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.

Multiparametric ultrasound imaging for early-stage steatosis: Comparison with magnetic resonance imaging-based proton density fat fraction

BACKGROUND

The prevalence of liver diseases, especially steatosis, requires a more convenient and noninvasive tool for liver diagnosis, which can be a surrogate for the gold standard biopsy. Magnetic resonance (MR) measurement offers potential, however ultrasound (US) has better accessibility than MR.

PURPOSE

This study aims to suggest a multiparametric US approach which demonstrates better quantification and imaging performance than MR imaging-based proton density fat fraction (MRI-PDFF) for hepatic steatosis assessment.

METHODS

We investigated early-stage steatosis to evaluate our approach. An in vivo (within the living) animal study was performed. Fat inclusions were accumulated in the animal livers by feeding a methionine and choline deficient (MCD) diet for 2 weeks. The animals (n = 19) underwent US and MR imaging, and then their livers were excised for histological staining. From the US, MR, and histology images, fat accumulation levels were measured and compared: multiple US parameters; MRI-PDFF; histology fat percentages. Seven individual US parameters were extracted using B-mode measurement, Burr distribution estimation, attenuation estimation, H-scan analysis, and shear wave elastography. Feature selection was performed, and the selected US features were combined, providing quantification of fat accumulation. The combined parameter was used for visualizing the localized probability of fat accumulation level in the liver; This procedure is known as disease-specific imaging (DSI).

RESULTS

The combined US parameter can sensitively assess fat accumulation levels, which is highly correlated with histology fat percentage (R = 0.93, p-value < 0.05) and outperforms the correlation between MRI-PDFF and histology (R = 0.89, p-value < 0.05). Although the seven individual US parameters showed lower correlation with histology compared to MRI-PDFF, the multiparametric analysis enabled US to outperform MR. Furthermore, this approach allowed DSI to detect and display gradual increases in fat accumulation. From the imaging output, we measured the color-highlighted area representing fatty tissues, and the fat fraction obtained from DSI and histology showed strong agreement (R = 0.93, p-value < 0.05).

CONCLUSIONS

We demonstrated that fat quantification utilizing a combination of multiple US parameters achieved higher performance than MRI-PDFF; therefore, our multiparametric analysis successfully combined selected features for hepatic steatosis characterization. We anticipate clinical use of our proposed multiparametric US analysis, which could be beneficial in assessing steatosis in humans.

Liver Fat Quantification With Ultrasound: Depth Dependence of Attenuation Coefficient

OBJECTIVES

The primary aim was to estimate the influence of various depths on ultrasound attenuation coefficient (AC) of multiple vendors in the liver. The secondary aim was to evaluate the impact of region of interest (ROI) size on AC measurements in a subset of participants.

METHODS

This Institutional Review Board (IRB)-approved Health Insurance Portability and Accountability Act (HIPAA)-compliant retrospective study was carried out in two centers using AC-Canon and AC-Philips algorithms and extracting AC-Siemens values from ultrasound-derived fat fraction algorithm. Measurements were performed positioning ROI upper edge (3 cm size) at 2, 3, 4, 5 cm from the liver capsule with AC-Canon and AC-Philips and at 1.5, 2, 3 cm with Siemens algorithm. In a subset of participants, measurements were obtained with 1 and 3 cm ROI size. Univariate and multivariate linear regression models and Lin's concordance correlation coefficient (CCC) were used for statistical analysis as appropriate.

RESULTS

Three different cohorts were studied. Sixty-three participants (34 females; mean age: 51 ± 14 years) were studied with AC-Canon, 60 (46 females; mean age: 57 ± 11 years) with AC-Philips, and 50 (25 females; 61 ± 13 years) with AC-Siemens. There was a decrease in AC values per 1 cm increase in depth in all. In multivariable analysis, the coefficient was -0.049 (-0.060; -0.038 P < .001) with AC-Canon, -0.058 (-0.066; -0.049 P < .001) with AC-Philips and -0.081 (-0.112; -0.050 P < .001) with AC-Siemens. AC values with 1 cm ROI were significantly higher than those obtained with 3 cm ROI at all depths (P < .001) but the agreement between AC values obtained with different ROI size was excellent (CCC 0.82 [0.77-0.88]).

CONCLUSIONS

There is depth dependence in AC measurement that affects results. A standardized protocol with fixed ROI's depth and size is needed.

Quantification of the renal sinus fat and exploration of its relationship with ectopic fat deposition in normal subjects using MRI fat fraction mapping

Purpose

To determine the renal sinus fat (RSF) volume and fat fraction (FF) in normal Chinese subjects using MRI fat fraction mapping and to explore their associations with age, gender, body mass index (BMI) and ectopic fat deposition.

Methods

A total of 126 subjects were included in the analysis. RSF volume and FF, visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) area, and hepatic and pancreatic FFs were measured for each subject. The comparisons in gender were determined using two-tailed t-tests or the nonparametric Mann-Whitney U-test for normally or non-normally distributed data for continuous variables and the chi-square test for categorical variables. Comparisons of RFS volume and FF between right and left kidneys were determined using paired sample t-tests. Multivariable logistic models were performed to confirm whether RSF differences between men and women are independent of VAT or SAT area. When parameters were normally distributed, the Pearson correlation coefficient was used; otherwise, the Spearman correlation coefficient was applied.

Results

The RSF volumes (cm3) of both kidneys in men (26.86 ± 8.81 for right and 31.62 ± 10.32 for left kidneys) were significantly bigger than those of women (21.47 ± 6.90 for right and 26.03 ± 8.55 for left kidneys) (P < 0.05). The RSF FFs (%) of both kidneys in men (28.33 ± 6.73 for right and 31.21 ± 6.29 for left kidneys) were significantly higher than those of the women (23.82 ± 7.74 for right and 27.92 ± 8.15 for left kidneys) (P < 0.05). The RSF differences between men and women are independent of SAT area and dependent of VAT area (except for right RSF volume). In addition, the RSF volumes and FFs in both kidneys in the overall subjects show significant correlations with age, BMI, VAT area, hepatic fat fraction and pancreatic fat fraction (P < 0.05). However, the patterns of these correlations varied by gender. The RSF volume and FF of left kidney were significantly larger than those of the right kidney (P < 0.05).

Conclusion

The association between renal sinus fat and ectopic fat deposition explored in this study may help establish a consensus on the normal values of RSF volume and FF for the Chinese population. This will facilitate the identification of clinicopathological changes and aid in the investigation of whether RSF volume and FF can serve as early biomarkers for metabolic diseases and renal dysfunction in future studies.

Comparison of CT and Dixon MR Abdominal Adipose Tissue Quantification Using a Unified Computer-Assisted Software Framework

PURPOSE

Reliable and objective measures of abdominal fat distribution across imaging modalities are essential for various clinical and research scenarios, such as assessing cardiometabolic disease risk due to obesity. We aimed to compare quantitative measures of subcutaneous (SAT) and visceral (VAT) adipose tissues in the abdomen between computed tomography (CT) and Dixon-based magnetic resonance (MR) images using a unified computer-assisted software framework.

MATERIALS AND METHODS

This study included 21 subjects who underwent abdominal CT and Dixon MR imaging on the same day. For each subject, two matched axial CT and fat-only MR images at the L2-L3 and the L4-L5 intervertebral levels were selected for fat quantification. For each image, an outer and an inner abdominal wall regions as well as SAT and VAT pixel masks were automatically generated by our software. The computer-generated results were then inspected and corrected by an expert reader.

RESULTS

There were excellent agreements for both abdominal wall segmentation and adipose tissue quantification between matched CT and MR images. Pearson coefficients were 0.97 for both outer and inner region segmentation, 0.99 for SAT, and 0.97 for VAT quantification. Bland-Altman analyses indicated minimum biases in all comparisons.

CONCLUSION

We showed that abdominal adipose tissue can be reliably quantified from both CT and Dixon MR images using a unified computer-assisted software framework. This flexible framework has a simple-to-use workflow to measure SAT and VAT from both modalities to support various clinical research applications.

Motion-resolved fat-fraction mapping with whole-heart free-running multiecho GRE and pilot tone

PURPOSE

To develop a free-running 3D radial whole-heart multiecho gradient echo (ME-GRE) framework for cardiac- and respiratory-motion-resolved fat fraction (FF) quantification.

METHODS

(N_TE  = 8) readouts optimized for water-fat separation and quantification were integrated within a continuous non-electrocardiogram-triggered free-breathing 3D radial GRE acquisition. Motion resolution was achieved with pilot tone (PT) navigation, and the extracted cardiac and respiratory signals were compared to those obtained with self-gating (SG). After extra-dimensional golden-angle radial sparse parallel-based image reconstruction, FF, R₂ *, and B₀ maps, as well as fat and water images were generated with a maximum-likelihood fitting algorithm. The framework was tested in a fat-water phantom and in 10 healthy volunteers at 1.5 T using N_TE  = 4 and N_TE  = 8 echoes. The separated images and maps were compared with a standard free-breathing electrocardiogram (ECG)-triggered acquisition.

RESULTS

The method was validated in vivo, and physiological motion was resolved over all collected echoes. Across volunteers, PT provided respiratory and cardiac signals in agreement (r = 0.91 and r = 0.72) with SG of the first echo, and a higher correlation to the ECG (0.1% of missed triggers for PT vs. 5.9% for SG). The framework enabled pericardial fat imaging and quantification throughout the cardiac cycle, revealing a decrease in FF at end-systole by 11.4% ± 3.1% across volunteers (p < 0.0001). Motion-resolved end-diastolic 3D FF maps showed good correlation with ECG-triggered measurements (FF bias of -1.06%). A significant difference in free-running FF measured with N_TE  = 4 and N_TE  = 8 was found (p < 0.0001 in sub-cutaneous fat and p < 0.01 in pericardial fat).

