Joint estimation of water/fat images and field inhomogeneity map

Fatty acid composition MRI of epicardial adipose tissue: Methods and detection of proinflammatory biomarkers in ST-segment elevation myocardial infarction patients

PURPOSE

To develop a method for quantifying the fatty acid composition (FAC) of human epicardial adipose tissue (EAT) using accelerated MRI and identify its potential for detecting proinflammatory biomarkers in patients with ST-segment elevation myocardial infarction (STEMI).

METHODS

A multi-echo radial gradient-echo sequence was developed for accelerated imaging during a breath hold using a locally low-rank denoising technique to reconstruct undersampled images. FAC mapping was achieved by fitting the multi-echo images to a multi-resonance complex signal model based on triglyceride characterization. Validation of the method was assessed using a phantom comprised of multiple oils. In vivo imaging was performed in STEMI patients (n = 21; 14 males/seven females). FAC was quantified in EAT, subcutaneous AT, and abdominal visceral AT.

RESULTS

Phantom validation demonstrated strong correlations (r > 0.97) and statistical significance (p < 0.0001) between measured and reference proton density fat fraction and FAC values. In vivo imaging of STEMI patients revealed a distinct EAT FAC profile compared to subcutaneous AT and abdominal visceral AT. EAT FAC parameters had significant correlations with left ventricular (LV) end-diastolic volume index (p < 0.05), LV end-systolic volume index (p < 0.05), and LV mass index (p < 0.05).

CONCLUSIONS

Accelerated MRI enabled accurate quantification of human EAT FAC. The relationships between the EAT FAC profile and LV structure and function in STEMI patients suggest the potential of EAT FAC MRI as a biomarker for adipose tissue quality and inflammatory status in cardiovascular disease.

Application and research progress of magnetic resonance proton density fat fraction in metabolic dysfunction-associated steatotic liver disease: a comprehensive review

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD), formerly known as Non-Alcoholic Fatty Liver Disease (NAFLD), is a chronic liver disorder associated with disturbances in lipid metabolism. The disease is prevalent worldwide, particularly closely linked with metabolic syndromes such as obesity and diabetes. Magnetic Resonance Proton Density Fat Fraction (MRI-PDFF), serving as a non-invasive and highly quantitative imaging assessment tool, holds promising applications in the diagnosis and research of MASLD. This paper aims to comprehensively review and summarize the applications and research progress of MRI-PDFF technology in MASLD, analyze its strengths and challenges, and anticipate its future developments in clinical practice.

The effect of fat model variation on muscle fat fraction quantification in a cross-sectional cohort

Spectroscopic imaging, rooted in Dixon's two-echo spin sequence to distinguish water and fat, has evolved significantly in acquisition and processing. Yet precise fat quantification remains a persistent challenge in ongoing research. With adequate phase characterization and correction, the fat composition models will impact measurements of fatty tissue. However, the effect of the used fat model in low-fat regions such as healthy muscle is unknown. In this study, we investigate the effect of assumed fat composition, in terms of chain length and double bond count, on fat fraction quantification in healthy muscle, while addressing phase and relaxometry confounders. For this purpose, we acquired bilateral thigh datasets from 38 healthy volunteers. Fat fractions were estimated using the IDEAL algorithm employing three different fat models fitted with and without the initial phase constrained. After data processing and model fitting, we used a convolutional neural net to automatically segment all thigh muscles and subcutaneous fat to evaluate the fitted parameters. The fat composition was compared with those reported in the literature. Overall, all the observed estimated fat composition values fall within the range of previously reported fatty acid composition based on gas chromatography measurements. All methods and models revealed different estimates of the muscle fat fractions in various evaluated muscle groups. Lateral differences changed from 0.5% to 5.3% in the hamstring muscle groups depending on the chosen method. The lowest observed left-right differences in each muscle group were all for the fat model estimating the number of double bonds with the initial phase unconstrained. With this model, the left-right differences were 0.64% ± 0.31%, 0.50% ± 0.27%, and 0.50% ± 0.40% for the quadriceps, hamstrings, and adductors muscle groups, respectively. Our findings suggest that a fat model estimating double bond numbers while allowing separate phases for each chemical species, given some assumptions, yields the best fat fraction estimate for our dataset.

Use of two-point and six-point Dixon MRI for fat fraction analysis in the lumbar vertebral bodies and paraspinal muscles in healthy dogs: comparison with magnetic resonance spectroscopy

Introduction

Fatty degeneration of the vertebral bodies and paravertebral muscles is associated with the presence, severity, and prognosis of spinal disease such as intervertebral disc degeneration. Therefore, the fat fraction (FF) of the vertebral bodies and paraspinal muscles has been considered a potential biomarker for assessing the pathophysiology, progression, and treatment response of spinal disease. Magnetic resonance spectroscopy (MRS) is considered the reference standard for fat quantification; however, it has limitations of a long acquisition time and is technically demanding. Chemical shift-encoding water-fat imaging, called the Dixon method, has recently been applied for rapid fat quantification with high spatial resolution. However, the Dixon method has not been validated in veterinary medicine, and we hypothesized that the Dixon method would provide a comparable assessment of the FF to MRS but would be faster and easier to implement in dogs.

