.88). The optimal cutoff for R2* and R2_water are 60.5 s^-1 and 40.85 s^-1, respectively.

CONCLUSION

The computer-aided dual-ratio discrimination with two-point Dixon is a useful qualitative screening tool with high negative predictive value for hepatic steatosis and iron overload. Multi-echo Dixon and MRS have similar accuracy for detection of hepatic steatosis and iron overload at 3 Tesla.

Liver MRI susceptibility-weighted imaging (SWI) compared to T2* mapping in the presence of steatosis and fibrosis

PURPOSE

To show that both susceptibility-weighted imaging (SWI) and T2*-mapping are dependent on liver steatosis, which should be taken into account when using these parameters to grade liver fibrosis and cirrhosis.

METHODS

In this prospective study, a total of 174 patients without focal liver disease underwent multiparametric MRI at 3 T including SWI, T1- and T2* mapping, proton density fat fraction (PDFF) quantification and MR elastography. SWI, T2* and T1 were measured in the liver (4 locations), as well as in paraspinal muscles, to calculate the liver-to-muscle ratio (LMR). Liver and LMR values were compared among patients with different steatosis grades (PDFF < 5%, 5-10%, 10-20% and >20%), patients with normal, slightly increased and increased liver stiffness (<2.8 kPa, 2.8-3.5 kPa and >3.5 kPa, respectively). ANOVA with Bonferroni-corrected post hoc tests as well as a multivariate analysis were used to compare values among groups and parameters.

RESULTS

SWI and T2* both differed significantly among groups with different steatosis grades (p < 0.001). However, SWI allowed a better differentiation among liver fibrosis grades (p < 0.001) than did T2* (p = 0.05). SWI LMR (p < 0.001) and T2* LMR (p = 0.036) showed a similar performance in differentiating among liver fibrosis grades.

CONCLUSION

SWI and T2*-mapping are strongly dependent on the liver steatosis grades. Nevertheless, both parameters are useful predictors for liver fibrosis when using a multiparametric approach.

3D Multi-Echo Dixon technique for simultaneous assessment of liver steatosis and iron overload in patients with chronic liver diseases: a feasibility study

BACKGROUND

Patients with chronic liver diseases (CLDs) often suffer from lipidosis or siderosis. Proton density fat fraction (PDFF) and R2* can be used as quantitative parameters to assess the fat/iron content of the liver. The aim of this study was to evaluate the influence of liver fibrosis and inflammation on the 3D Multi-echo Dixon (3D ME Dixon) parameters (MRI-PDFF and R2*) in patients with CLDs and to determine the feasibility of 3D ME Dixon technique for the simultaneous assessment of liver steatosis and iron overload using histopathologic findings as the reference standard.

METHODS

Ninety-nine consecutive patients with CLDs underwent T1-independent, T2*-corrected 3D ME Dixon sequence with reconstruction using multipeak spectral modeling on a 3T MR scanner. Liver specimen was reviewed in all cases, grading liver steatosis, siderosis, fibrosis, and inflammation. Spearman correlation analysis was performed to determine the relationship between 3D ME Dixon parameters (MRI-PDFF and R2*) and histopathological and biochemical features [liver steatosis, iron overload, liver fibrosis, inflammation, alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBIL)]. Multiple regression analysis was applied to identify variables associated with 3D ME Dixon parameters. Receiver operating characteristic (ROC) analysis was performed to determine the diagnostic performance of these parameters to differentiate liver steatosis or iron overload.

RESULTS

In multivariate analysis, only liver steatosis independently influenced PDFF values (R2=0.803, P<0.001), liver iron overload and fibrosis influenced R2* values (R2=0.647, P<0.001). The Spearman analyses showed that R2* values were moderately correlated with fibrosis stages (r=0.542, P<0.001) in the subgroup with the absence of iron overload. The area under the ROC curve of PDFF was 0.989 for the diagnosis of steatosis grade 1 or greater, and 0.986 for steatosis grade 2 or greater. The area under the ROC curve of R2* was 0.815 for identifying iron overload grade 1 or greater, and 0.876 for iron overload grade 2 or greater.

CONCLUSIONS

3D Multi-Echo Dixon can be used to simultaneously evaluate liver steatosis and iron overload in patients with CLDs, especially for quantification of liver steatosis. However, liver R2* value may be affected by the liver fibrosis in the setting of CLDs with absence of iron overload.