CONCLUSION

Free-running fat fraction mapping was validated at 1.5 T, enabling ME-GRE-based fat quantification with N_TE  = 8 echoes in 6:15 min.

A Combined Region- and Pixel-Based Deep Learning Approach for Quantifying Abdominal Adipose Tissue in Adolescents Using Dixon Magnetic Resonance Imaging

BACKGROUND

The development of adipose tissue during adolescence may provide valuable insights into obesity-associated diseases. We propose an automated convolutional neural network (CNN) approach using Dixon-based magnetic resonance imaging (MRI) to quantity abdominal subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) in children and adolescents.

METHODS

474 abdominal Dixon MRI scans of 136 young healthy volunteers (aged 8-18) were included in this study. For each scan, an axial fat-only Dixon image located at the L2-L3 disc space and another image at the L4-L5 disc space were selected for quantification. For each image, an outer and an inner region around the abdomen wall, as well as SAT and VAT pixel masks, were generated by expert readers as reference standards. A standard U-Net CNN architecture was then used to train two models: one for region segmentation and one for fat pixel classification. The performance was evaluated using the dice similarity coefficient (DSC) with fivefold cross-validation, and by Pearson correlation and the Student's t-test against the reference standards.

RESULTS

For the DSC results, means and standard deviations of the outer region, inner region, SAT, and VAT comparisons were 0.974 ± 0.026, 0.997 ± 0.003, 0.981 ± 0.025, and 0.932 ± 0.047, respectively. Pearson coefficients were 1.000 for both outer and inner regions, and 1.000 and 0.982 for SAT and VAT comparisons, respectively (all p = NS).

CONCLUSION

These results show that our method not only provides excellent agreement with the reference SAT and VAT measurements, but also accurate abdominal wall region segmentation. The proposed combined region- and pixel-based CNN approach provides automated abdominal wall segmentation as well as SAT and VAT quantification with Dixon MRI and enables objective longitudinal assessment of adipose tissues in children during adolescence.

Automated Measurement of Pancreatic Fat Deposition on Dixon MRI Using nnU-Net

BACKGROUND

Pancreatic fat accumulation may cause or aggravate the process of acute pancreatitis, β-cell dysfunction, T2DM disease, and even be associated with pancreatic tumors. The pathophysiology of fatty pancreas remains overlooked and lacks effective imaging diagnostics.

PURPOSE

To automatically measure the distribution of pancreatic fat deposition on Dixon MRI in multicenter/population datasets using nnU-Net models.

STUDY TYPE

Retrospective.

POPULATION

A total of 176 obese/nonobese subjects (90 males, 86 females; mean age, 27.2 ± 19.7) were enrolled, including a training set (N = 132) and a testing set (N = 44).

FIELD STRENGTH/SEQUENCE

A 3 T and 1.5 T/gradient echo T₁ dual-echo Dixon.

ASSESSMENT

The segmentation results of four types of nnU-Net models were compared using dice similarity coefficient (DSC), positive predicted value (PPV), and sensitivity. The ground truth was the manual delineation by two radiologists according to in-phase (IP) and opposed-phase (OP) images.

STATISTICAL TESTS

The group difference of segmentation results of four models were assessed by the Kruskal-Wallis H test with Dunn-Bonferroni comparisons. The interobserver agreement of pancreatic fat fraction measurements across three observers and test-retest reliability of human and machine were assessed by intragroup correlation coefficient (ICC). P < 0.05 was considered statistically significant.

RESULTS

The three-dimensional (3D) dual-contrast model had significantly improved performance than 2D dual-contrast (DSC/sensitivity) and 3D one-contrast (IP) models (DSC/PPV/sensitivity) and had less errors than 3D one-contrast (OP) model according to higher DSC and PPV (not significant), with a mean DSC of 0.9158, PPV of 0.9105 and sensitivity of 0.9232 in the testing set. The test-retest ICC of this model was above 0.900 in all pancreatic regions, exceeded human.

DATA CONCLUSION

3D Dual-contrast nnU-Net aided segmentation of pancreas on Dixon images appears to be adaptable to multicenter/population datasets. It fully automates the assessment of pancreatic fat distribution and has high reliability.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 3.

Quantification of Liver Fat Content with the iATT Algorithm: Correlation with Controlled Attenuation Parameter

Background: The primary aim of our study was to assess the correlation between an improved version of the attenuation coefficient available on the Arietta 850 ultrasound system (iATT, Fujifilm Healthcare, Tokyo, Japan) and controlled attenuation parameter (CAP). The secondary aim was to assess whether focusing only on iATT acquisition without following the strict protocol for liver stiffness measurements would affect iATT measurement. Methods: Consecutive individuals were enrolled. Pearson’s r was used to test the correlation between ATT and CAP values. The concordance between iATT and CAP was tested using Lin’s concordance correlation coefficient (CCC). Results: 354 individuals (203 males, 151 females) were studied. The overall Pearson correlation between CAP and iATT values obtained following or not following the liver stiffness measurement protocol, respectively, were r = 0.73 and r = 0.71. The correlation was affected by the interquartile range/median (IQR/M) of the 10 measurements: it was r = 0.75 for IQR/M ≤ 15% and r = 0.60 for IQR/M > 15%. CCC showed that there was a moderate to good concordance between iATT and CAP values. Conclusion: iATT shows a strong correlation with CAP that does not decrease when the protocol for liver stiffness acquisition is not followed. The correlation between iATT and CAP values is higher when the IQR/M ≤ 15%.

Feasibility of Ultrasound Attenuation Imaging for Assessing Pediatric Hepatic Steatosis

We investigated the feasibility of ultrasound attenuation imaging (ATI) for assessing pediatric hepatic steatosis. A total of 111 children and adolescents who underwent liver ultrasonography with ATI for suspected hepatic steatosis were included. Participants were classified into the normal, mild, or moderate−severe fatty liver group according to grayscale US findings. Associations between clinical factors, magnetic resonance imaging proton density fat fraction, steatosis stage and ATI values were evaluated. To determine the cutoff values of ATI for staging hepatic steatosis, areas under the curve (AUCs) were analyzed. Factors that could cause measurement failure with ATI were assessed. Of 111 participants, 88 had successful measurement results. Median ATI values were significantly increased according to steatosis stage (p < 0.001). Body mass index (BMI) was a significant factor for increased ATI values (p = 0.047). To differentiate fatty liver from normal liver, a cutoff value of 0.59 dB/cm/MHz could be used with an AUC value of 0.853. To differentiate moderate to severe fatty liver from mild fatty liver, a cutoff value of 0.69 dB/cm/MHz could be used with an AUC value up to 0.91. ATI can be used in children as an effective ultrasonography technique for quantifying and staging pediatric hepatic steatosis.

Quantification of Liver Fat Content after Radiofrequency Ablation for Liver Cancer: Correlation with Hepatic Perfusion Disorders

PURPOSE

To quantitatively investigate the correlation between liver fat content and hepatic perfusion disorders (HPD) after radiofrequency ablation (RFA) for liver cancer using magnetic resonance imaging (MRI)-determined proton density fat fraction (PDFF).

MATERIALS AND METHODS

A total of 150 liver cancer patients underwent liver MRI examination within one month after RFA and at four months after RFA. According to the liver fat content, they were divided into non-, mild, moderate, and severe fatty liver groups. The liver fat content and hepatic perfusion disorders were determined using PDFF images and dynamic contrast-enhanced MRI images. The relationship between the liver fat content and HPD was investigated.

RESULTS

At the first postoperative MRI examination, the proportion of patients in the nonfatty liver group with hyperperfused foci (11.11%) was significantly lower than that in the mild (30.00%), moderate (42.86%), and severe fatty liver (56.67%) groups (p < 0.05), whereas the proportions of patients with hypoperfused foci (6.67%, 7.5%, 5.71%, and 6.67%, respectively) were not significantly different among the four groups (p > 0.05). In the nonfatty liver group, the liver fat content was not correlated with hyperperfusion abnormalities or hypoperfusion abnormalities. By contrast, in the three fatty liver groups, the liver fat content was correlated with hyperperfusion abnormalities but was not correlated with hypoperfusion abnormalities. At the second postoperative MRI examination, six patients in the nonfatty liver group were diagnosed with fatty liver, including two patients with newly developed hyperperfusion abnormalities and one patient whose hypoperfusion abnormality remained the same as it was in the first postoperative MRI examination.

CONCLUSION

There was a high correlation between the liver fat content and hyperperfusion abnormalities after RFA for liver cancer. The higher the liver fat content was, the higher the was risk of hyperperfusion abnormalities. However, there was little correlation between liver fat content and hypoperfusion abnormalities, and the increase in postoperative liver fat content did not induce or alter the presence of hypoperfused foci.

Impact of iron deposit on the accuracy of quantifying liver fat fraction using multi-material decomposition algorithm in dual-energy spectral computed tomography

Objectives

To investigate the accuracy of using multi‐material decomposition (MMD) algorithm in dual‐energy spectral computed tomography (CT) for quantifying fat fraction (FF) in the presence of iron.

Materials

Nine tubes with various proportions of fat and iron were prepared. FF were divided into three levels (10%, 20%, and 30%), recorded as references (FF_ref). Iron concentrations (in mg/100 g) were divided into three ranges (25.25–25.97, 50.38–51.55 and 75.57–77.72). The nine‐tube phantom underwent dual‐energy CT and MR. CT attenuation was measured and FF were determined using MMD in CT (FF_CT) and Iterative Decomposition of water and fat with Echo Asymmetry and Least squares estimation (IDEAL‐IQ) in MR (FF_MR) for each tube. Statistical analyses used were: Spearman rank correlation for correlations between FF_ref and CT attenuation, FF_CT, and FF_MR; one‐way ANOVA, and one‐sample t‐test for the differences between FF_CT and FF_ref and between FF_MR and FF_ref. A multivariate linear regression model was established to analyze the differences between the corresponding values with different iron concentrations under the same FF_ref.

