Linearity, Bias, and Precision of Hepatic Proton Density Fat Fraction Measurements by Using MR Imaging: A Meta-Analysis

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

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

Advanced MRI techniques in abdominal imaging

Magnetic resonance imaging (MRI) is a crucial modality for abdominal imaging evaluation of focal lesions and tissue properties. However, several obstacles, such as prolonged scan times, limitations in patients' breath-hold capacity, and contrast agent-associated artifacts, remain in abdominal MR images. Recent techniques, including parallel imaging, three-dimensional acquisition, compressed sensing, and deep learning, have been developed to reduce the scan time while ensuring acceptable image quality or to achieve higher resolution without extending the scan duration. Quantitative measurements using MRI techniques enable the noninvasive evaluation of specific materials. A comprehensive understanding of these advanced techniques is essential for accurate interpretation of MRI sequences. Herein, we therefore review advanced abdominal MRI techniques.

Effect of particle size on liver MRI R 2 * relaxometry: Monte Carlo simulation and phantom studies

PURPOSE

To investigate the effect of particle size on liverR 2 * $$ {\mathrm{R}}_2^{\ast } $$ by Monte Carlo simulation and phantom studies at both 1.5 T and 3.0 T.

METHODS

Two kinds of particles (i.e., iron sphere and fat droplet) with varying sizes were considered separately in simulation and phantom studies. MRI signals were synthesized and analyzed for predictingR 2 * $$ {\mathrm{R}}_2^{\ast } $$ , based on simulations by incorporating virtual liver model, particle distribution, magnetic field generation, and proton movement into phase accrual. In the phantom study, iron-water and fat-water phantoms were constructed, and each phantom contained 15 separate vials with combinations of five particle concentrations and three particle sizes.R 2 * $$ {\mathrm{R}}_2^{\ast } $$ measurements in the phantom were made at both 1.5 T and 3.0 T. Finally, differences inR 2 * $$ {\mathrm{R}}_2^{\ast } $$ predictions or measurements were evaluated across varying particle sizes.

RESULTS

In the simulation study, strong linear and positively correlated relationships were observed betweenR 2 * $$ {\mathrm{R}}_2^{\ast } $$ predictions and particle concentrations across varying particle sizes and magnetic field strengths (r ≥ 0.988 $$ r\ge 0.988 $$ ). The relationships were affected by iron sphere size (p < 0.001 $$ p<0.001 $$ ), where smaller iron sphere size yielded higher predictedR 2 * $$ {\mathrm{R}}_2^{\ast } $$ , whereas fat droplet size had no effect onR 2 * $$ {\mathrm{R}}_2^{\ast } $$ predictions (p ≥ 0.617 $$ p\ge 0.617 $$ ) for constant total fat concentration. Similarly, the phantom study showed thatR 2 * $$ {\mathrm{R}}_2^{\ast } $$ measurements were relatively sensitive to iron sphere size (p ≤ 0.004 $$ p\le 0.004 $$ ) unlike fat droplet size (p ≥ 0.223 $$ p\ge 0.223 $$ ).

CONCLUSION

LiverR 2 * $$ {\mathrm{R}}_2^{\ast } $$ is affected by iron sphere size, but is relatively unaffected by fat droplet size. These findings may lead to an improved understanding of the underlying mechanisms ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ relaxometry in vivo, and enable improved quantitative MRI phantom design.

Confidence maps for reliable estimation of proton density fat fraction and R 2 * in the liver

PURPOSE

The objective was to develop a fully automated algorithm that generates confidence maps to identify regions valid for analysis of quantitative proton density fat fraction (PDFF) andR 2 * $$ {R}_2^{\ast } $$ maps of the liver, generated with chemical shift-encoded MRI (CSE-MRI). Confidence maps are urgently needed for automated quality assurance, particularly with the emergence of automated segmentation and analysis algorithms.

METHODS

Confidence maps for both PDFF andR 2 * $$ {R}_2^{\ast } $$ maps are generated based on goodness of fit, measured by normalized RMS error between measured complex signals and the CSE-MRI signal model. Based on Cramér-Rao lower bound and Monte-Carlo simulations, normalized RMS error threshold criteria were developed to identify unreliable regions in quantitative maps. Simulation, phantom, and in vivo clinical studies were included. To analyze the clinical data, a board-certified radiologist delineated regions of interest (ROIs) in each of the nine liver segments for PDFF andR 2 * $$ {R}_2^{\ast } $$ analysis in consecutive clinical CSE-MRI data sets. The percent area of ROIs in areas deemed unreliable by confidence maps was calculated to assess the impact of confidence maps on real-world clinical PDFF andR 2 * $$ {R}_2^{\ast } $$ measurements.

RESULTS

Simulations and phantom studies demonstrated that the proposed algorithm successfully excluded regions with unreliable PDFF andR 2 * $$ {R}_2^{\ast } $$ measurements. ROI analysis by the radiologist revealed that 2.6% and 15% of the ROIs were placed in unreliable areas of PDFF andR 2 * $$ {R}_2^{\ast } $$ maps, as identified by confidence maps.

CONCLUSION

A proposed confidence map algorithm that identifies reliable areas of PDFF andR 2 * $$ {R}_2^{\ast } $$ measurements from CSE-MRI acquisitions was successfully developed. It demonstrated technical and clinical feasibility.

Influence of Gadoxetate disodium to the hepatic proton density fat fraction quantified with the Dixon sequences in a rabbit model

OBJECTIVE

To study the impact of Gx on quantification of hepatic fat contents under metabolic dysfunction-associated steatotic liver disease (MASLD) imaged on VIBE Dixon in hepatobiliary specific phase.

METHODS

Forty-two rabbits were randomly divided into control group (n = 10) and high-fat diet group (n = 32). Imaging was performed before enhancement (Pre-Gx) and at the 13th (Post-Gx13) and 17th (Post-Gx17) min after Gx enhancement with 2E- and 6E-VIBE Dixon to determine hepatic proton density fat fractions (PDFF). PDFFs were compared with vacuole percentage (VP) measured under histopathology.

RESULTS

33 animals were evaluated and including control group (n = 11) and MASLD group (n = 22). Pre-Gx, Post-Gx13, Post-Gx17 PDFFs under 6E-VIBE Dixon had strong correlations with VPs (r2 = 0.8208-0.8536). PDFFs under 2E-VIBE Dixon were reduced significantly (P < 0.001) after enhancement (r2 = 0.7991/0.8014) compared with that before enhancement (r2 = 0.7643). There was no significant difference between PDFFs of Post-Gx13 and Post-Gx17 (P = 0.123) for which the highest consistency being found with 6E-VIBE Dixon before enhancement (r2 = 0.8536). The signal intensity of the precontrast compared with the postcontrast, water image under 2E-VIBE Dixon increased significantly (P < 0.001), fat image showed no significant difference (P = 0.754).

CONCLUSION

2E- and 6E-VIBE Dixon can obtain accurate PDFFs in the hepatobiliary specific phase from 13 to 17th min after Gx enhancement. On 2E-VIBE Dixon (FA = 10°), effective minimization of T1 Bias by the Gx administration markedly improved the accuracy of the hepatic PDFF quantification.

Automated liver volumetry and hepatic steatosis quantification with magnetic resonance imaging proton density fat fraction

BACKGROUND

Preoperative imaging evaluation of liver volume and hepatic steatosis for the donor affects transplantation outcomes. However, computed tomography (CT) for liver volumetry and magnetic resonance spectroscopy (MRS) for hepatic steatosis are time consuming. Therefore, we investigated the correlation of automated 3D-multi-echo-Dixon sequence magnetic resonance imaging (ME-Dixon MRI) and its derived proton density fat fraction (MRI-PDFF) with CT liver volumetry and MRS hepatic steatosis measurements in living liver donors.

METHODS

This retrospective cross-sectional study was conducted from December 2017 to November 2022. We enrolled donors who received a dynamic CT scan and an MRI exam within 2 days. First, the CT volumetry was processed semiautomatically using commercial software, and ME-Dixon MRI volumetry was automatically measured using an embedded sequence. Next, the signal intensity of MRI-PDFF volumetric data was correlated with MRS as the gold standard.

RESULTS

We included the 165 living donors. The total liver volume of ME-Dixon MRI was significantly correlated with CT (r = 0.913, p < 0.001). The fat percentage measured using MRI-PDFF revealed a strong correlation between automatic segmental volume and MRS (r = 0.705, p < 0.001). Furthermore, the hepatic steatosis group (MRS ≥5%) had a strong correlation than the non-hepatic steatosis group (MRS <5%) in both volumetric (r = 0.906 vs. r = 0.887) and fat fraction analysis (r = 0.779 vs. r = 0.338).

CONCLUSION

Automated ME-Dixon MRI liver volumetry and MRI-PDFF were strongly correlated with CT liver volumetry and MRS hepatic steatosis measurements, especially in donors with hepatic steatosis.

Body composition analysis by radiological imaging - methods, applications, and prospects

BACKGROUND

 This review discusses the quantitative assessment of tissue composition in the human body (body composition, BC) using radiological methods. Such analyses are gaining importance, in particular, for oncological and metabolic problems. The aim is to present the different methods and definitions in this field to a radiological readership in order to facilitate application and dissemination of BC methods. The main focus is on radiological cross-sectional imaging.

METHODS

 The review is based on a recent literature search in the US National Library of Medicine catalog (pubmed.gov) using appropriate search terms (body composition, obesity, sarcopenia, osteopenia in conjunction with imaging and radiology, respectively), as well as our own work and experience, particularly with MRI- and CT-based analyses of abdominal fat compartments and muscle groups.

RESULTS AND CONCLUSION

 Key post-processing methods such as segmentation of tomographic datasets are now well established and used in numerous clinical disciplines, including bariatric surgery. Validated reference values are required for a reliable assessment of radiological measures, such as fatty liver or muscle. Artificial intelligence approaches (deep learning) already enable the automated segmentation of different tissues and compartments so that the extensive datasets can be processed in a time-efficient manner - in the case of so-called opportunistic screening, even retrospectively from diagnostic examinations. The availability of analysis tools and suitable datasets for AI training is considered a limitation.