Liver R2* is affected by both iron and fat: A dual biopsy-validated study of chronic liver disease

BACKGROUND

Liver iron content (LIC) in chronic liver disease (CLD) is currently determined by performing an invasive liver biopsy. MRI using R2* relaxometry is a noninvasive alternative for estimating LIC. Fat accumulation in the liver, or proton density fat fraction (PDFF), may be a possible confounder of R2* measurements. Previous studies of the effect of PDFF on R2* have not used quantitative LIC measurement.

PURPOSE

To assess the associations between R2*, LIC, PDFF, and liver histology in patients with suspected CLD.

STUDY TYPE

Prospective.

POPULATION

Eighty-one patients with suspected CLD.

FIELD STRENGTH/SEQUENCE

1.5 T. Multiecho turbo field echo to quantify R2*. PRESS MRS to quantify PDFF.

ASSESSMENT

Each patient underwent an MR examination, followed by two needle biopsies immediately following the MR examination. The first biopsy was used for conventional histological assessment of LIC, whereas the second biopsy was used to quantitatively measure LIC using mass spectrometry. R2* was correlated with both LIC and PDFF. A correction for the influence of fat on R2* was calculated.

STATISTICAL TESTS

Pearson correlation, linear regression, and area under the receiver operating curve.

RESULTS

There was a positive linear correlation between R2* and PDFF (R = 0.69), after removing data from patients with elevated iron levels, as defined by LIC. R2*, corrected for PDFF, was the best method for identifying patients with elevated iron levels, with a correlation of R = 0.87 and a sensitivity and specificity of 87.5% and 98.6%, respectively.

DATA CONCLUSION

PDFF increases R2*.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:325-333.

Liver Iron Quantification with MR Imaging: A Primer for Radiologists

Iron overload is a systemic disorder and is either primary (genetic) or secondary (exogenous iron administration). Primary iron overload is most commonly associated with hereditary hemochromatosis and secondary iron overload with ineffective erythropoiesis (predominantly caused by β-thalassemia major and sickle cell disease) that requires long-term transfusion therapy, leading to transfusional hemosiderosis. Iron overload may lead to liver cirrhosis and hepatocellular carcinoma, in addition to cardiac and endocrine complications. The liver is one of the main iron storage organs and the first to show iron overload. Therefore, detection and quantification of liver iron overload are critical to initiate treatment and prevent complications. Liver biopsy was the historical reference standard for detection and quantification of liver iron content. Magnetic resonance (MR) imaging is now commonly used for liver iron quantification, including assessment of distribution, detection, grading, and monitoring of treatment response in iron overload. Several MR imaging techniques have been developed for iron quantification, each with advantages and limitations. The liver-to-muscle signal intensity ratio technique is simple and widely available; however, it assumes that the reference tissue is normal. Transverse magnetization (also known as R2) relaxometry is validated but is prone to respiratory motion artifacts due to a long acquisition time, is presently available only for 1.5-T imaging, and requires additional cost and delay for off-line analysis. The R2* technique has fast acquisition time, demonstrates a wide range of liver iron content, and is available for 1.5-T and 3.0-T imaging but requires additional postprocessing software. Quantitative susceptibility mapping has the highest sensitivity for detecting iron deposition; however, it is still investigational, and the correlation with liver iron content is not yet established. ^©RSNA, 2018.

Validation of water-fat MRI and proton MRS in assessment of hepatic fat and the heterogeneous distribution of hepatic fat and iron in subjects with non-alcoholic fatty liver disease

BACKGROUND

Research studies demonstrated pathologic lesions were unevenly distributed in patients with non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis. As hepatic steatosis occurs prior to steatohepatitis and other late stage liver conditions, the distribution pattern of hepatic fat and iron concentration should be investigated to prevent sampling variability. The first purpose of this study was to perform comparison and validation of in-house hepatic fat measurements using water-fat MRI and MRS. The second objective was to quantify hepatic fat-fraction and T2* values in left and right liver lobes using water-fat MRI.