Results

Fat fraction on CT (FFCT) and FF_MR were positively correlated with FF_ref (all p < 0.001), while the CT attenuation was negatively correlated with FF_ref in the three iron concentration ranges. For a given FF_ref, FF_CT decreased and FF_MR increased as the iron concentration increased. The mean difference between FF_CT and FF_ref over the nine tube measurements was 0.25 ± 2.45%, 5.7% lower the 5.98 ± 3.33% value between FF_MR and FF_ref (F = 310.017, p < 0.01).

Conclusion

The phantom results indicate that MMD in dual‐energy CT can directly quantify volumetric FF and is less affected by iron concentration than MR IDEAL‐IQ method.

Deep Learning-Based Parameter Mapping with Uncertainty Estimation for Fat Quantification using Accelerated Free-Breathing Radial MRI

Deep learning has been applied to remove artifacts from undersampled MRI and to replace time-consuming signal fitting in quantitative MRI, but these have usually been treated as separate tasks, which does not fully exploit the shared information. This work proposes a new two-stage framework that completes these two tasks in a concerted approach and also estimates the pixel-wise uncertainty levels. Results from accelerated free-breathing radial MRI for liver fat quantification demonstrate that the proposed framework can achieve high image quality from undersampled radial data, high accuracy for liver fat quantification, and detect uncertainty caused by noisy input data. The proposed framework achieved 3-fold acceleration to <1 min scan time and reduced the computational time for signal fitting to <100 ms/slice in free-breathing liver fat quantification.

Deep Learning-Based Parameter Mapping with Uncertainty Estimation for Fat Quantification using Accelerated Free-Breathing Radial MRI

Deep learning has been applied to remove artifacts from undersampled MRI and to replace time-consuming signal fitting in quantitative MRI, but these have usually been treated as separate tasks, which does not fully exploit the shared information. This work proposes a new two-stage framework that completes these two tasks in a concerted approach and also estimates the pixel-wise uncertainty levels. Results from accelerated free-breathing radial MRI for liver fat quantification demonstrate that the proposed framework can achieve high image quality from undersampled radial data, high accuracy for liver fat quantification, and detect uncertainty caused by noisy input data. The proposed framework achieved 3-fold acceleration to <1 min scan time and reduced the computational time for signal fitting to <100 ms/slice in free-breathing liver fat quantification.

Temperature-corrected proton density fat fraction estimation using chemical shift-encoded MRI in phantoms

PURPOSE

Chemical shift-encoded MRI (CSE-MRI) is well-established to quantify proton density fat fraction (PDFF) as a quantitative biomarker of hepatic steatosis. However, temperature is known to bias PDFF estimation in phantom studies. In this study, strategies were developed and evaluated to correct for the effects of temperature on PDFF estimation through simulations, temperature-controlled experiments, and a multi-center, multi-vendor phantom study.

THEORY AND METHODS

A technical solution that assumes and automatically estimates a uniform, global temperature throughout the phantom is proposed. Computer simulations modeled the effect of temperature on PDFF estimation using magnitude-, complex-, and hybrid-based CSE-MRI methods. Phantom experiments were performed to assess the temperature correction on PDFF estimation at controlled phantom temperatures. To assess the temperature correction method on a larger scale, the proposed method was applied to data acquired as part of a nine-site multi-vendor phantom study and compared to temperature-corrected PDFF estimation using an a priori guess for ambient room temperature.

RESULTS

Simulations and temperature-controlled experiments show that as temperature deviates further from the assumed temperature, PDFF bias increases. Using the proposed correction method and a reasonable a priori guess for ambient temperature, PDFF bias and variability were reduced using magnitude-based CSE-MRI, across MRI systems, field strengths, protocols, and varying phantom temperature. Complex and hybrid methods showed little PDFF bias and variability both before and after correction.

CONCLUSION

Correction for temperature reduces temperature-related PDFF bias and variability in phantoms across MRI vendors, sites, field strengths, and protocols for magnitude-based CSE-MRI, even without a priori information about the temperature.

T1 -corrected quantitative chemical shift-encoded MRI

PURPOSE

To develop and validate a T₁ -corrected chemical-shift encoded MRI (CSE-MRI) method to improve noise performance and reduce bias for quantification of tissue proton density fat-fraction (PDFF).

METHODS

A variable flip angle (VFA)-CSE-MRI method using joint-fit reconstruction was developed and implemented. In computer simulations and phantom experiments, sources of bias measured using VFA-CSE-MRI were investigated. The effect of tissue T₁ on bias using low flip angle (LFA)-CSE-MRI was also evaluated. The noise performance of VFA-CSE-MRI was compared to LFA-CSE-MRI for liver fat quantification. Finally, a prospective pilot study in patients undergoing gadoxetic acid-enhanced MRI of the liver to evaluate the ability of the proposed method to quantify liver PDFF before and after contrast.

RESULTS

VFA-CSE-MRI was accurate and insensitive to transmit B₁ inhomogeneities in phantom experiments and computer simulations. With high flip angles, phase errors because of RF spoiling required modification of the CSE signal model. For relaxation parameters commonly observed in liver, the joint-fit reconstruction improved the noise performance marginally, compared to LFA-CSE-MRI, but eliminated T₁ -related bias. A total of 25 patients were successfully recruited and analyzed for the pilot study. Strong correlation and good agreement between PDFF measured with VFA-CSE-MRI and LFA-CSE-MRI (pre-contrast) was observed before (R² = 0.97; slope = 0.88, 0.81-0.94 95% confidence interval [CI]; intercept = 1.34, -0.77-1.92 95% CI) and after (R² = 0.93; slope = 0.88, 0.78-0.98 95% CI; intercept = 1.90, 1.01-2.79 95% CI) contrast.

CONCLUSION

Joint-fit VFA-CSE-MRI is feasible for T₁ -corrected PDFF quantification in liver, is insensitive to B₁ inhomogeneities, and can eliminate T₁ bias, but with only marginal SNR advantage for T₁ values observed in the liver.

Topics on quantitative liver magnetic resonance imaging

Liver magnetic resonance imaging (MRI) is subject to continuous technical innovations through advances in hardware, sequence and novel contrast agent development. In order to utilize the abilities of liver MR to its full extent and perform high-quality efficient exams, it is mandatory to use the best imaging protocol, to minimize artifacts and to select the most adequate type of contrast agent. In this article, we review the routine clinical MR techniques applied currently and some latest developments of liver imaging techniques to help radiologists and technologists to better understand how to choose and optimize liver MRI protocols that can be used in clinical practice. This article covers topics on (I) fat signal suppression; (II) diffusion weighted imaging (DWI) and intravoxel incoherent motion (IVIM) analysis; (III) dynamic contrast-enhanced (DCE) MR imaging; (IV) liver fat quantification; (V) liver iron quantification; and (VI) scan speed acceleration.

Hierarchical iterative linear-fitting algorithm (HILA) for phase correction in fat quantification by bipolar multi-echo sequence

Background

Multi-echo gradient echo (GRE) sequence with bipolar readout gradients can reduce achievable echo spacing and thus have higher acquisition efficiency compared to unipolar readout gradients for fat fraction (FF) quantification. However, the eddy current induced phase (EC-phase) in a bipolar sequence corrupts the phase consistency between echoes and can lead to inaccurate fat quantification.

Methods

A hierarchical iterative linear-fitting algorithm (HILA) was proposed for EC-phase correction. In each iteration, image blocks were divided into sub-blocks. The EC-phase was fitted to a linear model in each sub-block. The estimated linear phase in each sub-block was then used as a starting value for the next iteration. Finally, a weighted average over all levels was calculated to obtain the final EC-phase map. Monte Carlo simulations were adopted to evaluate how the residual EC-phase would affect FF quantification accuracy. The performance of the proposed HILA method was then compared to the well-established unipolar acquisition method in phantom and in vivo experiments on 3T.

Results

The simulations showed that certain ΔTE values, such as ΔTE =~0.80/1.50/1.95 ms, allowed for FF estimation that were relatively robust to the residual EC-phase ranging from -2π/15 to 2π/15 for a 6-echo bipolar acquisition on 3T. The phantom study showed that the maximum mean FF error, after EC-phase correction with the proposed HILA method, was smaller than 2%, implying that HILA can approximate the high-order term of the EC-phase through step-wise linear fitting. There was no significant difference between the FFs from bipolar and unipolar acquisitions on the two MR systems in the in vivo experiments.

Conclusions

The proposed HILA method provides a simple and efficient EC-phase correction method for bipolar acquisition without acquiring additional data. The appropriate choice of TEs may further reduce the effect of the residual EC-phase on accurate FF quantification with bipolar readout sequence.

Magnetic resonance fingerprinting with dictionary-based fat and water separation (DBFW MRF): A multi-component approach

Purpose

To obtain a fast and robust fat‐water separation with simultaneous estimation of water T₁, fat T₁, and fat fraction maps.

Methods

We modified an MR fingerprinting (MRF) framework to use a single dictionary combination of a water and fat dictionary. A variable TE acquisition pattern with maximum TE = 4.8 ms was used to increase the fat–water separability. Radiofrequency (RF) spoiling was used to reduce the size of the dictionary by reducing T₂ sensitivity. The technique was compared both in vitro and in vivo to an MRF method that incorporated 3‐point Dixon (DIXON MRF), as well as Cartesian IDEAL with different acquisition parameters.

Results

The proposed dictionary‐based fat–water separation technique (DBFW MRF) successfully provided fat fraction, water, and fat T₁, B₀, and B₁₊ maps both in vitro and in vivo. The fat fraction and water T₁ values obtained with DBFW MRF show excellent agreement with DIXON MRF as well as with the reference values obtained using a Cartesian IDEAL with a long TR (concordance correlation coefficient: 0.97/0.99 for fat fraction–water T₁). Whereas fat fraction values with Cartesian IDEAL were degraded in the presence of T₁ saturation, MRF methods successfully estimated and accounted for T₁ in the fat fraction estimates.