KEY POINTS

  · Radiological imaging methods are increasingly used to determine body composition (BC).. · BC parameters are usually quantitative and well reproducible.. · CT image data from routine clinical examinations can be used retrospectively for BC analysis.. · Prospectively, MRI examinations can be used to determine organ-specific BC parameters.. · Automated and in-depth analysis methods (deep learning or radiomics) appear to become important in the future..

CITATION FORMAT

· Linder N, Denecke T, Busse H. Body composition analysis by radiological imaging - methods, applications, and prospects. Fortschr Röntgenstr 2024; DOI: 10.1055/a-2263-1501.

Liver Stiffness Determined by Transient Elastography Is a Simple and Highly Accurate Predictor for Presence of Liver Cirrhosis in Clinical Routine

INTRODUCTION

Early detection of patients with advanced chronic liver disease is critical for the prevention of complications and inclusion in surveillance programs for hepatocellular carcinoma. In daily clinical care, it remains challenging to differentiate early cirrhosis from lower fibrosis grades without performing a liver biopsy. The aim of the present study was to assess the performance of different non-invasive detection tools to differentiate cirrhosis from lower fibrosis grades.

METHODS

Data of 116 patients (51 male, 65 female) with chronic liver disease of various origins undergoing liver biopsy was analyzed. Routine laboratory values, liver stiffness measurement (LSM) by transient elastography, and histological liver assessment were collected.

RESULTS

Robust and significant correlations with the histological fibrosis stage were identified for LSM (r = 0.65), the FAST score (0.64), the FIB-4 (0.48), serum aspartate aminotransferase (AST) concentration (0.41), NFS (0.33), international normalized ratio (INR; 0.30), methacetin breath test results (-0.40), and serum albumin concentration (-0.29) by spearman rank correlation. Receiver operating characteristic curves were built for these parameters to separate patients with cirrhosis from those with any other fibrosis stage. The highest AUC was achieved by LSM (0.9130), followed by the FAST score (0.8842), the FIB-4 (0.8644), the NFS (0.8227), INR (0.8142), serum albumin (0.7710), and serum AST (0.7620). The most promising clinical applicability would be an LSM value of 12.2 kPa, achieving 95.7% sensitivity and 75.3% specificity.

CONCLUSION

LSM and FAST score seem to be robust non-invasive measurements for liver fibrosis. LSM and FAST scores may have the potential to reliably detect patients with liver cirrhosis in clinical routine settings.

Advanced fibrosis leads to overestimation of steatosis with quantitative ultrasound in individuals without hepatic steatosis

PURPOSE

The effect of hepatic fibrosis stage on quantitative ultrasound based on the attenuation coefficient (AC) for liver lipid quantification is controversial. The objective of this study was to determine how the degree of fibrosis assessed by magnetic resonance (MR) elastography affects AC based on the ultrasound-guided attenuation parameter according to the grade of hepatic steatosis, using magnetic resonance imaging (MRI)-derived proton density fat fraction (MRIderived PDFF) as the reference standard.

METHODS

Between February 2020 and April 2021, 982 patients with chronic liver disease who underwent AC and MRI-derived PDFF measurement as well as MR elastography were enrolled. Multiple regression was used to investigate whether AC was affected by the degree of liver stiffness.

RESULTS

AC increased as liver stiffness progressed in 344 patients without hepatic steatosis (P=0.009). In multivariable analysis, AC was positively correlated with skin-capsule distance (P<0.001), MR elastography value (P=0.037), and MRI-derived PDFF (P<0.001) in patients without hepatic steatosis. In 52 of 982 patients (5%), the correlation between AC and MRIderived PDFF fell outside the 95% confidence interval for the regression line slope. Patients with MRI-derived PDFF lower than their AC (n=36) had higher fibrosis-4 scores, albumin-bilirubin scores, and MR elastography values than patients with MRI-derived PDFF greater than their AC (n=16; P=0.018, P=0.001, and P=0.011, respectively).

CONCLUSION

AC is affected by liver fibrosis (MR elastography value ≥6.7 kPa) only in patients without hepatic steatosis (MRI-derived PDFF <5.2%). These values should be interpreted with caution in patients with advanced liver fibrosis.

Comparison of the accuracy of commercial two-point and multi-echo Dixon MRI for quantification of fat in liver, paravertebral muscles, and vertebral bone marrow

PURPOSE

Excess fat accumulation contributes significantly to metabolic dysfunction and diseases. This study aims to systematically compare the accuracy of commercially available Dixon techniques for quantification of fat fraction in liver, skeletal musculature, and vertebral bone marrow (BM) of healthy individuals, investigating biases and sex-specific influences.

METHOD

100 healthy White individuals (50 women) underwent abdominal MRI using two-point and multi-echo Dixon sequences. Fat fraction (FF), proton density fat fraction (PDFF) and T2* values were calculated for liver, paravertebral muscles (PVM) and vertebral BM (Th8-L5). Agreement and systematic deviations were assessed using linear correlation and Bland-Altman plots.

RESULTS

High correlations between FF and PDFF were observed in liver (r = 0.98 for women; r = 0.96 for men), PVM (r = 0.92 for women; r = 0.93 for men) and BM (r = 0.97 for women; r = 0.95 for men). Relative deviations between FF and PDFF in liver (18.92 % for women; 13.32 % for men) and PVM (1.96 % for women; 11.62 % for men) were not significant. Relative deviations in BM were significant (38.13 % for women; 27.62 % for men). Bias correction using linear models reduced discrepancies. T2* times were significantly shorter in BM (8.72 ms for women; 7.26 ms for men) compared to PVM (13.45 ms for women; 13.62 ms for men) and liver (29.47 ms for women; 26.35 ms for men).

CONCLUSION

While no significant differences were observed for liver and PVM, systematic errors in BM FF estimation using two-point Dixon imaging were observed. These discrepancies - mainly resulting from organ-specific T2* times - have to be considered when applying two-point Dixon approaches for assessment of fat content. As suitable correction tools, linear models could provide added value in large-scale epidemiological cohort studies. Sex-specific differences in T2* should be considered.

MASH Resolution Index: development and validation of a non-invasive score to detect histological resolution of MASH

BACKGROUND

Dynamic changes in non-invasive tests, such as changes in alanine aminotransferase (ALT) and MRI proton-density-fat-fraction (MRI-PDFF), may help to detect metabolic dysfunction-associated steatohepatitis (MASH) resolution, but a combination of non-invasive tests may be more accurate than either alone. We developed a novel non-invasive score, the MASH Resolution Index, to detect the histological resolution of MASH.

METHODS

This study included a derivation cohort of 95 well-characterised adult participants (67% female) with biopsy-confirmed MASH who underwent contemporaneous laboratory testing, MRI-PDFF and liver biopsy at two time points. The primary objective was to develop a non-invasive score to detect MASH resolution with no worsening of fibrosis. The most predictive logistic regression model was selected based on the highest area under the receiver operating curve (AUC), and the lowest Akaike information criterion and Bayesian information criterion. The model was then externally validated in a distinct cohort of 163 participants with MASH from a clinical trial.

RESULTS

The median (IQR) age and body mass index were 55 (45-62) years and 32.0 (30-37) kg/m2, respectively, in the derivation cohort. The most accurate model (MASH Resolution Index) included MRI-PDFF, ALT and aspartate aminotransferase. The index had an AUC of 0.81 (95% CI 0.69 to 0.93) for detecting MASH resolution in the derivation cohort. The score calibrated well and performed robustly in a distinct external validation cohort (AUC 0.83, 95% CI 0.76 to 0.91), and outperformed changes in ALT and MRI-PDFF.

CONCLUSION

The MASH Resolution Index may be a useful score to non-invasively identify MASH resolution.

Fasting-mimicking diet causes hepatic and blood markers changes indicating reduced biological age and disease risk

In mice, periodic cycles of a fasting mimicking diet (FMD) protect normal cells while killing damaged cells including cancer and autoimmune cells, reduce inflammation, promote multi-system regeneration, and extend longevity. Here, we performed secondary and exploratory analysis of blood samples from a randomized clinical trial (NCT02158897) and show that 3 FMD cycles in adult study participants are associated with reduced insulin resistance and other pre-diabetes markers, lower hepatic fat (as determined by magnetic resonance imaging) and increased lymphoid to myeloid ratio: an indicator of immune system age. Based on a validated measure of biological age predictive of morbidity and mortality, 3 FMD cycles were associated with a decrease of 2.5 years in median biological age, independent of weight loss. Nearly identical findings resulted from  a second clinical study (NCT04150159). Together these results provide initial support for beneficial effects of the FMD on multiple cardiometabolic risk factors and biomarkers of biological age.

Metabolic syndrome: imaging features and clinical outcomes

Metabolic syndrome, which affects around a quarter of adults worldwide, is a group of metabolic abnormalities characterized mainly by insulin resistance and central adiposity. It is strongly correlated with cardiovascular and all-cause mortality. Early identification of the changes induced by metabolic syndrome in target organs and timely intervention (eg, weight reduction) can decrease morbidity and mortality. Imaging can monitor the main components of metabolic syndrome and identify early the development and progression of its sequelae in various organs. In this review, we discuss the imaging features across different modalities that can be used to evaluate changes due to metabolic syndrome, including fatty deposition in different organs, arterial stiffening, liver fibrosis, and cardiac dysfunction. Radiologists can play a vital role in recognizing and following these target organ injuries, which in turn can motivate lifestyle modification and therapeutic intervention.

Comparative review of algorithms and methods for chemical-shift-encoded quantitative fat-water imaging

PURPOSE

To propose a standardized comparison between state-of-the-art open-source fat-water separation algorithms for proton density fat fraction (PDFF) andR 2 * $$ {R}_2^{\ast } $$ quantification using an open-source multi-language toolbox.

METHODS

Eight recent open-source fat-water separation algorithms were compared in silico, in vitro, and in vivo. Multi-echo data were synthesized with varying fat-fractions, B0 off-resonance, SNR and TEs. Experimental evaluation was conducted using calibrated fat-water phantoms acquired at 3T and multi-site open-source phantoms data. Algorithms' performances were observed on challenging in vivo datasets at 3T. Finally, reconstruction algorithms were investigated with different fat spectra to evaluate the importance of the fat model.