METHOD

Fifty-four non-alcoholic adults (27 NAFLD, age: 42.8 ± 11.8), 27 non-NAFLD, age: 45.5 ± 11.2) and 46 non-alcoholic teenagers (23 NAFLD (age: 15.4 ± 2.6), 23 non-NAFLD (age: 13.9 ± 2.3) were recruited. All participants underwent chemical shift water-fat MRI and 1H MRS at 3 T. Hepatic steatosis was defined by intrahepatic triglyceride more than the threshold of 5.56% using MRS (clinical reference) and non-alcoholic was defined by alcohol ingestion of no more than 30 g and 20 g per day for male and female respectively. Hepatic fat-fractions in left and right liver lobes were measured using regions-of-interest (ROIs) approach. Three ROIs were drawn on the fat-fraction images and duplicated on to the co-registered T2* images at the inferior right, superior right and superior left liver lobes. Comparison and validation of water-fat MRI and MRS were performed using intraclass correlation coefficient (ICC) and Bland-Altman plot. Hepatic fat-fraction and T2* measured from the ROIs were compared using repeated measures ANOVA. Independent t-test was used for between groups analysis.

RESULTS

Statistical analysis indicated good correlation (R = 0.987) and agreement (ICC = 0.982) between MRS and water-fat MRI in hepatic fat measurements. Results indicated that hepatic fat was significantly higher in the right lobe compared to the left in NAFLD adults (p < 0.001) and NAFLD teenagers (p < 0.001). For T2*, significant difference between left and right lobes was observed in NAFLD adults (p < 0.001) and non-NAFLD adults (p < 0.001) but not in teenagers.

CONCLUSION

Hepatic fat measurements using MRS and water-fat MRI are statistically equivalent. In subjects with NAFLD regardless of their age, hepatic fat is stored preferentially in the right live lobe probably due to the streamline of blood flow to the right liver. T2* value is significantly higher in the right liver lobe in adults but not in the teenagers regardless of their hepatic fat contents probably due to the longer time span of hepatic iron accumulation.

Evaluation of liver function using gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid enhanced magnetic resonance imaging based on a three-dimensional volumetric analysis system

Background

Magnetic resonance imaging with gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (EOB-MRI) is a diagnostic modality for liver tumors. Three-dimensional (3D) volumetric analysis systems using EOB-MRI data are used to simulate liver anatomy for surgery. This study was conducted to investigate clinical utility of a 3D volumetric analysis system on EOB-MRI to evaluate liver function.

Methods

Between August 2014 and December 2015, 181 patients underwent laboratory and radiological exams as standardized preoperative evaluation for liver surgery. The liver-spleen contrast-enhanced ratio (LSR) was measured by a semi-automated 3D volumetric analysis system on EOB-MRI. First, the inter-evaluator variability of the calculated LSR was evaluated. Additionally, a subset of liver surgical specimens was evaluated histologically by using immunohistochemical staining. Finally, the correlations between the LSR and grading systems of liver function, laboratory data, or histological findings were analyzed.

Results

The inter-evaluator correlation coefficient of the measured LSR was 0.986. The mean LSR was significantly correlated with the Child–Pugh score (p = 0.014) and the ALBI score (p < 0.001). Significant correlations were also observed between the LSR and indocyanine green retention rate at 15 min (r = − 0.601, p < 0.001), between the LSR and liver fibrosis stage (r = − 0.556, p < 0.001), and between the LSR and liver steatosis grade (r = − 0.396, p < 0.001).

Conclusion

The LSR calculated by a 3D volumetric analysis system on EOB-MRI was highly reproducible and was shown to be correlated with liver function parameters and liver histology. These data suggest that this imaging modality can be a reliable tool to evaluate liver function.

Electronic supplementary material

The online version of this article (10.1007/s12072-018-9874-x) contains supplementary material, which is available to authorized users.

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.

Quantitative susceptibility mapping in combination with water-fat separation for simultaneous liver iron and fat fraction quantification

PURPOSES

To evaluate the feasibility of simultaneous quantification of liver iron concentration (LIC) and fat fraction (FF) using water-fat separation and quantitative susceptibility mapping (QSM).

METHODS

Forty-five patients suspected of liver iron overload (LIO) were included. A volumetric interpolated breath-hold examination sequence for QSM and FF, a fat-saturated gradient echo sequence for R₂^*, a spin echo sequence for LIC measurements and MRS analyses for FF (FF-MRS) were performed. Magnetic susceptibility and FF were calculated using a water-fat separation method (FF-MRI). Correlation and receiver operating characteristic analyses were performed.