Conclusion

The DBFW MRF technique can successfully provide T₁ and fat fraction quantification in under 20 s per slice, intrinsically correcting T₁ biases typical of fast Dixon techniques. These features could improve the diagnostic quality and use of images in presence of fat.

High-Resolution MR Imaging of Muscular Fat Fraction-Comparison of Three T2-Based Methods and Chemical Shift-Encoded Imaging

Chemical shift-encoded imaging (CSEI) is the most common magnetic resonance imaging fat–water separation method. However, when high spatial resolution fat fraction (FF) images are desired, CSEI might be challenging owing to the increased interecho spacing. Here, 3 T₂-based methods have been assessed as alternative methods for obtaining high-resolution FF images. Images from the calf of 10 healthy volunteers were acquired; FF maps were then estimated using 3 T₂-based methods (2- and 3-parameter nonlinear least squares fit and a Bayesian probability method) and CSEI for reference. In addition, simulations were conducted to characterize the performance of various methods. Here, all T₂-based methods resulted in qualitatively improved high-resolution FF images compared with high-resolution CSEI. The 2-parameter fit showed best quantitative agreement to low-resolution CSEI, even at low FF. The estimated T₂-values of fat and water, and the estimated muscle FF of the calf, agreed well with previously published data. In conclusion, T₂-based methods can provide improved high-resolution FF images of the calf compared with the CSEI method.

Optimization of region-of-interest sampling strategies for hepatic MRI proton density fat fraction quantification

BACKGROUND

Clinical trials utilizing proton density fat fraction (PDFF) as an imaging biomarker for hepatic steatosis have used a laborious region-of-interest (ROI) sampling strategy of placing an ROI in each hepatic segment.

PURPOSE

To identify a strategy with the fewest ROIs that consistently achieves close agreement with the nine-ROI strategy.

STUDY TYPE

Retrospective secondary analysis of prospectively acquired clinical research data.

POPULATION

A total of 391 adults (173 men, 218 women) with known or suspected NAFLD.

FIELD STRENGTH/SEQUENCE

Confounder-corrected chemical-shift-encoded 3T MRI using a 2D multiecho gradient-recalled echo technique.

ASSESSMENT

An ROI was placed in each hepatic segment. Mean nine-ROI PDFF and segmental PDFF standard deviation were computed. Segmental and lobar PDFF were compared. PDFF was estimated using every combinatorial subset of ROIs and compared to the nine-ROI average.

STATISTICAL TESTING

Mean nine-ROI PDFF and segmental PDFF standard deviation were summarized descriptively. Segmental PDFF was compared using a one-way analysis of variance, and lobar PDFF was compared using a paired t-test and a Bland-Altman analysis. The PDFF estimated by every subset of ROIs was informally compared to the nine-ROI average using median intraclass correlation coefficients (ICCs) and Bland-Altman analyses.

RESULTS

The study population's mean whole-liver PDFF was 10.1 ± 8.9% (range: 1.1-44.1%). Although there was no significant difference in average segmental (P = 0.452) or lobar (P = 0.154) PDFF, left and right lobe PDFF differed by at least 1.5 percentage points in 25.1% (98/391) of patients. Any strategy with ≥4 ROIs had ICC >0.995. 115 of 126 four-ROI strategies (91%) had limits of agreement (LOA) <1.5%, including four-ROI strategies with two ROIs from each lobe, which all had LOA <1.5%. 14/36 (39%) of two-ROI strategies and 74/84 (88%) of three-ROI strategies had ICC >0.995, and 2/36 (6%) of two-ROI strategies and 46/84 (55%) of three-ROI strategies had LOA <1.5%.

DATA CONCLUSION

Four-ROI sampling strategies with two ROIs in the left and right lobes achieve close agreement with nine-ROI PDFF.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:988-994.

Epidemiology of Hepatic Steatosis at a Tertiary Care Center: An MRI-based Analysis

RATIONALE AND OBJECTIVES

Little is known about the frequency and risk factors of hepatic steatosis in the tertiary care setting. Such knowledge is essential to clinicians making decisions about testing for this condition. Thus, our aim was to describe the epidemiology of hepatic steatosis, as captured by magnetic resonance imaging (MRI), at a tertiary care center.

MATERIALS AND METHODS

A near-consecutive cohort of 1006 adult patients underwent standard-of-care liver MRIs. Images were retrospectively processed to derive proton density fat fraction (PDFF) maps. Data from three spatially distinct regions of interest (ROIs) were aggregated to derive overall hepatic PDFF values. Demographic, anthropometric, clinical, and laboratory variables were included in a multivariate analysis to determine predictors of hepatic steatosis grades (based on established PDFF cutoffs). Hepatic steatosis grades derived from single vs aggregated ROIs were compared.

RESULTS

Hepatic steatosis was observed in 25% of patients (19% grade 1; 3% grade 2; 3% grade 3). Controlling for all other variables, the odds of hepatic steatosis increased by 7%-9% (P <.001) for each whole point increase in body mass index (BMI), whereas elevated serum bilirubin was associated with lower odds of hepatic steatosis (P = .002). Race, diabetes mellitus, dyslipidemia, and metabolic syndrome were not independently predictive of hepatic steatosis when controlling for other variables (eg, BMI). Employing single ROIs (rather than three aggregated ROIs) resulted in incorrect steatosis grading in up to 8.0% of patients.

CONCLUSION

Many adult patients undergoing liver MRI at a tertiary care center have hepatic steatosis, with larger BMIs as the only independent predictor of higher grades. This information can be used by clinicians at such centers to make evidence-based decisions about when to test for hepatic steatosis in their patients.

Sources of systematic error in proton density fat fraction (PDFF) quantification in the liver evaluated from magnitude images with different numbers of echoes

The purpose of this work was to investigate sources of bias in magnetic resonance imaging (MRI) liver fat quantification that lead to a dependence of the proton density fat fraction (PDFF) on the number of echoes. This was a retrospective analysis of liver MRI data from 463 subjects. The magnitude signal variation with TE from spoiled gradient echo images was curve fitted to estimate the PDFF using a model that included monoexponential R₂ * decay and a multi-peak fat spectrum. Additional corrections for non-exponential decay (Gaussian), bi-exponential decay, degree of fat saturation, water frequency shift and noise bias were introduced. The fitting error was minimized with respect to 463 × 3 = 1389 subject-specific parameters and seven additional parameters associated with these corrections. The effect on PDFF was analyzed, notably the dependence on the number of echoes. The effects on R₂ * were also analyzed. The results showed that the inclusion of bias corrections resulted in an increase in the quality of fit (r² ) in 427 of 463 subjects (i.e. 92.2%) and a reduction in the total fitting error (residual norm) of 43.6%. This was largely a result of the Gaussian decay (57.8% of the reduction), fat spectrum (31.0%) and biexponential decay (8.8%) terms. The inclusion of corrections was also accompanied by a decrease in the dependence of PDFF on the number of echoes. Similar analysis of R₂ * showed a decrease in the dependence on the number of echoes. Comparison of PDFF with spectroscopy indicated excellent agreement before and after correction, but the latter exhibited lower bias on a Bland-Altman plot (1.35% versus 0.41%). In conclusion, correction for known and expected biases in PDFF quantification in liver reduces the fitting error, decreases the dependence on the number of echoes and increases the accuracy.

Reliable quantification of marrow fat content and unsaturation level using in vivo MR spectroscopy

PURPOSE

To develop a novel technique for reliable quantification of bone marrow fat content and composition using in vivo MR spectroscopy (MRS).

METHODS

An MRS quantification method combining both advantages of Voigt line shape model and time-domain analysis was developed. The proposed method was tested using computer-simulated data and in vivo data acquired at lumbar vertebral bodies of 23 subjects (age, 83.8 ± 3.7 y; male, n = 13; female, n = 10) from L1 to L4. Reliability and reproducibility were calculated for the quantification results. Comparisons between the proposed method and some conventional methods were conducted.

RESULTS

Low mean absolute percentage errors and low mean coefficients of variation for computer simulations suggest that the proposed method is accurate and precise. By using this method, marrow fat content can be quantified reliably, even for data with low spectral resolution and low signal-to-noise ratio (SNR). Unsaturation level can be reliably quantified for data with moderate spectral resolution and moderate SNR. Results obtained from in vivo data using the proposed method demonstrated better model fit than conventional methods.

CONCLUSION

The method proposed in this study has better performance than conventional methods in the quantification of bone marrow MRS data and has great potential for wide applications of studying marrow fat content and composition. Magn Reson Med 79:1722-1729, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Exploiting multicompartment effects in triple-echo steady-state T2 mapping for fat fraction quantification

PURPOSE

To investigate and exploit the effect of intravoxel off-resonance compartments in the triple-echo steady-state (TESS) sequence without fat suppression for T₂ mapping and to leverage the results for fat fraction quantification.

METHODS

In multicompartment tissue, where at least one compartment is excited off-resonance, the total signal exhibits periodic modulations as a function of echo time (TE). Simulated multicompartment TESS signals were synthesized at various TEs. Fat emulsion phantoms were prepared and scanned at the same TE combinations using TESS. In vivo knee data were obtained with TESS to validate the simulations. The multicompartment effect was exploited for fat fraction quantification in the stomach by acquiring TESS signals at two TE combinations.

RESULTS

Simulated and measured multicompartment signal intensities were in good agreement. Multicompartment effects caused erroneous T₂ offsets, even at low water-fat ratios. The choice of TE caused T₂ variations of as much as 28% in cartilage. The feasibility of fat fraction quantification to monitor the decrease of fat content in the stomach during digestion is demonstrated.