RESULTS

In silico and in vitro results proved most algorithms to be not sensitive to fat-water swaps andB 0 $$ {\mathrm{B}}_0 $$ offsets with five or more echoes. However, two methods remained inaccurate even with seven echoes and SNR = 50, and two other algorithms' precision depended on the echo spacing scheme (p < 0.05). The remaining four algorithms provided reliable performances with limits of agreement under 2% for PDFF and 6 s-1 forR 2 * $$ {R}_2^{\ast } $$ . The choice of fat spectrum model influenced quantification of PDFF mildly (<2% bias) and ofR 2 * $$ {R}_2^{\ast } $$ more severely, with errors up to 20 s-1 .

CONCLUSION

In promoting standardized comparisons of MRI-based fat and iron quantification using chemical-shift encoded multi-echo methods, this benchmark work has revealed some discrepancies between recent approaches for PDFF andR 2 * $$ {R}_2^{\ast } $$ mapping. Explicit choices and parameterization of the fat-water algorithm appear necessary for reproducibility. This open-source toolbox further enables the user to optimize acquisition parameters by predicting algorithms' margins of errors.

Validity of an automated screening Dixon technique for quantifying hepatic steatosis in living liver donors

PURPOSE

This retrospective study aimed to evaluate the validity of an automated screening Dixon (e-DIXON) technique for quantifying hepatic steatosis in living liver-donor patients by comparison with magnetic resonance spectroscopy (MRS) as a reference standard.

METHODS

A total of 285 living liver-donor candidates were examined with the e-DIXON technique and single-voxel MRS to assess hepatic steatosis and iron deposition between January 2014 and February 2019. The sensitivity, specificity, and positive and negative predictive values (PPV and NPV) of the e-DIXON technique for hepatic steatosis were calculated. The mean fat signal fractions obtained in MRS were compared between the donors diagnosed with hepatic steatosis and the normal group. The mean R2 values of donors with or without hepatic siderosis also were compared.

RESULTS

The e-DIXON technique diagnosed normal in 133 (47%), fat in 124 (44%), iron in one (0.4%), and a combination of both fat and iron in 27 (10%) donors. The sensitivity, specificity, PPV, and NPV ​​for diagnosing hepatic steatosis were 94%, 70%, 64%, and 96%, respectively. There was a significant difference in the mean fat signal fraction obtained in MRS between the steatosis and normal groups (p < 0.001), but R2 values were not significantly different between siderosis and normal groups (p = 0.11). The e-DIXON technique showed a strong correlation with MRS in fat measurement (r2 = 0.92, p < 0.001).

CONCLUSION

The e-DIXON technique reliably screens for hepatic steatosis but may not accurate for detecting hepatic iron deposition.

Protocol of quantitative ultrasound techniques for noninvasive assessing of hepatic steatosis after bariatric surgery

Introduction

Roux-en-Y gastric bypass surgery can effectively improve steatosis, necroinflammatory activity, and hepatic fibrosis in individuals diagnosed with morbid obesity or nonalcoholic steatohepatitis (NASH). Common methods such as body mass index (BMI) to evaluate the postoperative effect of clinical bariatric surgery cannot differentiate subcutaneous fats from visceral fats and muscles. Several Quantitative ultrasound (QUS)-based approaches have been developed to quantify hepatic steatosis. QUS techniques (tissue attenuation imaging (TAI), tissue scatter distribution imaging (TSI)) from radio frequency (RF) data analysis as a means for the detection and grading of hepatic steatosis has been posited as an objective and noninvasive approach. The implementation and standardization of QUS techniques (TAI, TSI) in assessing hepatic steatosis quantitatively after bariatric surgery is of high-priority. Our study is aimed to assess hepatic steatosis with QUS techniques (TAI, TSI) in morbidly obese individuals before and after bariatric surgery, and to compare with anthropometric measurements, laboratory assessments and other imaging methods.

Methods and analysis

The present investigation, a self-discipline examination of navigational capacity devoid of visual cues, is designed as a single-site, forward-looking evaluation of efficacy with the imprimatur of the institutional review board. The duration of the study has been provisionally determined to span from 1 January 2023 through 31 December 2025. Our cohort shall encompass one hundred participants, who was scheduled to undergo Roux-en-Y gastric bypass (RYGB) at Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. All patients will undergo anthropometric measurements, blood-based biochemical analyses, ultrasonic examination and magnetic resonance imaging proton density fat fraction (MRI-PDFF). The primary endpoint is the analysis of evaluating the efficacy of QUS techniques assessing hepatic steatosis compared to other methods before and after bariatric surgery.

Results

Prior to the fomal study, we recruited 21 obese Chinese participants who received ultrasonic examination (TAI, TSI) and MRI-PDFF. AC-TAI showed moderate correlations with MRI-PDFF (adjusted r = 0.632; P < 0.05). For MRI-PDFF ≥10%, SC-TSI showed moderate correlations with MRI-PDFF (adjusted r = 0.677; P < 0.05).

Conclusion

Our pre-experiment results signified that using QUS techniques for postoperative evaluation of bariatric surgery is promising. QUS techniques will be signed a widespread availability, real-time functionality, and low-cost approach for assessing hepatic steatosis before and after bariatric surgery in obese individuals, thus is capable for subsequent scale-up liver fat quantification.

Ethics and dissemination

The present research endeavor has been bestowed with the imprimatur of the Ethics Committee of the Hospital, as indicated by its Approval Number: 2023-KY-015. In due course, upon completion of the study, we intend to disseminate our findings by publishing them in a suitable academic journal, thereby facilitating their widespread utilization.

Registration

The trial is duly registered with the Chinese Clinical Trial Registry, and with a unique Trial Registration Number, ChiCTR2300069892, approved on March 28, 2023.

Quantification of Hepatic Steatosis on Dual-Energy CT in Comparison With MRI mDIXON-Quant Sequence in Breast Cancer

OBJECTIVE

The study aimed to evaluate the correlation and diagnostic value of liver fat quantification in unenhanced dual-energy CT (DECT) using quantitative magnetic resonance imaging (MRI) mDIXON-Quant sequence as reference standard in patients with breast cancer.

METHODS

Patients with breast cancer were prospectively recruited between June 2018 and April 2020. Each patient underwent liver DECT and MRI mDIXON-Quant examination. The DECT-fat volume fraction (FVF) and liver-spleen attenuation differences were compared with the MRI-proton density fat fraction using scatterplots, Bland-Altman plots, and concordance correlation coefficient. Receiver operating characteristic curves were established to determine the diagnostic accuracy of hepatic steatosis by DECT.

RESULTS

A total of 216 patients with breast cancer (mean age, 50.08 ± 9.33 years) were evaluated. The DECT-FVF correlated well with MRI-proton density fat fraction ( r2 = 0.902; P < 0.001), which was higher than the difference in liver-spleen attenuation ( r2 = 0.728; P < 0.001). Bland-Altman analysis revealed slight positive bias; the mean difference was 3.986. The DECT-FVF yielded an average concordance correlation coefficient of 0.677, which was higher than the difference of liver-spleen attenuation (-0.544). The DECT-FVF and the difference in liver-spleen attenuation both lead to mild overestimation of hepatic steatosis. The areas under the curve of DECT-FVF (0.956) were higher than the difference in liver-spleen attenuation (0.807) in identifying hepatic steatosis ( P < 0.001).

CONCLUSIONS

Dual-energy CT-FVF may serve as a reliable screening and quantitative tool for hepatic steatosis in patients with breast cancer.

An Update on the Effect Of Sodium Glucose Cotransporter 2 Inhibitors on Non-Alcoholic Fatty Liver Disease: A Systematic Review of Clinical Trials

Non-alcoholic fatty liver disease (NAFLD) is one of the main causes of liver disease, specifically chronic liver disease. Type 2 diabetes (T2DM) is associated with the risk of NAFLD given that patients usually have insulin resistance as one of the observed complications with NAFLD. Hypoglycemic agents, including sodium glucose cotransporter 2 (SGLT-2), have shown to improve NAFLD. The objective of this study is to evaluate the effect of SGLT-2 inhibitors on NAFLD patients' outcomes, whether they have T2DM or not. We conducted a comprehensive search using the PubMed and Ovid databases to identify published studies that addressed the use of SGLT-2 inhibitors in NAFLD patients. The outcomes assessed include changes in liver enzymes, lipid profiles, weight changes, the fibrosis-4-index (FIB4), and magnetic resonance imaging proton density-based fat fraction (MRI-PDFF). Only clinical trials that met the quality measures were included in this review. Out of 382 potential studies, we included 16 clinical trials that discussed the use of SGLT-2 inhibitors in NAFLD patients. A total of 753 patients were enrolled in these trials. The majority of the trials reported positive effects of SGLT-2 inhibitors on liver enzymes; alanine transaminase (ALT), aspartate aminotransferase (AST), and gamma-glutamyl transferase. All 10 trials that reported changes in body mass index (BMI) from baseline showed a statistically significant reduction with SGLT-2 inhibitor use, while 11 studies reported a significant increase in high density lipoprotein (HDL) levels, 3 studies reported a reduction in triglycerides (TG) levels, and 2 studies showed a decrease in low density lipoprotein (LDL) levels. The available evidence shows that the use of SGLT-2 inhibitors in NAFLD is associated with positive outcomes on liver enzymes, lipid profiles, and BMI. Further studies with larger sample size and longer follow-up time are warranted.

Marked difference in liver fat measured by histology vs. magnetic resonance-proton density fat fraction: A meta-analysis

Background & Aims

Pathologists quantify liver steatosis as the fraction of lipid droplet-containing hepatocytes out of all hepatocytes, whereas the magnetic resonance-determined proton density fat fraction (PDFF) reflects the tissue triacylglycerol concentration. We investigated the linearity, agreement, and correspondence thresholds between histological steatosis and PDFF across the full clinical spectrum of liver fat content associated with non-alcoholic fatty liver disease.

Methods

Using individual patient-level measurements, we conducted a systematic review and meta-analysis of studies comparing histological steatosis with PDFF determined by magnetic resonance spectroscopy or imaging in adults with suspected non-alcoholic fatty liver disease. Linearity was assessed by meta-analysis of correlation coefficients and by linear mixed modelling of pooled data, agreement by Bland-Altman analysis, and thresholds by receiver operating characteristic analysis. To explain observed differences between the methods, we used RNA-seq to determine the fraction of hepatocytes in human liver biopsies.