Methods

In this prospective study, we assessed the FF of the lumbar vertebral bodies and paravertebral muscles from the first to sixth lumbar vertebrae using MRS, the two-point Dixon method (LAVA-FLEX), and the six-point Dixon method (IDEAL-IQ) and compared these techniques.

Results and discussion

The FFs of vertebral bodies and paravertebral muscles derived from LAVA-FLEX and IDEAL-IQ showed significant correlations and agreement with those obtained with MRS. In particular, the FFs obtained with IDEAL-IQ showed higher correlations and better agreement with those obtained with MRS than those derived by LAVA-FLEX. Both Dixon methods showed excellent intra- and interobserver reproducibility for FF analysis of the vertebral bodies and paraspinal muscles. However, the test-retest repeatability of vertebral body and paraspinal muscle FF analysis was low for all three sequences, especially for the paraspinal muscles. The results of this study showed that LAVA-FLEX and IDEAL-IQ have high reproducibility and that their findings were highly correlated with the FFs of the lumber vertebral bodies and paraspinal muscles determined by MRS in dogs. The FF analysis could be performed much more easily and quickly using LAVA-FLEX and IDEAL-IQ than using MRS. In conclusion, LAVA-FLEX and IDEAL-IQ can be used as routine procedures in spinal magnetic resonance imaging in dogs for FF analysis of the vertebral bodies and paraspinal muscles.

Rationale and design of the multi organ inflammation with serial testing study: a comprehensive assessment of functional and structural abnormalities in patients with recovered COVID-19

Introduction

Short-term clinical outcomes from SARS-CoV-2 infection are generally favorable. However, 15-20% of patients report persistent symptoms of at least 12 weeks duration, often referred to as long COVID. Population studies have also demonstrated an increased risk of incident diabetes and cardiovascular disease at 12 months following infection. While imaging studies have identified multi-organ injury patterns in patients with recovered COVID-19, their respective contributions to the disability and morbidity of long COVID is unclear.

Methods

A multicenter, observational study of 215 vaccine-naïve patients with clinically recovered COVID-19, studied at 3-6 months following infection, and 133 healthy volunteers without prior SARS-CoV-2 infection. Patients with recovered COVID-19 were screened for long COVID related symptoms and their impact on daily living. Multi-organ, multi-parametric magnetic resonance imaging (MRI) and circulating biomarkers were acquired to document sub-clinical organ pathology. All participants underwent pulmonary function, aerobic endurance (6 min walk test), cognition testing and olfaction assessment. Clinical outcomes were collected up to 1 year from infection. The primary objective of this study is to identify associations between organ injury and disability in patients with long-COVID symptoms in comparison to controls. As a secondary objective, imaging and circulating biomarkers with the potential to exacerbate cardiovascular health were characterized.

Discussion

Long-term sequelae of COVID-19 are common and can result in significant disability and cardiometabolic disease. The overall goal of this project is to identify novel targets for the treatment of long COVID including mitigating the risk of incident cardiovascular disease.

Study registration

clinicaltrials.gov (MOIST late cross-sectional study; NCT04525404).

Metabolic-associated fatty liver voxel-based quantification on CT images using a contrast adapted automatic tool

BACKGROUND & AIMS

Metabolic-dysfunction associated fatty liver disease (MAFLD) is highly prevalent and can lead to liver complications and comorbidities, with non-invasive tests such as vibration-controlled transient elastography (VCTE) and invasive liver biopsies being used for diagnosis The aim of the present study was to develop a new fully automatized method for quantifying the percentage of fat in the liver based on a voxel analysis on computed tomography (CT) images to solve previously unconcluded diagnostic deficiencies either in contrast (CE) or non-contrast enhanced (NCE) assessments.

METHODS

Liver and spleen were segmented using nn-UNet on CE- and NCE-CT images. Radiodensity values were obtained for both organs for defining the key benchmarks for fatty liver assessment: liver mean, liver-to-spleen ratio, liver-spleen difference, and their average. VCTE was used for validation. A classification task method was developed for detection of suitable patients to fulfill maximum reproducibility across cohorts and highlight subjects with other potential radiodensity-related diseases.