CONCLUSIONS

Intravoxel off-resonance compartments are a confounding factor for T₂ quantification using TESS, causing errors that are dependent on the TE. At the same time, off-resonance effects may allow for efficient fat fraction mapping using steady-state imaging. Magn Reson Med 79:423-429, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Correction of phase errors in quantitative water-fat imaging using a monopolar time-interleaved multi-echo gradient echo sequence

PURPOSE

To propose a phase error correction scheme for monopolar time-interleaved multi-echo gradient echo water-fat imaging that allows accurate and robust complex-based quantification of the proton density fat fraction (PDFF).

METHODS

A three-step phase correction scheme is proposed to address a) a phase term induced by echo misalignments that can be measured with a reference scan using reversed readout polarity, b) a phase term induced by the concomitant gradient field that can be predicted from the gradient waveforms, and c) a phase offset between time-interleaved echo trains. Simulations were carried out to characterize the concomitant gradient field-induced PDFF bias and the performance estimating the phase offset between time-interleaved echo trains. Phantom experiments and in vivo liver and thigh imaging were performed to study the relevance of each of the three phase correction steps on PDFF accuracy and robustness.

RESULTS

The simulation, phantom, and in vivo results showed in agreement with the theory an echo time-dependent PDFF bias introduced by the three phase error sources. The proposed phase correction scheme was found to provide accurate PDFF estimation independent of the employed echo time combination.

CONCLUSION

Complex-based time-interleaved water-fat imaging was found to give accurate and robust PDFF measurements after applying the proposed phase error correction scheme. Magn Reson Med 78:984-996, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Accuracy of Liver Fat Quantification With Advanced CT, MRI, and Ultrasound Techniques: Prospective Comparison With MR Spectroscopy

OBJECTIVE

The purpose of this study was to prospectively evaluate the accuracy of proton-density fat-fraction, single- and dual-energy CT (SECT and DECT), gray-scale ultrasound (US), and US shear-wave elastography (US-SWE) in the quantification of hepatic steatosis with MR spectroscopy (MRS) as the reference standard.

SUBJECTS AND METHODS

Fifty adults who did not have symptoms (23 men, 27 women; mean age, 57 ± 5 years; body mass index, 27 ± 5) underwent liver imaging with un-enhanced SECT, DECT, gray-scale US, US-SWE, proton-density fat-fraction MRI, and MRS for this prospective trial. MRS voxels for the reference standard were colocalized with all other modalities under investigation. For SECT (120 kVp), attenuation values were recorded. For rapid-switching DECT (80/140 kVp), monochromatic images (70-140 keV) and fat density-derived material decomposition images were reconstructed. For proton-density fat fraction MRI, a quantitative chemical shift-encoded method was used. For US, echogenicity was evaluated on a qualitative 0-3 scale. Quantitative US shear-wave velocities were also recorded. Data were analyzed by linear regression for each technique compared with MRS.

RESULTS

There was excellent correlation between MRS and both proton-density fat-fraction MRI (r² = 0.992; slope, 0.974; intercept, -0.943) and SECT (r² = 0.856; slope, -0.559; intercept, 35.418). DECT fat attenuation had moderate correlation with MRS measurements (r² = 0.423; slope, 0.034; intercept, 8.459). There was good correlation between qualitative US echogenicity and MRS measurements with a weighted kappa value of 0.82. US-SWE velocity did not have reliable correlation with MRS measurements (r² = 0.004; slope, 0.069; intercept, 6.168).

CONCLUSION

Quantitative MRI proton-density fat fraction and SECT fat attenuation have excellent linear correlation with MRS measurements and can serve as accurate noninvasive biomarkers for quantifying steatosis. Material decomposition with DECT does not improve the accuracy of fat quantification over conventional SECT attenuation. US-SWE has poor accuracy for liver fat quantification.

Emulsion Stability Modulates Gastric Secretion and Its Mixing with Emulsified Fat in Healthy Adults in a Randomized Magnetic Resonance Imaging Study

BACKGROUND

Oil-in-water emulsions have recently become of interest to nutritional sciences because of their ability to influence gastrointestinal digestive processes and ultimately benefit human health. MRI offers the potential to noninvasively characterize the interaction between emulsified lipids and gastric secretion within the stomach.

OBJECTIVES

We determined noninvasively how emulsion stability modulates volumes of fat and secretion, layering of fat, and the mixing of emulsified fat with secretion within the stomach. This required the development of MRI technology for quantifying fat and secretion concentrations inside the stomach.

METHODS

Twenty-one healthy adults [13 men, mean ± SD age: 22.5 ± 2.5 y, mean ± SD body mass index (in kg/m²): 22.7 ± 1.8] were analyzed in a single-blind, randomized, parallel design. MRI was used to acquire the distributions of fat and secretion in the stomach after ingestion of 2 emulsions: a stable emulsion (E1) or an unstable emulsion (E4) with 20% fat fraction and ∼0.3 mm droplet sizes. Layer, volume, and mixing variables were fitted to the data and compared between the 2 emulsions.

RESULTS

The intragastric mixing between fat and secretion was better with the E4 than the E1 [increase in content heterogeneity of 17.1% (95% CI: 12.3%, 21.9%)]. The E4 demonstrated a linear relation [slope 1.57 (95% CI: 0.86, 2.29)] between the degree of layering and mixing. In contrast, no such relation was detected for the E1. Accumulated secretion volume in the stomach was lower with the E4 [decrease in volume variable k_s of 2.3 (95% CI: -3.9, -0.7)] and correlated with the degree of layering (r = 0.62, P < 0.001).

CONCLUSIONS

In healthy adults, intragastric fat layering was influenced mainly by the degree of intragastric mixing, rather than the overall dominance of secretion. The E1 triggered a higher accumulation of gastric secretion, which in turn facilitated homogenization of intragastric content in comparison with its unstable counterpart. This trial was registered at clinicaltrials.gov as NCT02602158.

Multisite, multivendor validation of the accuracy and reproducibility of proton-density fat-fraction quantification at 1.5T and 3T using a fat-water phantom

PURPOSE

To evaluate the accuracy and reproducibility of quantitative chemical shift-encoded (CSE) MRI to quantify proton-density fat-fraction (PDFF) in a fat-water phantom across sites, vendors, field strengths, and protocols.

METHODS

Six sites (Philips, Siemens, and GE Healthcare) participated in this study. A phantom containing multiple vials with various oil/water suspensions (PDFF:0%-100%) was built, shipped to each site, and scanned at 1.5T and 3T using two CSE protocols per field strength. Confounder-corrected PDFF maps were reconstructed using a common algorithm. To assess accuracy, PDFF bias and linear regression with the known PDFF were calculated. To assess reproducibility, measurements were compared across sites, vendors, field strengths, and protocols using analysis of covariance (ANCOVA), Bland-Altman analysis, and the intraclass correlation coefficient (ICC).

RESULTS

PDFF measurements revealed an overall absolute bias (across sites, field strengths, and protocols) of 0.22% (95% confidence interval, 0.07%-0.38%) and R²  > 0.995 relative to the known PDFF at each site, field strength, and protocol, with a slope between 0.96 and 1.02 and an intercept between -0.56% and 1.13%. ANCOVA did not reveal effects of field strength (P = 0.36) or protocol (P = 0.19). There was a significant effect of vendor (F = 25.13, P = 1.07 × 10^-10 ) with a bias of -0.37% (Philips) and -1.22% (Siemens) relative to GE Healthcare. The overall ICC was 0.999.

CONCLUSION

CSE-based fat quantification is accurate and reproducible across sites, vendors, field strengths, and protocols. Magn Reson Med 77:1516-1524, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Fat-water MRI of a diet-induced obesity mouse model at 15.2T

Quantitative fat-water MRI (FWMRI) methods provide valuable information about the distribution, volume, and composition of adipose tissue (AT). Ultra high field FWMRI of animal models may have the potential to provide insights into the progression of obesity and its comorbidities. Here, we present quantitative FWMRI with all known confounder corrections on a 15.2T preclinical scanner for noninvasive in vivo monitoring of an established diet-induced obesity mouse model. Male C57BL/6J mice were placed on a low-fat (LFD) or a high-fat diet (HFD). Three-dimensional (3-D) multiple gradient echo MRI at 15.2T was performed at baseline, 4, 8, 12, and 16 weeks after diet onset. A 3-D fat-water separation algorithm and additional processing were used to generate proton-density fat fraction (PDFF), local magnetic field offset, and [Formula: see text] maps. We examined these parameters in perirenal AT ROIs from LFD and HFD mice. The data suggest that PDFF, local field offset, and [Formula: see text] have different time course behaviors between LFD and HFD mice over 16 weeks. This work suggests FWMRI at 15.2T may be a useful tool for longitudinal studies of adiposity due to the advantages of ultra high field although further investigation is needed to understand the observed time course behavior.

Correlations between quantitative fat-water magnetic resonance imaging and computed tomography in human subcutaneous white adipose tissue

Beyond estimation of depot volumes, quantitative analysis of adipose tissue properties could improve understanding of how adipose tissue correlates with metabolic risk factors. We investigated whether the fat signal fraction (FSF) derived from quantitative fat-water magnetic resonance imaging (MRI) scans at 3.0 T correlates to CT Hounsfield units (HU) of the same tissue. These measures were acquired in the subcutaneous white adipose tissue (WAT) at the umbilical level of 21 healthy adult subjects. A moderate correlation exists between MRI- and CT-derived WAT values for all subjects, [Formula: see text], [Formula: see text], with a slope of [Formula: see text], (95% CI [Formula: see text]), indicating that a decrease of 1 HU equals a mean increase of 0.38% FSF. We demonstrate that FSF estimates obtained using quantitative fat-water MRI techniques correlate with CT HU values in subcutaneous WAT, and therefore, MRI-based FSF could be used as an alternative to CT HU for assessing metabolic risk factors.