Results

Eligible studies numbered 9 (N = 597). The relationship between PDFF and histology was predominantly linear (r = 0.85 [95% CI, 0.80-0.89]), and their values approximately coincided at 5% steatosis. Above 5% and towards higher levels of steatosis, absolute values of the methods diverged markedly, with histology exceeding PDFF by up to 3.4-fold. On average, 100% histological steatosis corresponded to a PDFF of 33.0% (29.5-36.7%). Targeting at a specificity of 90%, optimal PDFF thresholds to predict histological steatosis grades were ≥5.75% for ≥S1, ≥15.50% for ≥S2, and ≥21.35% for S3. Hepatocytes comprised 58 ± 5% of liver cells, which may partly explain the lower values of PDFF vs. histology.

Conclusions

Histological steatosis and PDFF have non-perfect linearity and fundamentally different scales of measurement. Liver fat values obtained using these methods may be rendered comparable by conversion equations or threshold values.

Impact and implications

Magnetic resonance-proton density fat fraction (PDFF) is increasingly being used to measure liver fat in place of the invasive liver biopsy. Understanding the relationship between PDFF and histological steatosis fraction is important for preventing misjudgement of clinical status or treatment effects in patient care. Our analysis revealed that histological steatosis fraction is often significantly higher than PDFF, and their association varies across the spectrum of fatty liver severity. These findings are particularly important for physicians and clinical researchers, who may use these data to interpret PDFF measurements in the context of histologically evaluated liver fat content.

Evaluation of proton density fat fraction (PDFF) obtained from a vendor-neutral MRI sequence and MRQuantif software

OBJECTIVE

To validate the proton density fat fraction (PDFF) obtained by the MRQuantif software from 2D chemical shift encoded MR (CSE-MR) data in comparison with the histological steatosis data.

METHODS

This study, pooling data from 3 prospective studies spread over time between January 2007 and July 2020, analyzed 445 patients who underwent 2D CSE-MR and liver biopsy. MR derived liver iron concentration (MR-LIC) and PDFF was calculated using the MRQuantif software. The histological standard steatosis score (SS) served as reference. In order to get a value more comparable to PDFF, histomorphometry fat fraction (HFF) were centrally determined for 281 patients. Spearman correlation and the Bland and Altman method were used for comparison.

RESULTS

Strong correlations were found between PDFF and SS (rs = 0.84, p < 0.001) or HFF (rs = 0.87, p < 0.001). Spearman's coefficients increased to 0.88 (n = 324) and 0.94 (n = 202) when selecting only the patients without liver iron overload. The Bland and Altman analysis between PDFF and HFF found a mean bias of 5.4% ± 5.7 [95% CI 4.7, 6.1]. The mean bias was 4.7% ± 3.7 [95% CI 4.2, 5.3] and 7.1% ± 8.8 [95% CI 5.2, 9.0] for the patients without and with liver iron overload, respectively.

CONCLUSION

The PDFF obtained by MRQuantif from a 2D CSE-MR sequence is highly correlated with the steatosis score and very close to the fat fraction estimated by histomorphometry. Liver iron overload reduced the performance of steatosis quantification and joint quantification is recommended. This device-independent method can be particularly useful for multicenter studies.

CLINICAL RELEVANCE STATEMENT

The quantification of liver steatosis using a vendor-neutral 2D chemical-shift MR sequence, processed by MRQuantif, is well correlated to steatosis score and histomorphometric fat fraction obtained from biopsy, whatever the magnetic field and the MR device used.

KEY POINTS

• The PDFF measured by MRQuantif from 2D CSE-MR sequence data is highly correlated to hepatic steatosis. • Steatosis quantification performance is reduced in case of significant hepatic iron overload. • This vendor-neutral method may allow consistent estimation of PDFF in multicenter studies.

MRI proton density fat fraction for estimation of tumor grade in steatotic hepatocellular carcinoma

OBJECTIVES

Image-based detection of intralesional fat in focal liver lesions has been established in diagnostic guidelines as a feature indicative of hepatocellular carcinoma (HCC) and associated with a favorable prognosis. Given recent advances in MRI-based fat quantification techniques, we investigated a possible relationship between intralesional fat content and histologic tumor grade in steatotic HCCs.

METHODS

Patients with histopathologically confirmed HCC and prior MRI with proton density fat fraction (PDFF) mapping were retrospectively identified. Intralesional fat of HCCs was assessed using an ROI-based analysis and the median fat fraction of steatotic HCCs was compared between tumor grades G1-3 with non-parametric testing. ROC analysis was performed in case of statistically significant differences (p < 0.05). Subgroup analyses were conducted for patients with/without liver steatosis and with/without liver cirrhosis.

RESULTS

A total of 57 patients with steatotic HCCs (62 lesions) were eligible for analysis. The median fat fraction was significantly higher for G1 lesions (median [interquartile range], 7.9% [6.0─10.7%]) than for G2 (4.4% [3.2─6.6%]; p = .001) and G3 lesions (4.7% [2.8─7.8%]; p = .036). PDFF was a good discriminator between G1 and G2/3 lesions (AUC .81; cut-off 5.8%, sensitivity 83%, specificity 68%) with comparable results in patients with liver cirrhosis. In patients with liver steatosis, intralesional fat content was higher than in the overall sample, with PDFF performing better in distinguishing between G1 and G2/3 lesions (AUC .92; cut-off 8.8%, sensitivity 83%, specificity 91%).

CONCLUSIONS

Quantification of intralesional fat using MRI PDFF mapping allows distinction between well- and less-differentiated steatotic HCCs.

CLINICAL RELEVANCE

PDFF mapping may help optimize precision medicine as a tool for tumor grade assessment in steatotic HCCs. Further investigation of intratumoral fat content as a potential prognostic indicator of treatment response is encouraged.

KEY POINTS

• MRI proton density fat fraction mapping enables distinction between well- (G1) and less- (G2 and G3) differentiated steatotic hepatocellular carcinomas. • In a retrospective single-center study with 62 histologically proven steatotic hepatocellular carcinomas, G1 tumors showed a higher intralesional fat content than G2 and G3 tumors (7.9% vs. 4.4% and 4.7%; p = .004). • In liver steatosis, MRI proton density fat fraction mapping was an even better discriminator between G1 and G2/G3 steatotic hepatocellular carcinomas.

Quantification of ectopic fat storage in the liver and pancreas using six-point Dixon MRI and its association with insulin sensitivity and β-cell function in patients with central obesity

OBJECTIVES

To assess the association of ectopic fat deposition in the liver and pancreas quantified by Dixon magnetic resonance imaging (MRI) with insulin sensitivity and β-cell function in patients with central obesity.

MATERIALS AND METHODS

A cross-sectional study of 143 patients with central obesity with normal glucose tolerance (NGT), prediabetes (PreD), and untreated type 2 diabetes mellitus (T2DM) was conducted between December 2019 and March 2022. All participants underwent routine medical history taking, anthropometric measurements, and laboratory tests, including a standard glucose tolerance test to quantify insulin sensitivity and β-cell function. The fat content in the liver and pancreas was measured with MRI using the six-point Dixon technique.

RESULTS

Patients with T2DM and PreD had a higher liver fat fraction (LFF) than those with NGT, while those with T2DM had a higher pancreatic fat fraction (PFF) than those with PreD and NGT. LFF was positively correlated with homeostatic model assessment of insulin resistance (HOMA-IR), while PFF was negatively correlated with homeostatic model assessment of insulin secretion (HOMA-β). Furthermore, using a structured equation model, we found LFF and PFF to be positively associated with glycosylated hemoglobin via HOMA-IR and HOMA-β, respectively.

CONCLUSIONS

In patients with central obesity, the effects of LFF and PFF on glucose metabolism. were associated with HOMA-IR and HOMA-β, respectively. Ectopic fat storage in the liver and pancreas quantified by MR Dixon imaging potentially plays a notable role in the onset ofT2DM.

CLINICAL RELEVANCE STATEMENT

We highlight the potential role of ectopic fat deposition in the liver and pancreas in the development of type 2 diabetes in patients with central obesity, providing valuable insights into the pathogenesis of the disease and potential targets for intervention.

KEY POINTS

• Ectopic fat deposition in the liver and pancreas is associated with T2DM. • T2DM and prediabetes patients had higher liver and pancreatic fat fractions than normal individuals. • The results provide valuable insights into pathogenesis of T2DM and potential targets for intervention.

Reduced adipose tissue in growth-restricted fetuses using quantitative analysis of magnetic resonance images

OBJECTIVES

Fat-water MRI can be used to quantify tissues' lipid content. We aimed to quantify fetal third trimester normal whole-body subcutaneous lipid deposition and explore differences between appropriate for gestational age (AGA), fetal growth restriction (FGR), and small for gestational age fetuses (SGAs).

METHODS

We prospectively recruited women with FGR and SGA-complicated pregnancies and retrospectively recruited the AGA cohort (sonographic estimated fetal weight [EFW] ≥ 10th centile). FGR was defined using the accepted Delphi criteria, and fetuses with an EFW < 10th centile that did not meet the Delphi criteria were defined as SGA. Fat-water and anatomical images were acquired in 3 T MRI scanners. The entire fetal subcutaneous fat was semi-automatically segmented. Three adiposity parameters were calculated: fat signal fraction (FSF) and two novel parameters, i.e., fat-to-body volume ratio (FBVR) and estimated total lipid content (ETLC = FSF*FBVR). Normal lipid deposition with gestation and differences between groups were assessed.

RESULTS

Thirty-seven AGA, 18 FGR, and 9 SGA pregnancies were included. All three adiposity parameters increased between 30 and 39 weeks (p < 0.001). All three adiposity parameters were significantly lower in FGR compared with AGA (p ≤ 0.001). Only ETLC and FSF were significantly lower in SGA compared with AGA using regression analysis (p = 0.018-0.036, respectively). Compared with SGA, FGR had a significantly lower FBVR (p = 0.011) with no significant differences in FSF and ETLC (p ≥ 0.053).