RESULTS

Magnetic susceptibility showed strong correlation with LIC (r_s=0.918). The optimal susceptibility cut-off values were 0.34, 0.63, 1.29 and 2.23 ppm corresponding to LIC thresholds of 1.8, 3.2, 7.0 and 15.0 mg/g dry weight. The area under the curve (AUC) were 0.948, 0.970, 1 and 1, respectively. No difference in AUC was found between susceptibility and R₂^* at all LIC thresholds. Correlation was found between FF-MRI and FF-MRS (R²=0.910).

CONCLUSIONS

QSM has a high diagnostic performance for LIC quantification, similar to that of R₂^*. FF-MRI provides simultaneous fat quantification. Findings suggest QSM in combination with water-fat separation has potential value for evaluating LIO, especially in cases with coexisting steatosis.

KEY POINTS

• Magnetic susceptibility showed strong correlation with LIC (r _s =0.918). • QSM showed high diagnostic performance for LIC, similar to that of R ₂^* . • Simultaneously estimated FF-MRI showed strong correlation with MR-Spectroscopy-based FF (R ² =0.910). • QSM combining water-fat separation has quantitative value for LIO with coexisted steatosis.

Tissue iron quantification in chronic liver diseases using MRI shows a relationship between iron accumulation in liver, spleen, and bone marrow

AIM

To investigate iron loading within the liver, pancreas, spleen, and bone marrow using magnetic resonance imaging (MRI) transverse relaxation rate (R2*), in patients with diffuse liver diseases; to evaluate the relationships between iron accumulation in these tissue compartments; and to assess the association between tissue iron overload and the pattern of hepatic cellular iron distribution (hepatocytes versus Kupffer cells).

MATERIAL AND METHODS

Fifty-six patients with diffuse liver diseases had MRI-derived R2* values, using a multi-echo chemical-shift encoded MRI sequence, of the liver, pancreas, spleen, and vertebral bone marrow. All patients had liver biopsy samples scored for hepatic iron grading (0-4) and iron cellular distribution (within hepatocytes only or within both hepatocytes and Kupffer cells).

RESULTS

Liver R2* increased with histological iron grade (R_S=0.58, p<0.001) and correlated with spleen (R_S=0.71, p<0.001) and bone marrow R2* (R_S=0.66, p<0.001), but not with pancreatic R2* (R_S=0.22, p=0.096). Splenic and bone marrow R2* values were also correlated (R_S=0.72, p<0.001). Patients with iron inside Kupffer cells had the highest R2* in liver, spleen and bone marrow.

CONCLUSIONS

Patients with chronic diffuse liver diseases have concomitant hepatic, splenic, and bone marrow iron loading. The highest hepatic iron scores and iron inside Kupffer cells were associated with the highest splenic and bone marrow deposits, suggesting systemic iron accumulation in the mononuclear phagocytic system.

Liver MRI: From basic protocol to advanced techniques

Liver MR is a well-established modality with multiparametric capabilities. However, to take advantage of its full capacity, it is mandatory to master the technique and optimize imaging protocols, apply advanced imaging concepts and understand the use of different contrast media. Physiologic artefacts although inherent to upper abdominal studies can be minimized using triggering techniques and new strategies for motion control. For standardization, the liver MR protocol should include motion-resistant T2-w sequences, in-op phase GRE T1 and T2-w fast spin echo sequences with fat suppression. Diffusion-weighted imaging (DWI) is mandatory, especially for detection of sub-centimetre metastases. Contrast-enhanced MR is the cornerstone of liver MR, especially for lesion characterization. Although extracellular agents are the most extensively used contrast agents, hepatobiliary contrast media can provide an extra-layer of functional diagnostic information adding to the diagnostic value of liver MR. The use of high field strength (3T) increases SNR but is more challenging especially concerning artefact control. Quantitative MR belongs to the new and evolving field of radiomics where the use of emerging biomarkers such as perfusion or DWI can derive new information regarding disease detection, prognostication and evaluation of tumour response. This information can overcome some of the limitations of current tests, especially when using vascular disruptive agents for oncologic treatment assessment. MR is, today, a robust, mature, multiparametric imaging modality where clinical applications have greatly expanded from morphology to advanced imaging. This new concept should be acknowledged by all those involved in producing high quality, high-end liver MR studies.