Total liver fat quantification using three-dimensional respiratory self-navigated MRI sequence

PURPOSE

MRI can produce quantitative liver fat fraction (FF) maps noninvasively, which can help to improve diagnoses of fatty liver diseases. However, most sequences acquire several two-dimensional (2D) slices during one or more breath-holds, which may be difficult for patients with limited breath-holding capacity. A whole-liver 3D FF map could also be obtained in a single acquisition by applying a reliable breathing-motion correction method. Several correction techniques are available for 3D imaging, but they use external devices, interrupt acquisition, or jeopardize the spatial resolution. To overcome these issues, a proof-of-concept study introducing a self-navigated 3D three-point Dixon sequence is presented here.

METHODS

A respiratory self-gating strategy acquiring a center k-space profile was integrated into a three-point Dixon sequence. We obtained 3D FF maps from a water-fat emulsions phantom and fifteen volunteers. This sequence was compared with multi-2D breath-hold and 3D free-breathing approaches.

RESULTS

Our 3D three-point Dixon self-navigated sequence could correct for respiratory-motion artifacts and provided more precise FF measurements than breath-hold multi-2D and 3D free-breathing techniques.

CONCLUSION

Our 3D respiratory self-gating fat quantification sequence could correct for respiratory motion artifacts and yield more-precise FF measurements. Magn Reson Med 76:1400-1409, 2016. © 2015 International Society for Magnetic Resonance in Medicine.

MRI-determined liver proton density fat fraction, with MRS validation: Comparison of regions of interest sampling methods in patients with type 2 diabetes

PURPOSE

To assess the agreement between published magnetic resonance imaging (MRI)-based regions of interest (ROI) sampling methods using liver mean proton density fat fraction (PDFF) as the reference standard.

MATERIALS AND METHODS

This retrospective, internal review board-approved study was conducted in 35 patients with type 2 diabetes. Liver PDFF was measured by magnetic resonance spectroscopy (MRS) using a stimulated-echo acquisition mode sequence and MRI using a multiecho spoiled gradient-recalled echo sequence at 3.0T. ROI sampling methods reported in the literature were reproduced and liver mean PDFF obtained by whole-liver segmentation was used as the reference standard. Intraclass correlation coefficients (ICCs), Bland-Altman analysis, repeated-measures analysis of variance (ANOVA), and paired t-tests were performed.

RESULTS

ICC between MRS and MRI-PDFF was 0.916. Bland-Altman analysis showed excellent intermethod agreement with a bias of -1.5 ± 2.8%. The repeated-measures ANOVA found no systematic variation of PDFF among the nine liver segments. The correlation between liver mean PDFF and ROI sampling methods was very good to excellent (0.873 to 0.975). Paired t-tests revealed significant differences (P < 0.05) with ROI sampling methods that exclusively or predominantly sampled the right lobe. Significant correlations with mean PDFF were found with sampling methods that included higher number of segments, total area equal or larger than 5 cm(2) , or sampled both lobes (P = 0.001, 0.023, and 0.002, respectively).

CONCLUSION

MRI-PDFF quantification methods should sample each liver segment in both lobes and include a total surface area equal or larger than 5 cm(2) to provide a close estimate of the liver mean PDFF.

Modeling of T2* decay in vertebral bone marrow fat quantification

Bone marrow fat fraction mapping using chemical shift encoding-based water-fat separation is becoming a useful tool in investigating the association between bone marrow adiposity and bone health and in assessing cancer treatment-induced bone marrow damage. Vertebral bone marrow is characterized by short T2* relaxation times, which are in general different for the water and fat components and can confound fat quantification. The purpose of the present study is to compare different approaches to T2* correction in chemical shift encoding-based water-fat imaging of vertebral bone marrow using single-voxel MRS as reference. Eight-echo gradient-echo imaging and single-voxel MRS measurements were made on the spine (L3-L5) of 25 healthy volunteers. Different approaches were evaluated for correction of T2* effects: (a) single-T2* correction, (b) dual-T2* correction, (c) T2' correction using the a priori-known T2 from the MRS at each vertebral body and (d) T2' correction using the a priori-known T2 equal to previously measured average values. Dual-T2* correction resulted in noisier imaging fat fraction maps than single-T2* correction or T2' correction using a priori-known T2. Linear regression analysis between imaging and MRS fat fraction showed a slope significantly different from 1 when using single-T2* correction (R(2) = 0.96) or dual-T2* correction (R(2) = 0.87). T2' correction using the a priori-known T2 resulted in a slope not significantly different from 1, an intercept significantly different from 0 (between 2.4% and 3%) and R(2) = 0.96. Therefore, a T2' correction using a priori-known T2 can remove the fat fraction bias induced by the difference in T2* between water and fat components without degrading noise performance in fat fraction mapping of vertebral bone marrow.

Whole-Body Muscle MRI in Patients with Hyperkalemic Periodic Paralysis Carrying the SCN4A Mutation T704M: Evidence for Chronic Progressive Myopathy with Selective Muscle Involvement

Background and Purpose

Hyperkalemic periodic paralysis (hyperKPP) is a muscle sodium-ion channelopathy characterized by recurrent paralytic attacks. A proportion of affected individuals develop fixed or chronic progressive weakness that results in significant disability. However, little is known about the pathology of hyperKPP-induced fixed weakness, including the pattern of muscle involvement. The aim of this study was to characterize the patterns of muscle involvement in hyperKPP by whole-body magnetic resonance imaging (MRI).

Methods

We performed whole-body muscle MRI in seven hyperKPP patients carrying the T704M mutation in the SCN4A skeletal sodium-channel gene. Muscle fat infiltration, suggestive of chronic progressive myopathy, was analyzed qualitatively using a grading system and was quantified by the two-point Dixon technique.

Results

Whole-body muscle MRI analysis revealed muscle atrophy and fatty infiltration in hyperKPP patients, especially in older individuals. Muscle involvement followed a selective pattern, primarily affecting the posterior compartment of the lower leg and anterior thigh muscles. The muscle fat fraction increased with patient age in the anterior thigh (r=0.669, p=0.009), in the deep posterior compartment of the lower leg (r=0.617, p=0.019), and in the superficial posterior compartment of the lower leg (r=0.777, p=0.001).

Conclusions

Our whole-body muscle MRI findings provide evidence for chronic progressive myopathy in hyperKPP patients. The reported data suggest that a selective pattern of muscle involvement-affecting the posterior compartment of the lower leg and the anterior thigh-is characteristic of chronic progressive myopathy in hyperKPP.

Predictive accuracy of single- and multi-slice MRI for the estimation of total visceral adipose tissue in overweight to severely obese patients

The quantification of visceral adipose tissue (VAT) is increasingly being considered for risk assessment and treatment monitoring in obese patients, but is generally time-consuming. The goals of this work were to semi-automatically segment and quantify VAT areas of MRI slices at previously proposed anatomical landmarks and to evaluate their predictive power for whole-abdominal VAT volumes on a relatively large number of patients. One-hundred and ninety-seven overweight to severely obese patients (65 males; body mass index, 33.3 ± 3.5 kg/m(2); 132 females; body mass index, 34.3 ± 3.2 kg/m(2)) underwent MRI examination. Total VAT volumes (VVAT-T ) of the abdominopelvic cavity were quantified by retrospective analysis of two-point Dixon MRI data (active-contour segmentation, visual correction and histogram analysis). VVAT-T was then compared with VAT areas determined on one or five slices defined at seven anatomical landmarks (lumbar intervertebral spaces, umbilicus and femoral heads) and corresponding conversion factors were determined. Statistical measures were the coefficients of variation and standard deviations σ1 and σ5 of the difference between predicted and measured VAT volumes (Bland-Altman analysis). VVAT-T was 6.0 ± 2.0 L (2.5-11.2 L) for males and 3.2 ± 1.4 L (0.9-7.7 L) for females. The analysis of five slices yielded a better agreement than the analysis of single slices, required only a little extra time (4 min versus 2 min) and was substantially faster than whole-abdominal assessment (24 min). Best agreements were found at intervertebral spaces L3-L4 for females (σ5/1 = 523/608 mL) and L2-L3 for males (σ5/1 = 613/706 mL). Five-slice VAT volume estimates at the level of lumbar disc L3-L4 for females and L2-L3 for males can be obtained within 4 min and were a reliable predictor for abdominopelvic VAT volume in overweight to severely adipose patients. One-slice estimates took only 2 min and were slightly less accurate. These findings may contribute to the implementation of analytical methods for fast and reliable (routine) estimation of VAT volumes in obese patients.

Sensitivity of chemical shift-encoded fat quantification to calibration of fat MR spectrum

PURPOSE

To evaluate the impact of different fat spectral models on proton density fat fraction quantification using chemical shift-encoded MRI (CSE-MRI).

METHODS

In a simulation study, spectral models of fat were compared pairwise. Comparison of magnitude fitting and mixed fitting was performed over a range of echo times and fat fractions. In vivo acquisitions from 41 patients were reconstructed using seven published spectral models of fat. T2-corrected stimulated echo acquisition mode MR spectroscopy was used as a reference.

RESULTS

The simulations demonstrated that imperfectly calibrated spectral models of fat result in biases that depend on echo times and fat fraction. Mixed fitting was more robust against this bias than magnitude fitting. Multipeak spectral models showed much smaller differences among themselves than from the single-peak spectral model. In vivo studies showed that all multipeak models agreed better (for mixed fitting, the slope ranged from 0.967 to 1.045 using linear regression) with the reference standard than the single-peak model (for mixed fitting, slope = 0.76).

CONCLUSION

It is essential to use a multipeak fat model for accurate quantification of fat with CSE-MRI. Furthermore, fat quantification techniques using multipeak fat models are comparable, and no specific choice of spectral model has been shown to be superior to the rest.