CONCLUSIONS

Whole-body subcutaneous lipid accretion increased throughout the third trimester. Reduced lipid deposition is predominant in FGR and may be used to differentiate FGR from SGA, assess FGR severity, and study other malnourishment pathologies.

CLINICAL RELEVANCE STATEMENT

Fetuses with growth restriction have reduced lipid deposition than appropriately developing fetuses measured using MRI. Reduced fat accretion is linked with worse outcomes and may be used for growth restriction risk stratification.

KEY POINTS

• Fat-water MRI can be used to assess the fetal nutritional status quantitatively. • Lipid deposition increased throughout the third trimester in AGA fetuses. • FGR and SGA have reduced lipid deposition compared with AGA fetuses, more predominant in FGR.

Potassium Magnesium Citrate Is Superior to Potassium Chloride in Reversing Metabolic Side Effects of Chlorthalidone

BACKGROUND

Thiazide diuretics (TD) are the first-line treatment of hypertension because of its consistent benefit in lowering blood pressure and cardiovascular risk. TD is also known to cause an excess risk of diabetes, which may limit long-term use. Although potassium (K) depletion was thought to be the main mechanism of TD-induced hyperglycemia, TD also triggers magnesium (Mg) depletion. However, the role of Mg supplementation in modulating metabolic side effects of TD has not been investigated. Therefore, we aim to determine the effect of potassium magnesium citrate (KMgCit) on fasting plasma glucose and liver fat by magnetic resonance imaging during TD therapy.

METHODS

Accordingly, we conducted a double-blinded RCT in 60 nondiabetic hypertension patients to compare the effects of KCl versus KMgCit during chlorthalidone treatment. Each patient received chlorthalidone alone for 3 weeks before randomization. Primary end point was the change in fasting plasma glucose after 16 weeks of KCl or KMgCit supplementation from chlorthalidone alone.

RESULTS

The mean age of subjects was 59±11 years (30% Black participants). Chlorthalidone alone induced a significant rise in fasting plasma glucose, and a significant fall in serum K, serum Mg, and 24-hour urinary citrate excretion (all P<0.05). KMgCit attenuated the rise in fasting plasma glucose by 7.9 mg/dL versus KCl (P<0.05), which was not observed with KCl. There were no significant differences in liver fat between the 2 groups.

CONCLUSIONS

KMgCit is superior to KCl, the common form of K supplement used in clinical practice, in preventing TD-induced hyperglycemia. This action may improve tolerability and cardiovascular safety in patients with hypertension treated with this drug class.

Non-Invasive Diagnostic of NAFLD in Type 2 Diabetes Mellitus and Risk Stratification: Strengths and Limitations

The progressive potential of liver damage in type 2 diabetes mellitus (T2DM) towards advanced fibrosis, end-stage liver disease, and hepatocarcinoma has led to increased concern for quantifying liver injury and individual risk assessment. The combination of blood-based markers and imaging techniques is recommended for the initial evaluation in NAFLD and for regular monitoring to evaluate disease progression. Continued development of ultrasonographic and magnetic resonance imaging methods for accurate quantification of liver steatosis and fibrosis, as well as promising tools for the detection of high-risk NASH, have been noted. In this review, we aim to summarize available evidence regarding the usefulness of non-invasive methods for the assessment of NAFLD in T2DM. We focus on the power and limitations of various methods for diagnosis, risk stratification, and patient monitoring that support their implementation in clinical setting or in research field.

Correlation of histologic, imaging, and artificial intelligence features in NAFLD patients, derived from Gd-EOB-DTPA-enhanced MRI: a proof-of-concept study

OBJECTIVE

To compare unsupervised deep clustering (UDC) to fat fraction (FF) and relative liver enhancement (RLE) on Gd-EOB-DTPA-enhanced MRI to distinguish simple steatosis from non-alcoholic steatohepatitis (NASH), using histology as the gold standard.

MATERIALS AND METHODS

A derivation group of 46 non-alcoholic fatty liver disease (NAFLD) patients underwent 3-T MRI. Histology assessed steatosis, inflammation, ballooning, and fibrosis. UDC was trained to group different texture patterns from MR data into 10 distinct clusters per sequence on unenhanced T1- and Gd-EOB-DTPA-enhanced T1-weighted hepatobiliary phase (T1-Gd-EOB-DTPA-HBP), then on T1 in- and opposed-phase images. RLE and FF were quantified on identical sequences. Differences of these parameters between NASH and simple steatosis were evaluated with χ2- and t-tests, respectively. Linear regression and Random Forest classifier were performed to identify associations between histological NAFLD features, RLE, FF, and UDC patterns, and then determine predictors able to distinguish simple steatosis from NASH. ROC curves assessed diagnostic performance of UDC, RLE, and FF. Finally, we tested these parameters on 30 validation cohorts.

RESULTS

For the derivation group, UDC-derived features from unenhanced and T1-Gd-EOB-DTPA-HBP, plus from T1 in- and opposed-phase, distinguished NASH from simple steatosis (p ≤ 0.001 and p = 0.02, respectively) with 85% and 80% accuracy, respectively, while RLE and FF distinguished NASH from simple steatosis (p ≤ 0.001 and p = 0.004, respectively), with 83% and 78% accuracy, respectively. On multivariate regression analysis, RLE and FF correlated only with fibrosis (p = 0.040) and steatosis (p ≤ 0.001), respectively. Conversely, UDC features, using Random Forest classifier predictors, correlated with all histologic NAFLD components. The validation group confirmed these results for both approaches.

CONCLUSION

UDC, RLE, and FF could independently separate NASH from simple steatosis. UDC may predict all histologic NAFLD components.

CLINICAL RELEVANCE STATEMENT

Using gadoxetic acid-enhanced MR, fat fraction (FF > 5%) can diagnose NAFLD, and relative liver enhancement can distinguish NASH from simple steatosis. Adding AI may let us non-invasively estimate the histologic components, i.e., fat, ballooning, inflammation, and fibrosis, the latter the main prognosticator.

KEY POINTS

• Unsupervised deep clustering (UDC) and MR-based parameters (FF and RLE) could independently distinguish simple steatosis from NASH in the derivation group. • On multivariate analysis, RLE could predict only fibrosis, and FF could predict only steatosis; however, UDC could predict all histologic NAFLD components in the derivation group. • The validation cohort confirmed the findings for the derivation group.

The Role of the Multiparametric MRI LiverMultiScanTM in the Quantitative Assessment of the Liver and Its Predicted Clinical Applications in Patients Undergoing Major Hepatic Resection for Colorectal Liver Metastasis

Liver biopsy remains the gold standard for the histological assessment of the liver. With clear disadvantages and the rise in the incidences of liver disease, the role of neoadjuvant chemotherapy in colorectal liver metastasis (CRLM) and an explosion of surgical management options available, non-invasive serological and imaging markers of liver histopathology have never been more pertinent in order to assess liver health and stratify patients considered for surgical intervention. Liver MRI is a leading modality in the assessment of hepatic malignancy. Recent technological advancements in multiparametric MRI software such as the LiverMultiScanTM offers an attractive non-invasive assay of anatomy and histopathology in the pre-operative setting, especially in the context of CRLM. This narrative review examines the evidence for the LiverMultiScanTM in the assessment of hepatic fibrosis, steatosis/steatohepatitis, and potential applications for chemotherapy-associated hepatic changes. We postulate its future role and the hurdles it must surpass in order to be implemented in the pre-operative management of patients undergoing hepatic resection for colorectal liver metastasis. Such a role likely extends to other hepatic malignancies planned for resection.

Ultrasound-derived fat fraction for detection of hepatic steatosis and quantification of liver fat content

PURPOSE

To compare ultrasound (US) and US-derived fat fraction (UDFF) with magnetic resonance proton density fat fraction (MRI-PDFF) for the detection of hepatic steatosis and quantification of liver fat content.

MATERIALS AND METHODS

Between October and December 2022, 149 patients scheduled for an abdominal MRI agreed to participate in this study and underwent MRI-PDFF, US and UDFF. Inclusion criteria were: (a) no chronic liver disease or jaundice; (b) no MRI motion artifacts; (c) adequate liver examination at US. Exclusion criteria were: (a) alcohol abuse, chronic hepatitis, cirrhosis, or jaundice; (b) MRI artifacts or insufficient US examination. The median of 10 MRI-PDFF and UDFF measurements in the right hepatic lobe was analyzed. UDFF and MRI-PDFF were compared by Bland-Altman difference plot and Pearson's test. Sensitivity, specificity, positive and negative predictive values, accuracy, and area under the receiver-operator curve (AUC-ROC) of US and UDFF were calculated using an MRI-PDFF cut-off value of 5%. p values ≤ 0.05 were statistically significant.

RESULTS

122 patients were included (61 men, mean age 60 years, standard deviation 15 years). The median MRI-PDFF value was 4.1% (interquartile range 2.9-6); 37.7% patients had a median MRI-PDFF value ≥ 5%. UDFF and MRI-PDFF had high agreement (p = 0.11) and positive correlation (⍴ = 0.81, p < 0.001). UDFF had a higher diagnostic value than US for the detection of steatosis, with AUC-ROCs of 0.75 (95% CI 0.65, 0.84) and 0.53 (95% CI 0.42, 0.64), respectively.

CONCLUSIONS

UDFF reliably quantifies liver fat content and improves the diagnostic value of US for the detection of hepatic steatosis.