Quantification of liver fat with respiratory-gated quantitative chemical shift encoded MRI

PURPOSE

To evaluate free-breathing chemical shift-encoded (CSE) magnetic resonance imaging (MRI) for quantification of hepatic proton density fat-fraction (PDFF). A secondary purpose was to evaluate hepatic R2* values measured using free-breathing quantitative CSE-MRI.

MATERIALS AND METHODS

Fifty patients (mean age, 56 years) were prospectively recruited and underwent the following four acquisitions to measure PDFF and R2*; 1) conventional breath-hold CSE-MRI (BH-CSE); 2) respiratory-gated CSE-MRI using respiratory bellows (BL-CSE); 3) respiratory-gated CSE-MRI using navigator echoes (NV-CSE); and 4) single voxel MR spectroscopy (MRS) as the reference standard for PDFF. Image quality was evaluated by two radiologists. MRI-PDFF measured from the three CSE-MRI methods were compared with MRS-PDFF using linear regression. The PDFF and R2* values were compared using two one-sided t-test to evaluate statistical equivalence.

RESULTS

There was no significant difference in the image quality scores among the three CSE-MRI methods for either PDFF (P = 1.000) or R2* maps (P = 0.359-1.000). Correlation coefficients (95% confidence interval [CI]) for the PDFF comparisons were 0.98 (0.96-0.99) for BH-, 0.99 (0.97-0.99) for BL-, and 0.99 (0.98-0.99) for NV-CSE. The statistical equivalence test revealed that the mean difference in PDFF and R2* between any two of the three CSE-MRI methods was less than ±1 percentage point (pp) and ±5 s(-1) , respectively (P < 0.046).

CONCLUSION

Respiratory-gated CSE-MRI with respiratory bellows or navigator echo are feasible methods to quantify liver PDFF and R2* and are as valid as the standard breath-hold technique.

The need for T₂ correction on MRS-based vertebral bone marrow fat quantification: implications for bone marrow fat fraction age dependence

Vertebral bone marrow fat quantification using single-voxel MRS is confounded by overlapping water-fat peaks and the difference in T2 relaxation time between water and fat components. The purposes of the present study were: (i) to determine the proton density fat fraction (PDFF) of vertebral bone marrow using single-voxel multi-TE MRS, addressing these confounding effects; and (ii) to investigate the implications of these corrections with respect to the age dependence of the PDFF. Single-voxel MRS was performed in the L5 vertebral body of 86 subjects (54 women and 32 men). To reliably extract the water peak from the overlying fat peaks, the mean bone marrow fat spectrum was characterized based on the area of measurable fat peaks and an a priori knowledge of the chemical triglyceride structure. MRS measurements were performed at multiple TEs. The T2 -weighted fat fraction was calculated at each TE. In addition, a T2 correction was performed to obtain the PDFF and the T2 value of water (T2w ) was calculated. The implications of the T2 correction were investigated by studying the age dependence of the T2 -weighted fat fractions and the PDFF. Compared with the PDFF, all T2 -weighted fat fractions significantly overestimated the fat fraction. Compared with the age dependence of the PDFF, the age dependence of the T2 -weighted fat fraction showed an increased slope and intercept as TE increased for women and a strongly increased intercept as TE increased for men. For women, a negative association between the T2 value of bone marrow water and PDFF was found. Single-voxel MRS-based vertebral bone marrow fat quantification should be based on a multi-TE MRS measurement to minimize confounding effects on PDFF determination, and also to allow the simultaneous calculation of T2w , which might be considered as an additional parameter sensitive to the composition of the water compartment.

Reproducibility of MR-based liver fat quantification across field strength: Same-day comparison between 1.5T and 3T in obese subjects

PURPOSE

To examine the reproducibility of quantitative magnetic resonance (MR) methods to estimate hepatic proton density fat-fraction (PDFF) at different magnetic field strengths.

MATERIALS AND METHODS

This Health Insurance Portability and Accountability Act (HIPAA)-compliant study was approved by the Institutional Review Board. Following informed consent, 25 severely obese subjects (mean body mass index [BMI]: 45 ± 4, range: 38-53 kg/m(2) ) were scanned at 1.5T and 3T on the same day. Two confounder-corrected multiecho chemical shift-encoded gradient-echo-based imaging methods were acquired to estimate PDFF over the entire liver: 3D complex-based (MRI-C) and 2D magnitude-based (MRI-M) MRI. Single-voxel MR spectroscopy (MRS) was performed in the right liver lobe. Using linear regression, pairwise comparisons of estimated PDFF were made between methods (MRI-C, MRI-M, MRS) at each field strength and for each method across field strengths.

RESULTS

1.5T vs. 3T regression analyses for MRI-C, MRI-M, and MRS PDFF measurements yielded R(2) values of 0.99, 0.97, and 0.90, respectively. The best-fit line was near unity (slope(m) = 1, intercept(b) = 0), indicating excellent agreement for each case: MRI-C (m = 0.92 [0.87, 0.99], b = 1.4 [0.7, 1.8]); MRI-M (m = 1.0 [0.90, 1.08], b = -1.4 [-2.4, -0.5]); MRS (m = 0.98 [0.82, 1.15], b = 1.2 [-0.2, 3.0]). Comparing MRI-C and MRI-M yielded an R(2)  = 0.98 (m = 1.1 [1.02, 1.16], b = -1.8 [-2.8, -1.1]) at 1.5T, and R(2)  = 0.99 (m = 0.98 [0.93, 1.03], b = 1.2 [0.7, 1.7]) at 3T.

CONCLUSION

This study demonstrates that PDFF estimation is reproducible across field strengths and across two confounder-corrected MR-based methods.

Validation of bone marrow fat quantification in the presence of trabecular bone using MRI

BACKGROUND

To validate six-echo, chemical-shift based MRI with T2 * correction for the quantification of bone marrow fat content in the presence of trabecular bone.

METHODS

Ten bone phantoms were made using trabecular bone cores extracted from the distal femur and proximal tibia of 20 human cadaveric knees. Bone marrow was removed from the cores and the marrow spaces were filled with water-fat gelatin to mimic bone marrow of known fat fractions. A chemical-shift based water-fat separation method with T2 * correction was used to generate fat fraction maps. The proton density fat fractions (PDFF) between marrow regions with and without bone were compared with the reference standard of known fat fraction using the squared Pearson correlation coefficient and unpaired t-test.

RESULTS

Strong correlations were found between the known fat fraction and measured PDFF in marrow without trabecular bone (R(2) = 0.99; slope = 0.99, intercept = 0.94) as well as in marrow with trabecular bone (R(2) = 0.97; slope = 1.0, intercept = -3.58). Measured PDFF between regions with and without bone were not significantly different (P = 0.5). However, PDFF was systematically underestimated by -3.2% fat fraction in regions containing trabecular bone.

CONCLUSION

Our implementation of a six-echo chemical-shift based MRI pulse sequence with T2 * correction provided an accurate means of determining fat content in bone marrow in the presence of trabecular bone.

Quantification of the triglyceride fatty acid composition with 3.0 T MRI

The aim of this work was to validate a sequential method for quantifying the triglyceride fatty acid composition with 3.0 T MRI. The image acquisition was performed with a 3D spoiled gradient multiple echo sequence. A specific phase correction algorithm was implemented to correct the native phase images for wrap, zero- and first-order phase and rebuild the real part images. Then, using a model of a fat (1)H MR spectrum integrating nine components, the number of double bonds (ndb) and the number of methylene-interrupted double bonds (nmidb) were derived. The chain length (CL) was obtained from these parameters using heuristic approximation. Validations were performed on different vegetable oils whose theoretical fatty acid composition was used as reference and in five human subjects. In vivo measurements were made in the liver and in the subcutaneous and visceral adipose tissues. Linear regressions showed strong correlations between ndb and nmidb quantified with MRI and the theoretical values calculated using oil composition. Mean ndb/nmidb/CL were 1.80 ± 0.25/0.51 ± 0.21/17.43 ± 0.07, 2.72 ± 0.31/0.94 ± 0.16/17.47 ± 0.08 and 2.53 ± 0.21/0.84 ± 0.14/17.43 ± 0.07 in the liver, subcutaneous and visceral adipose tissues respectively. The results suggest that the triglyceride fatty acid composition can be assessed in human fatty liver and adipose tissues with a clinically relevant MRI method at 3.0 T.

Whole-body MRI-based fat quantification: a comparison to air displacement plethysmography

PURPOSE

To demonstrate the feasibility of an algorithm for MRI whole-body quantification of internal and subcutaneous fat and quantitative comparison of total adipose tissue to air displacement plethysmography (ADP).

MATERIALS AND METHODS

For comparison with ADP, whole-body MR data of 11 volunteers were obtained using a continuously moving table Dixon sequence. Resulting fat images were corrected for B1 related intensity inhomogeneities before fat segmentation.

RESULTS

The performed MR measurements of the whole body provided a direct comparison to ADP measurements. The segmentation of subcutaneous and internal fat in the abdomen worked reliably with an accuracy of 98%. Depending on the underlying model for fat quantification, the resultant MR fat masses represent an upper and a lower limit for the true fat masses. In comparison to ADP, the results were in good agreement with ρ ≥ 0.97, P < 0.0001.

CONCLUSION

Whole-body fat quantities derived noninvasively by using a continuously moving table Dixon acquisition were directly compared with ADP. The accuracy of the method and the high reproducibility of results indicate its potential for clinical applications.

Relaxation effects in MRI-based quantification of fat content and fatty acid composition

PURPOSE

To investigate various sources of bias in MRI-based quantification of fat fraction (FF) and fatty acid composition (FAC) using chemical shift-encoded techniques.

METHODS

Signals from various FFs and FACs and individual relaxation rates of all signal components were simulated. From these signals, FF and FAC parameters were estimated with and without correction for differences in individual relaxation rates. In addition, phantom experiments were conducted with various flip angles and number of echoes to validate the simulations.

RESULTS

As expected, T(1) weighting resulted in an overestimation of the FF, but had much smaller impact on the FAC parameters. Differences in T(2) values of the signal components resulted in overestimation of the FAC parameters in fat/water mixtures, whereas the estimation in pure oil was largely unaffected. This bias was corrected using a simplified signal model with different T(2) values of water and fat, where the accuracy of the modeled T(2) of water was critical. The results of the phantom experiment were in agreement with simulations.

CONCLUSION

T(1) weighting has only a minor effect on FAC quantification in both fat/water mixtures and pure oils. T(2) weighting is mainly a concern in fat/water mixtures but may be corrected using a simplified model.

Liver fat quantification using a multi-step adaptive fitting approach with multi-echo GRE imaging

PURPOSE

The purpose of this study was to develop a multi-step adaptive fitting approach for liver proton density fat fraction (PDFF) and R(2)* quantification, and to perform an initial validation on a broadly available hardware platform.

THEORY AND METHODS

The proposed method uses a multi-echo three-dimensional gradient echo acquisition, with initial guesses for the fat and water signal fractions based on a Dixon decomposition of two selected echoes. Based on magnitude signal equations with a multi-peak fat spectral model, a multi-step nonlinear fitting procedure is then performed to adaptively update the fat and water signal fractions and R(2)* values. The proposed method was validated using numeric phantoms as ground truth, followed by preliminary clinical validation of PDFF calculations against spectroscopy in 30 patients.

RESULTS

The results of the proposed method agreed well with the ground truth of numerical phantoms, and were relatively insensitive to changes in field strength, field homogeneity, monopolar/bipolar readout, signal to noise ratio, and echo time selections. The in vivo patient study showed excellent consistency between the PDFF values measured with the proposed approach compared with spectroscopy.

CONCLUSION

This multi-step adaptive fitting approach performed well in both simulated and initial clinical evaluation, and shows potential in the quantification of hepatic steatosis.

Quantitative proton MR techniques for measuring fat

Accurate, precise and reliable techniques for the quantification of body and organ fat distributions are important tools in physiology research. They are critically needed in studies of obesity and diseases involving excess fat accumulation. Proton MR methods address this need by providing an array of relaxometry-based (T1, T2) and chemical shift-based approaches. These techniques can generate informative visualizations of regional and whole-body fat distributions, yield measurements of fat volumes within specific body depots and quantify fat accumulation in abdominal organs and muscles. MR methods are commonly used to investigate the role of fat in nutrition and metabolism, to measure the efficacy of short- and long-term dietary and exercise interventions, to study the implications of fat in organ steatosis and muscular dystrophies and to elucidate pathophysiological mechanisms in the context of obesity and its comorbidities. The purpose of this review is to provide a summary of mainstream MR strategies for fat quantification. The article succinctly describes the principles that differentiate water and fat proton signals, summarizes the advantages and limitations of various techniques and offers a few illustrative examples. The article also highlights recent efforts in the MR of brown adipose tissue and concludes by briefly discussing some future research directions.

On the confounding effect of temperature on chemical shift-encoded fat quantification

PURPOSE

To characterize the confounding effect of temperature on chemical shift-encoded (CSE) fat quantification.

METHODS

The proton resonance frequency of water, unlike triglycerides, depends on temperature. This leads to a temperature dependence of the spectral models of fat (relative to water) that are commonly used by CSE-MRI methods. Simulation analysis was performed for 1.5 Tesla CSE fat-water signals at various temperatures and echo time combinations. Oil-water phantoms were constructed and scanned at temperatures between 0 and 40°C using spectroscopy and CSE imaging at three echo time combinations. An explanted human liver, rejected for transplantation due to steatosis, was scanned using spectroscopy and CSE imaging. Fat-water reconstructions were performed using four different techniques: magnitude and complex fitting, with standard or temperature-corrected signal modeling.

RESULTS

In all experiments, magnitude fitting with standard signal modeling resulted in large fat quantification errors. Errors were largest for echo time combinations near TEinit ≈ 1.3 ms, ΔTE ≈ 2.2 ms. Errors in fat quantification caused by temperature-related frequency shifts were smaller with complex fitting, and were avoided using a temperature-corrected signal model.

CONCLUSION

Temperature is a confounding factor for fat quantification. If not accounted for, it can result in large errors in fat quantifications in phantom and ex vivo acquisitions.

Quantitative assessment of fat infiltration in the rotator cuff muscles using water-fat MRI

PURPOSE

To evaluate a chemical shift-based fat quantification technique in the rotator cuff muscles in comparison with the semiquantitative Goutallier fat infiltration classification (GC) and to assess their relationship with clinical parameters.

MATERIALS AND METHODS

The shoulders of 57 patients were imaged using a 3T MR scanner. The rotator cuff muscles were assessed for fat infiltration using GC by two radiologists and an orthopedic surgeon. Sequences included oblique-sagittal T1-, T2-, and proton density-weighted fast spin echo, and six-echo gradient echo. The iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) was used to measure fat fraction. Pain and range of motion of the shoulder were recorded.

RESULTS

Fat fraction values were significantly correlated with GC grades (P < 0.0001, κ >0.9) showing consistent increase with GC grades (grade = 0, 0%-5.59%; grade = 1, 1.1%-9.70%; grade = 2, 6.44%-14.86%; grade = 3, 15.25%-17.77%; grade = 4, 19.85%-29.63%). A significant correlation between fat infiltration of the subscapularis muscle quantified with IDEAL versus 1) deficit in internal rotation (Spearman Rank Correlation Coefficient [SRC] = 0.39, 95% confidence interval [CI] 0.13-0.60, P < 0.01) and 2) pain (SRC coefficient = 0.313, 95% CI 0.049-0.536, P = 0.02) was found but was not seen between the clinical parameters and GC grades. Additionally, only quantitative fat infiltration measures of the supraspinatus muscle were significantly correlated with a deficit in abduction (SRC coefficient = 0.45, 95% CI 0.20-0.60, P < 0.01).

CONCLUSION

An accurate and highly reproducible fat quantification in the rotator cuff muscles using water-fat magnetic resonance imaging (MRI) techniques is possible and significantly correlates with shoulder pain and range of motion.

MR fat fraction mapping: a simple biomarker for liver steatosis quantification in nonalcoholic fatty liver disease patients

RATIONALE AND OBJECTIVES

To assess the performance, postprocessing time, and intra- and interobserver agreement of a simple magnetic resonance-based mapping technique to quantify liver fat.

MATERIALS AND METHODS

This prospective, single-center study included 26 patients who were overweight with type 2 diabetes and at risk for nonalcoholic fatty liver disease. Mapping of the liver was based on a triple echo gradient-echo sequence, and (1)H magnetic resonance spectroscopy was used as the reference standard. The nonparametric Spearman correlation coefficient and the Wilcoxon test were used for comparisons between mapping and spectroscopy. The mapping was assessed for its predictive performance using the area under the curve of a receiver operating characteristic curve. Intraclass correlation coefficients were used to calculate intra- and interobserver's agreement for mapping measurements.

RESULTS

Patients had a mean fat percentage of 11.7% (range, 2-35.4%). A strong correlation was seen between mapping and spectroscopy (r = 0.89, P < .0001). A cutoff of 6.9% for fat fraction mapping was found to diagnose steatosis with 93% sensitivity and 100% specificity with an area under the curve of 0.99. Mapping of the liver had shorter acquisition and post-processing times than spectroscopy (5 min vs. 38 min; P < .0001). Mapping measurements had an intra- and interobserver agreement of 0.98 and 0.99, respectively.

CONCLUSIONS

The magnetic resonance-based liver mapping can accurately quantify liver fat with a cutoff value of 6.9% and excellent intra- and interobserver agreement. This mapping technique, with its simple methodology and short postprocessing time, has the potential to be included in routine abdominal protocols.

Effect of echo-sampling strategy on the accuracy of out-of-phase and in-phase multiecho gradient-echo MRI hepatic fat fraction estimation

PURPOSE

To assess the effect of echo-sampling strategy on the accuracy of out-of-phase (OP) and in-phase (IP) multiecho gradient-echo magnetic resonance imaging (MRI) hepatic fat fraction (FF) estimation, using MR spectroscopy (MRS) proton density FF (PDFF) as a reference standard.

MATERIALS AND METHODS

In this Institutional Review Board (IRB)-approved, Health Insurance Portability and Accountability Act (HIPAA)-compliant prospective study, 84 subjects underwent proton MRS and non-T1 -weighted gradient-echo imaging of the liver at 3T. Imaging data were collected at 16 nominally OP and IP echo times (TEs). MRI-FF was estimated while varying two echo-sampling parameters (number of consecutive echoes, starting echo number). For each combination of these parameters, MRI-FF estimation accuracy was assessed with slope, intercept, average bias, and R2 from a linear regression of MRS-PDFF on MRI-FF. The relationship between accuracy metrics and echo-sampling parameters was assessed by Spearman rank correlation.

RESULTS

For FF calculations using 3-16 echoes and a starting echo number of 1, the intercept ranged from 0.0046 to 0.0124, slope from 0.941 to 0.96, average bias from 0.0034 to 0.0078, and R2 from 0.968 to 0.976. All four accuracy metrics were the best with the 3- and 4-echo calculations and worsened progressively with an increasing number of echoes. For a given number of echoes, there was an overall trend toward decreasing accuracy as starting echo number increased. Spearman correlation coefficients between starting echo number and intercept, slope, average bias, and R2 were 0.911, -0.64, -0.889, and -0.954, respectively, indicating progressive loss of accuracy in each case.

CONCLUSION

Multiecho OP and IP imaging provided high FF estimation accuracy. Accuracy was highest using the earliest 3 or 4 echoes. Incorporation of additional echoes or delaying the starting echo number progressively reduced accuracy.