Comparison of Radiologists and Deep Learning for US Grading of Hepatic Steatosis

Background Screening for nonalcoholic fatty liver disease (NAFLD) is suboptimal due to the subjective interpretation of US images. Purpose To evaluate the agreement and diagnostic performance of radiologists and a deep learning model in grading hepatic steatosis in NAFLD at US, with biopsy as the reference standard. Materials and Methods This retrospective study included patients with NAFLD and control patients without hepatic steatosis who underwent abdominal US and contemporaneous liver biopsy from September 2010 to October 2019. Six readers visually graded steatosis on US images twice, 2 weeks apart. Reader agreement was assessed with use of κ statistics. Three deep learning techniques applied to B-mode US images were used to classify dichotomized steatosis grades. Classification performance of human radiologists and the deep learning model for dichotomized steatosis grades (S0, S1, S2, and S3) was assessed with area under the receiver operating characteristic curve (AUC) on a separate test set. Results The study included 199 patients (mean age, 53 years ± 13 [SD]; 101 men). On the test set (n = 52), radiologists had fair interreader agreement (0.34 [95% CI: 0.31, 0.37]) for classifying steatosis grades S0 versus S1 or higher, while AUCs were between 0.49 and 0.84 for radiologists and 0.85 (95% CI: 0.83, 0.87) for the deep learning model. For S0 or S1 versus S2 or S3, radiologists had fair interreader agreement (0.30 [95% CI: 0.27, 0.33]), while AUCs were between 0.57 and 0.76 for radiologists and 0.73 (95% CI: 0.71, 0.75) for the deep learning model. For S2 or lower versus S3, radiologists had fair interreader agreement (0.37 [95% CI: 0.33, 0.40]), while AUCs were between 0.52 and 0.81 for radiologists and 0.67 (95% CI: 0.64, 0.69) for the deep learning model. Conclusion Deep learning approaches applied to B-mode US images provided comparable performance with human readers for detection and grading of hepatic steatosis. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Tuthill in this issue.

Clinical Application of Quantitative MR Imaging in Nonalcoholic Fatty Liver Disease

Viral hepatitis was previously the most common cause of chronic liver disease. However, in recent years, nonalcoholic fatty liver disease (NAFLD) cases have been increasing, especially in developed countries. NAFLD is histologically characterized by fat, fibrosis, and inflammation in the liver, eventually leading to cirrhosis and hepatocellular carcinoma. Although biopsy is the gold standard for the assessment of the liver parenchyma, quantitative evaluation methods, such as ultrasound, CT, and MRI, have been reported to have good diagnostic performances. The quantification of liver fat, fibrosis, and inflammation is expected to be clinically useful in terms of the prognosis, early intervention, and treatment response for the management of NAFLD. The aim of this review was to discuss the basics and prospects of MRI-based tissue quantifications of the liver, mainly focusing on proton density fat fraction for the quantification of fat deposition, MR elastography for the quantification of fibrosis, and multifrequency MR elastography for the evaluation of inflammation.

Discordance diagnosis between B-mode ultrasonography and MRI proton density fat fraction for fatty liver

We aimed to evaluate the frequency and causes of discordant results in fatty liver (FL) diagnosis between B-mode ultrasonography (B-USG) and magnetic resonance imaging proton density fat fraction (MRI-PDFF). We analyzed patients who underwent both B-USG and MRI-PDFF within a 6-month interval. We made a confusion matrix for FL diagnosis between B-USG and MRI-PDFF and identified four discordant groups as follows: (1) the "UFL-MnFL-wo" group [B-USG FL-MRI-PDFF no FL without chronic liver disease (CLD) or liver cirrhosis (LC)]; (2) the "UFL-MnFL-w" group (B-USG FL-MRI-PDFF no FL with CLD or LC); (3) the "UnFL-MFL-wo" group (B-USG no FL-MRI-PDFF FL without CLD or LC); and (4) the "UnFL-MFL-w" group (B-USG no FL-MRI-PDFF FL with CLD or LC). We compared the "UFL-MnFL-wo" group with the control group in terms of various parameters. We found 201 patients (201/1514, 13.3%) with discordant results for FL diagnosis between B-USG and MRI-PDFF. The "UFL-MnFL-wo" group accounted for the largest portion at 6.8% (103/1514), followed by the "UFL-MnFL-w" group (79/1514, 5.2%) and the "UnFL-MFL-w" group (16/1514, 1.1%). The mean and right PDFF values, body mass index, and abdominal wall thickness were significantly higher in the "UFL-MnFL-wo" group than in the control group (p ≤ 0.001). The frequency of discordant results in the diagnosis of FL between B-USG and MRI-PDFF could be identified. The causes of discordant results were that B-USG was fairly accurate in diagnosing FL disease and that accompanying CLD or LC hindered the evaluation of FL.

Application of multi-echo Dixon and MRS in quantifying hepatic fat content and staging liver fibrosis

This study associated the liver proton density fat fraction (PDFF), measured by multi-echo Dixon (ME-Dixon) and breath-hold single-voxel high-speed T2-corrected multi-echo 1H magnetic resonance spectroscopy (HISTO) at 1.5 T, with serum biomarkers and liver fibrosis stages. This prospective study enrolled 75 patients suspected of liver fibrosis and scheduled for liver biopsy and 23 healthy participants with normal liver function. The participant underwent ME-Dixon and HISTO scanning. The agreement of PDFF measured by ME-Dixon (PDFF-D) and HISTO (PDFF-H) were compared. Correlations between PDFF and serum fat biomarkers (total cholesterol, triglyceride, and high- and low-density lipoproteins) and the liver fibrosis stages were assessed. PDFF were compared among the liver fibrosis stages (F0-F4) based on clinical liver biopsies. The Bland-Altman plot showed agreement between PDFF-D and PDFF-H(LoA, - 4.44 to 6.75), which have high consistency (ICC 0.752, P < 0.001). The correlations with the blood serum markers were mild to moderate (PDFF-H: r = 0.261-0.410, P < 0.01; PDFF-D: r = 0.265-0.367, P < 0.01). PDFF-D, PDFF-H, and steatosis were distributed similarly among the liver fibrosis stages. PDFF-H showed a slight negative correlation with the liver fibrosis stages (r = - 0.220, P = 0.04). Both ME-Dixon and HISTO sequences measured liver fat content noninvasively. Liver fat content was not directly associated with liver fibrosis stages.

US Quantification of Liver Fat: Past, Present, and Future

Fatty liver disease has a high and increasing prevalence worldwide, is associated with adverse cardiovascular events and higher long-term medical costs, and may lead to liver-related morbidity and mortality. There is an urgent need for accurate, reproducible, accessible, and noninvasive techniques appropriate for detecting and quantifying liver fat in the general population and for monitoring treatment response in at-risk patients. CT may play a potential role in opportunistic screening, and MRI proton-density fat fraction provides high accuracy for liver fat quantification; however, these imaging modalities may not be suited for widespread screening and surveillance, given the high global prevalence. US, a safe and widely available modality, is well positioned as a screening and surveillance tool. Although well-established qualitative signs of liver fat perform well in moderate and severe steatosis, these signs are less reliable for grading mild steatosis and are likely unreliable for detecting subtle changes over time. New and emerging quantitative biomarkers of liver fat, such as those based on standardized measurements of attenuation, backscatter, and speed of sound, hold promise. Evolving techniques such as multiparametric modeling, radiofrequency envelope analysis, and artificial intelligence-based tools are also on the horizon. The authors discuss the societal impact of fatty liver disease, summarize the current state of liver fat quantification with CT and MRI, and describe past, currently available, and potential future US-based techniques for evaluating liver fat. For each US-based technique, they describe the concept, measurement method, advantages, and limitations. © RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center.

Effect of aerobic exercise training on the fat fraction of the liver in persons with chronic hepatitis B and hepatic steatosis: Trial protocol for a randomized controlled intervention trial- The FitLiver study

BACKGROUND

The global prevalence of chronic hepatitis B is more than 300 million people, and in Denmark, 17,000 people are estimated to have chronic hepatitis B. Untreated, chronic hepatitis B can lead to the development of liver cirrhosis and liver cancer. There is no curable therapy. In persons with obesity and chronic hepatitis B infection, the development of hepatic steatosis imposes a double burden on the liver, leading to an increased risk of cirrhosis and liver cancer. In patients without chronic hepatitis B, exercise interventions have shown beneficial effects on hepatic steatosis through improvements in fat fraction of the liver, insulin resistance, fatty acid metabolism, and glucose metabolism, as well as activation of liver-induced regulatory protein secretion (hepatokines) after the exercise intervention.

OBJECTIVE

To investigate in persons with chronic hepatitis B and hepatic steatosis: Primary: Whether exercise will decrease the fat fraction of the liver. Secondary: If exercise will affect hepatokine secretion and if it will improve lipid- and glucose metabolism, liver status, markers of inflammation, body composition, and blood pressure.

METHODS

A randomized, controlled, clinical intervention trial consisting of 12 weeks of aerobic exercise training or no intervention. Thirty persons with chronic hepatitis B and hepatic steatosis will be randomized 1:1. Before and after the intervention, participants will undergo an MRI scan of the liver, blood sampling, oral glucose tolerance test, fibroscan, VO2_max test, DXA scan, blood pressure measurements, and optional liver biopsy. Lastly, a hormone infusion test with somatostatin and glucagon to increase the glucagon/insulin ratio for stimulating secretion of circulating hepatokines will be performed. The training program includes three weekly training sessions of 40 min/session over 12 weeks.

DISCUSSION

This trial, investigating high-intensity interval training in persons with chronic hepatitis B and hepatic steatosis, is the first exercise intervention trial performed on this group of patients. If exercise reduces hepatic steatosis and induces other beneficial effects of clinical markers in this group of patients, there might be an indication to recommend exercise as part of treatment. Furthermore, the investigation of the effect of exercise on hepatokine secretion will provide more knowledge on the effects of exercise on the liver.

TRIAL REGISTRATION

Danish Capital Regions committee on health research ethics reference: H-21034236 (version 1.4 date: 19-07-2022) and ClinicalTrials.gov: NCT05265026.

Liver Fibrosis, Fat, and Iron Evaluation with MRI and Fibrosis and Fat Evaluation with US: A Practical Guide for Radiologists

Quantitative imaging biomarkers of liver disease measured by using MRI and US are emerging as important clinical tools in the management of patients with chronic liver disease (CLD). Because of their high accuracy and noninvasive nature, in many cases, these techniques have replaced liver biopsy for the diagnosis, quantitative staging, and treatment monitoring of patients with CLD. The most commonly evaluated imaging biomarkers are surrogates for liver fibrosis, fat, and iron. MR elastography is now routinely performed to evaluate for liver fibrosis and typically combined with MRI-based liver fat and iron quantification to exclude or grade hepatic steatosis and iron overload, respectively. US elastography is also widely performed to evaluate for liver fibrosis and has the advantage of lower equipment cost and greater availability compared with those of MRI. Emerging US fat quantification methods can be performed along with US elastography. The author group, consisting of members of the Society of Abdominal Radiology (SAR) Liver Fibrosis Disease-Focused Panel (DFP), the SAR Hepatic Iron Overload DFP, and the European Society of Radiology, review the basics of liver fibrosis, fat, and iron quantification with MRI and liver fibrosis and fat quantification with US. The authors cover technical requirements, typical case display, quality control and proper measurement technique and case interpretation guidelines, pitfalls, and confounding factors. The authors aim to provide a practical guide for radiologists interpreting these examinations. ^© RSNA, 2023 See the invited commentary by Ronot in this issue. Quiz questions for this article are available in the supplemental material.

Development and accuracy validation of a fat fraction imaging biomarker for sialadenitis in the parotid gland

BACKGROUND

The diagnosis of sialadenitis, the most frequent disease of the salivary glands, is challenging when the symptoms are mild. In such cases, biomarkers can be used as definitive diagnostic indicators. Recently, biomarkers have been developed by extracting and analyzing pathological and morphological features from medical imaging. This study aimed to establish a diagnostic reference for sialadenitis based on the quantitative magnetic resonance imaging (MRI) biomarker IDEAL-IQ and assess its accuracy.

METHODS

Patients with sialadenitis (n = 46) and control subjects (n = 90) that underwent MRI were selected. Considering that the IDEAL-IQ value is a sensitive fat fractional marker to the body mass index (BMI), all subjects were also categorized as under-, normal-, and overweight. The fat fraction of parotid gland in the control and sialadenitis groups were obtained using IDEAL-IQ map. The values from the subjects in the control and sialadenitis groups were compared in each BMI category. For comparison, t-tests and receiver operating characteristic (ROC) curve analyses were performed.

RESULTS

The IDEAL-IQ fat faction of the control and sialadenitis glands were 38.57% and 23.69%, respectively, and the differences were significant. The values were significantly lower in the sialadenitis group (P), regardless of the BMI types. The area under the ROC curve (AUC) was 0.83 (cut-off value: 28.72) in patients with sialadenitis. The AUC for under-, normal-, and overweight individuals were 0.78, 0.81, and 0.92, respectively.

CONCLUSIONS

The fat fraction marker based on the IDEAL-IQ method was useful as an objective indicator for diagnosing sialadenitis. This marker would aid less-experienced clinicians in diagnosing sialadenitis.

Noninvasive biomarkers in pediatric nonalcoholic fatty liver disease

Nonalcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease worldwide among children and adolescents. It encompasses a spectrum of disease, from its mildest form of isolated steatosis, to nonalcoholic steatohepatitis (NASH) to liver fibrosis and cirrhosis, or end-stage liver disease. The early diagnosis of pediatric NAFLD is crucial in preventing disease progression and in improving outcomes. Currently, liver biopsy is the gold standard for diagnosing NAFLD. However, given its invasive nature, there has been significant interest in developing noninvasive methods that can be used as accurate alternatives. Here, we review noninvasive biomarkers in pediatric NAFLD, focusing primarily on the diagnostic accuracy of various biomarkers as measured by their area under the receiver operating characteristic, sensitivity, and specificity. We examine two major approaches to noninvasive biomarkers in children with NAFLD. First, the biological approach that quantifies serological biomarkers. This includes the study of individual circulating molecules as biomarkers as well as the use of composite algorithms derived from combinations of biomarkers. The second is a more physical approach that examines data measured through imaging techniques as noninvasive biomarkers for pediatric NAFLD. Each of these approaches was applied to children with NAFLD, NASH, and NAFLD with fibrosis. Finally, we suggest possible areas for future research based on current gaps in knowledge.

Non-Invasive Imaging Methods to Evaluate Non-Alcoholic Fatty Liver Disease with Fat Quantification: A Review

Hepatic steatosis without specific causes (e.g., viral infection, alcohol abuse, etc.) is called non-alcoholic fatty liver disease (NAFLD), which ranges from non-alcoholic fatty liver (NAFL) to non-alcoholic steatohepatitis (NASH), fibrosis, and NASH-related cirrhosis. Despite the usefulness of the standard grading system, liver biopsy has several limitations. In addition, patient acceptability and intra- and inter-observer reproducibility are also concerns. Due to the prevalence of NAFLD and limitations of liver biopsies, non-invasive imaging methods such as ultrasonography (US), computed tomography (CT), and magnetic resonance imaging (MRI) that can reliably diagnose hepatic steatosis have developed rapidly. US is widely available and radiation-free but cannot examine the entire liver. CT is readily available and helpful for detection and risk classification, significantly when analyzed using artificial intelligence; however, it exposes users to radiation. Although expensive and time-consuming, MRI can measure liver fat percentage with magnetic resonance imaging proton density fat fraction (MRI-PDFF). Specifically, chemical shift-encoded (CSE)-MRI is the best imaging indicator for early liver fat detection. The purpose of this review is to provide an overview of each imaging modality with an emphasis on the recent progress and current status of liver fat quantification.

Body composition profiling at 0.55T: Feasibility and precision

PURPOSE

Body composition MRI captures the distribution of fat and lean tissues throughout the body, and provides valuable biomarkers of obesity, metabolic disease, and muscle disorders, as well as risk assessment. Highly reproducible protocols have been developed for 1.5T and 3T MRI. The purpose of this work was to demonstrate the feasibility and test-retest repeatability of MRI body composition profiling on a 0.55T whole-body system.

METHODS

Healthy adult volunteers were scanned on a whole-body 0.55T MRI system using the integrated body RF coil. Experiments were performed to refine parameter settings such as TEs, resolution, flip angle, bandwidth, acceleration, and oversampling factors. The final protocol was evaluated using a test-retest study with subject removal and replacement in 10 adult volunteers (5 M/5F, age 25-60, body mass index 20-30).

RESULTS

Compared to 1.5T and 3T, the optimal flip angle at 0.55T was higher (15°), due to the shorter T1 times, and the optimal echo spacing was larger, due to smaller chemical shift between water and fat. Overall image quality was comparable to conventional field strengths, with no significant issues with fat/water swapping or inadequate SNR. Repeatability coefficient of visceral fat, subcutaneous fat, total thigh muscle volume, muscle fat infiltration, and liver fat were 11.8 cL (2.2%), 46.9 cL (1.9%), 14.6 cL (0.5%), 0.1 pp (2%), and 0.2 pp (5%), respectively (coefficient of variation in parenthesis).

CONCLUSIONS

We demonstrate that 0.55T body composition MRI is feasible and present optimized scan parameters. The resulting images provide satisfactory quality for automated post-processing and produce repeatable results.

Multiparametric MR assessment of liver fat, iron, and fibrosis: a concise overview of the liver "Triple Screen"

Chronic liver disease (CLD) is a common source of morbidity and mortality worldwide. Non-alcoholic fatty liver disease (NAFLD) serves as a major cause of CLD with a rising annual prevalence. Additionally, iron overload can be both a cause and effect of CLD with a negative synergistic effect when combined with NAFLD. The development of state-of-the-art multiparametric MR solutions has led to a change in the diagnostic paradigm in CLD, shifting from traditional liver biopsy to innovative non-invasive methods for providing accurate and reliable detection and quantification of the disease burden. Novel imaging biomarkers such as MRI-PDFF for fat, R2 and R2* for iron, and liver stiffness for fibrosis provide important information for diagnosis, surveillance, risk stratification, and treatment. In this article, we provide a concise overview of the MR concepts and techniques involved in the detection and quantification of liver fat, iron, and fibrosis including their relative strengths and limitations and discuss a practical abbreviated MR protocol for clinical use that integrates these three MR biomarkers into a single simplified MR assessment. Multiparametric MR techniques provide accurate and reliable non-invasive detection and quantification of liver fat, iron, and fibrosis. These techniques can be combined in a single abbreviated MR "Triple Screen" assessment to offer a more complete metabolic imaging profile of CLD.

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.

MAGORINO: Magnitude-only fat fraction and R* 2 estimation with Rician noise modeling

PURPOSE

Magnitude-based fitting of chemical shift-encoded data enables proton density fat fraction (PDFF) and R 2 * $$ {R}_2^{\ast } $$ estimation where complex-based methods fail or when phase data are inaccessible or unreliable. However, traditional magnitude-based fitting algorithms do not account for Rician noise, creating a source of bias. To address these issues, we propose an algorithm for magnitude-only PDFF and R 2 * $$ {R}_2^{\ast } $$ estimation with Rician noise modeling (MAGORINO).

METHODS

Simulations of multi-echo gradient-echo signal intensities are used to investigate the performance and behavior of MAGORINO over the space of clinically plausible PDFF, R 2 * $$ {R}_2^{\ast } $$ , and SNR values. Fitting performance is assessed through detailed simulation, including likelihood function visualization, and in a multisite, multivendor, and multi-field-strength phantom data set and in vivo.

RESULTS

Simulations show that Rician noise-based magnitude fitting outperforms existing Gaussian noise-based fitting and reveals two key mechanisms underpinning the observed improvement. First, the likelihood functions exhibit two local optima; Rician noise modeling increases the chance that the global optimum corresponds to the ground truth. Second, when the global optimum corresponds to ground truth for both noise models, the optimum from Rician noise modeling is closer to ground truth. Multisite phantom experiments show good agreement of MAGORINO PDFF with reference values, and in vivo experiments replicate the performance benefits observed in simulation.

CONCLUSION

The MAGORINO algorithm reduces Rician noise-related bias in PDFF and R 2 * $$ {R}_2^{\ast } $$ estimation, thus addressing a key limitation of existing magnitude-only fitting methods. Our results offer insight into the importance of the noise model for selecting the correct optimum when multiple plausible optima exist.

MRI Quantification of Placebo Effect in Nonalcoholic Steatohepatitis Clinical Trials

Background Several early-phase clinical trials for the treatment of nonalcoholic steatohepatitis (NASH) use liver fat content as measured with the MRI-derived proton density fat fraction (PDFF) for a primary outcome. These trials have shown relative reductions in liver fat content with placebo treatment alone, a phenomenon termed "the placebo effect." This phenomenon confounds the results and limits generalizability to future trials. Purpose To quantify the effect of placebo treatment on change in the absolute PDFF value and to identify variables associated with this observed change. Materials and Methods This is a secondary analysis of prospectively collected data from seven early phase clinical trials that included participants with a diagnosis of NASH based on MRI and/or liver biopsy who received placebo treatment. The primary outcome was a greater than or equal to 30% relative reduction in PDFF after placebo treatment. Normalization of PDFF, relative change in alanine aminotransferase (ALT) level, and normalization of ALT level were also examined. An exploratory linear mixed-effects model was used to estimate an overall change in absolute PDFF and to explore parameters associated with this response. Results A total of 187 participants (median age, 52 years [IQR, 43-60 years]; 114 women) who received placebo treatment were evaluated. A greater than or equal to 30% relative reduction in baseline PDFF was seen in 20% of participants after 12 weeks of placebo treatment (10 of 49), 9% of participants after 16 weeks (two of 22), and 28% of participants after 24 weeks (34 of 122). A repeated-measures linear mixed-effects model estimated a decrease of 2.3 units (median relative reduction of 13%) in absolute PDFF values after 24 weeks of placebo treatment (95% CI: 3.2, 1.4; P < .001). Conclusion In this analysis of 187 participants, a clinically relevant decrease in PDFF was observed with placebo treatment. Based on the study model, assuming an absolute PDFF decrease of approximately 3 units (upper limit of 95% CI) to account for this "placebo effect" in sample size calculations for future clinical trials is suggested. Clinical trial registration nos. NCT01066364, NCT01766713, NCT01963845, NCT02443116, NCT02546609, NCT02316717, and NCT02442687 © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Yoon in this issue.

Repeatability of Quantitative Magnetic Resonance Imaging Biomarkers in the Tibia Bone Marrow of a Murine Myelofibrosis Model

Quantitative MRI biomarkers are sought to replace painful and invasive sequential bone-marrow biopsies routinely used for myelofibrosis (MF) cancer monitoring and treatment assessment. Repeatability of MRI-based quantitative imaging biomarker (QIB) measurements was investigated for apparent diffusion coefficient (ADC), proton density fat fraction (PDFF), and magnetization transfer ratio (MTR) in a JAK2 V617F hematopoietic transplant model of MF. Repeatability coefficients (RCs) were determined for three defined tibia bone-marrow sections (2-9 mm; 10-12 mm; and 12.5-13.5 mm from the knee joint) across 15 diseased mice from 20-37 test-retest pairs. Scans were performed on consecutive days every two weeks for a period of 10 weeks starting 3-4 weeks after transplant. The mean RC with (95% confidence interval (CI)) for these sections, respectively, were for ADC: 0.037 (0.031, 0.050), 0.087 (0.069, 0.116), and 0.030 (0.022, 0.044) μm²/ms; for PDFF: 1.6 (1.3, 2.0), 15.5 (12.5, 20.2), and 25.5 (12.0, 33.0)%; and for MTR: 0.16 (0.14, 0.19), 0.11 (0.09, 0.15), and 0.09 (0.08, 0.15). Change-trend analysis of these QIBs identified a dynamic section within the mid-tibial bone marrow in which confident changes (exceeding RC) could be observed after a four-week interval between scans across all measured MRI-based QIBs. Our results demonstrate the capability to derive quantitative imaging metrics from mouse tibia bone marrow for monitoring significant longitudinal MF changes.

Using Free-Breathing MRI to Quantify Pancreatic Fat and Investigate Spatial Heterogeneity in Children

BACKGROUND

MRI acquisition for pediatric pancreatic fat quantification is limited by breath-holds (BH). Full segmentation (FS) or small region of interest (ROI) analysis methods may not account for pancreatic fat spatial heterogeneity, which may limit accuracy.

PURPOSE

To improve MRI acquisition and analysis for quantifying pancreatic proton-density fat fraction (pPDFF) in children by investigating free-breathing (FB)-MRI, characterizing pPDFF spatial heterogeneity, and relating pPDFF to clinical markers.

STUDY TYPE

Prospective.

POPULATION

A total of 34 children, including healthy (N = 16, 8 female) and overweight (N = 18, 5 female) subjects.

FIELD STRENGTH AND SEQUENCES

3 T; multiecho gradient-echo three-dimensional (3D) stack-of-stars FB-MRI, multiecho gradient-echo 3D Cartesian BH-MRI.

ASSESSMENT

A radiologist measured FS- and ROI-based pPDFF on FB-MRI and BH-MRI PDFF maps, with anatomical images as references. Regional pPDFF in the pancreatic head, body, and tail were measured on FB-MRI. FS-pPDFF, ROI-pPDFF, and regional pPDFF were compared, and related to clinical markers, including hemoglobin A1c.

STATISTICAL TESTS

T-test, Bland-Altman analysis, Lin's concordance correlation coefficient (CCC), one-way analysis of variance, and Spearman's rank correlation coefficient were used. P < 0.05 was considered significant.

RESULTS

FS-pPDFF and ROI-pPDFF from FB-MRI and BH-MRI had mean difference = 0.4%; CCC was 0.95 for FS-pPDFF and 0.62 for ROI-pPDFF. FS-pPDFF was higher than ROI-pPDFF (10.4% ± 6.4% vs. 4.2% ± 2.8%). Tail-pPDFF (11.6% ± 8.1%) was higher than body-pPDFF (8.9% ± 6.3%) and head-pPDFF (8.7% ± 5.2%). Head-pPDFF and body-pPDFF positively correlated with hemoglobin A1c.

DATA CONCLUSION

FB-MRI pPDFF is comparable to BH-MRI. Spatial heterogeneity affects pPDFF quantification. Regional measurements of pPDFF in the head and body were correlated with hemoglobin A1c, a marker of insulin sensitivity.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Impact of physiological parameters on the parotid gland fat fraction in a normal population

Quantifying physiological fat tissue in the organs is important to further assess the organ's pathologic status. This study aimed to investigate the impact of body mass index (BMI), age, and sex on the fat fraction of normal parotid glands. Patients undergoing magnetic resonance imaging (MRI) of iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL-IQ) due to non-salivary gland-related disease were reviewed. Clinical information of individual patients was categorized into groups based on BMI (under/normal/overweight), age (age I/age II/age III), and sex (female/male) and an inter-group comparison of the fat fraction values of both parotid glands was conducted. Overall, in the 626 parotid glands analyzed, the fat fraction of the gland was 35.80%. The mean fat fraction value increased with BMI (30.23%, 35.74%, and 46.61% in the underweight, normal and overweight groups, respectively [p < 0.01]) and age (32.42%, 36.20%, and 41.94% in the age I, II, and III groups, respectively [p < 0.01]). The fat content of normal parotid glands varies significantly depending on the body mass and age regardless of sex. Therefore, the patient's age and body mass should be considered when evaluating fatty change in the parotid glands in imaging results.

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.

Pregnancies complicated by gestational diabetes and fetal growth restriction: an analysis of maternal and fetal body composition using magnetic resonance imaging

INTRODUCTION

Maternal body composition may influence fetal body composition.

OBJECTIVE

The objective of this pilot study was to investigate the relationship between maternal and fetal body composition.

METHODS

Three pregnant women cohorts were studied: healthy, gestational diabetes (GDM), and fetal growth restriction (FGR). Maternal body composition (visceral adipose tissue volume (VAT), subcutaneous adipose tissue volume (SAT), pancreatic and hepatic proton-density fat fraction (PDFF) and fetal body composition (abdominal SAT and hepatic PDFF) were measured using MRI between 30 to 36 weeks gestation.

RESULTS

Compared to healthy and FGR fetuses, GDM fetuses had greater hepatic PDFF (5.2 [4.2, 5.5]% vs. 3.2 [3, 3.3]% vs. 1.9 [1.4, 3.7]%, p = 0.004). Fetal hepatic PDFF was associated with maternal SAT (r = 0.47, p = 0.02), VAT (r = 0.62, p = 0.002), and pancreatic PDFF (r = 0.54, p = 0.008). When controlling for maternal SAT, GDM increased fetal hepatic PDFF by 0.9 ([0.51, 1.3], p = 0.001).

CONCLUSION

In this study, maternal SAT, VAT, and GDM status were positively associated with fetal hepatic PDFF.

MR Fingerprinting for Liver Tissue Characterization: A Histopathologic Correlation Study

Background Liver MR fingerprinting (MRF) enables simultaneous quantification of T1, T2, T2*, and proton density fat fraction (PDFF) maps in single breath-hold acquisitions. Histopathologic correlation studies are desired for its clinical use. Purpose To compare liver MRF-derived metrics with separate reference quantitative MRI in participants with diffuse liver disease, evaluate scan-rescan repeatability of liver MRF, and validate MRF-derived measurements for histologic grading of liver biopsies. Materials and Methods This prospective study included participants with diffuse liver disease undergoing MRI from July 2021 to January 2022. Participants underwent two-dimensional single-section liver MRF and separate reference quantitative MRI. Linear regression, Bland-Altman plots, and coefficients of variation were used to assess the bias and repeatability of liver MRF measurements. For participants undergoing liver biopsy, the association between mapping and histologic grading was evaluated by using the Spearman correlation coefficient. Results Fifty-six participants (mean age, 59 years ± 15 [SD]; 32 women) were included to compare mapping techniques and 23 participants were evaluated with liver biopsy (mean age, 52.7 years ± 12.7; 14 women). The linearity of MRF with reference measurements in participants with diffuse liver disease (R² value) for T1, T2, T2*, and PDFF maps was 0.86, 0.88, 0.54, and 0.99, respectively. The overall coefficients of variation for repeatability in the liver were 3.2%, 5.5%, 7.1%, and 4.6% for T1, T2, T2*, and PDFF maps, respectively. MRF-derived metrics showed high diagnostic performance in differentiating moderate or severe changes from mild or no changes (area under the receiver operating characteristic curve for fibrosis, inflammation, steatosis, and siderosis: 0.62 [95% CI: 0.52, 0.62], 0.92 [95% CI: 0.88, 0.92], 0.97 [95% CI: 0.96, 0.97], and 0.74 [95% CI: 0.57, 0.74], respectively). Conclusion Liver MR fingerprinting provided repeatable T1, T2, T2*, and proton density fat fraction maps in high agreement with reference quantitative mapping and may correlate with pathologic grades in participants with diffuse liver disease. © RSNA, 2022 Online supplemental material is available for this article.