RESULTS

Best accuracy was attained using the average of all proposed benchmarks being the liver-to-spleen ratio highly useful for CE and the liver-to-spleen difference for NCE. The proposed whole-organ automatic segmentation displayed superior potential when compared to the typically used manual region-of-interest drawing as it allows to accurately obtain the percent of fat in liver, among other improvements. Atypical patients were successfully stratified through a function based on biochemical data.

CONCLUSIONS

The developed method tackles the current drawbacks including biopsy invasiveness, and CT-related weaknesses such as lack of automaticity, dependency on contrast agent, no quantification of the percentage of fat in liver, and limited information on region-to-organ affectation. We propose this tool as an alternative for individualized MAFLD evaluation by an early detection of abnormal CT patterns based in radiodensity whilst abording detection of non-suitable patients to avoid unnecessary exposure to CT radiation. Furthermore, this work presents a surrogate aid for assessing fatty liver at a primary assessment of MAFLD using elastography data.

Liver steatosis in patients with transfusion-dependent thalassaemia

We evaluated the prevalence and the clinical associations of liver steatosis (LS) in patients with transfusion-dependent thalassaemia (TDT). We considered 301 TDT patients (177 females, median age = 40.61 years) enrolled in the Extension-Myocardial Iron Overload in Thalassaemia Network, and 25 healthy subjects. Magnetic resonance imaging was used to quantify iron overload and hepatic fat fraction (FF) by T2* technique and cardiac function by cine images. The glucose metabolism was assessed by the oral glucose tolerance test (OGTT). Hepatic FF was significantly higher in TDT patients than in healthy subjects (median value: 1.48% vs. 0.55%; p = 0.013). In TDT, hepatic FF was not associated with age, gender, serum ferritin levels or liver function parameters, but showed a weak inverse correlation with high-density lipoprotein cholesterol. The 36.4% of TDT patients showed LS (FF >3.7%). Active hepatitis C virus (HCV) infection, increased body mass index and hepatic iron were independent determinants of LS. A hepatic FF >3.53% predicted the presence of an abnormal OGTT. Hepatic FF was not correlated with cardiac iron, biventricular volumes or ejection fractions, but was correlated with left ventricular mass index. In TDT, LS is a frequent finding, associated with iron overload, increased weight and HCV, and conveying an increased risk for the alterations of glucose metabolism.

Comparison of Vendor-Independent Software Tools for Liver Proton Density Fat Fraction Estimation at 1.5 T

(1) Background: Open-source software tools are available to estimate proton density fat fraction (PDFF). (2) Methods: We compared four algorithms: complex-based with graph cut (GC), magnitude-based (MAG), magnitude-only estimation with Rician noise modeling (MAG-R), and multi-scale quadratic pseudo-Boolean optimization with graph cut (QPBO). The accuracy and reliability of the methods were evaluated in phantoms with known fat/water ratios and a patient cohort with various grades (S0-S3) of steatosis. Image acquisitions were performed at 1.5 Tesla (T). (3) Results: The PDFF estimates showed a nearly perfect correlation (Pearson r = 0.999, p < 0.001) and inter-rater agreement (ICC = from 0.995 to 0.999, p < 0.001) with true fat fractions. The absolute bias was low with all methods (0.001-1%), and an ANCOVA detected no significant difference between the algorithms in vitro. The agreement across the methods was very good in the patient cohort (ICC = 0.891, p < 0.001). However, MAG estimates (-2.30% ± 6.11%, p = 0.005) were lower than MAG-R. The field inhomogeneity artifacts were most frequent in MAG-R (70%) and GC (39%) and absent in QPBO images. (4) Conclusions: The tested algorithms all accurately estimate PDFF in vitro. Meanwhile, QPBO is the least affected by field inhomogeneity artifacts in vivo.

Accelerated four-dimensional free-breathing whole-liver water-fat magnetic resonance imaging with deep dictionary learning and chemical shift modeling

Background

Multi-echo chemical-shift-encoded magnetic resonance imaging (MRI) has been widely used for fat quantification and fat suppression in clinical liver examinations. Clinical liver water-fat imaging typically requires breath-hold acquisitions, with the free-breathing acquisition method being more desirable for patient comfort. However, the acquisition for free-breathing imaging could take up to several minutes. The purpose of this study is to accelerate four-dimensional free-breathing whole-liver water-fat MRI by jointly using high-dimensional deep dictionary learning and model-guided (MG) reconstruction.

Methods

A high-dimensional model-guided deep dictionary learning (HMDDL) algorithm is proposed for the acceleration. The HMDDL combines the powers of the high-dimensional dictionary learning neural network (hdDLNN) and the chemical shift model. The neural network utilizes the prior information of the dynamic multi-echo data in spatial respiratory motion, and echo dimensions to exploit the features of images. The chemical shift model is used to guide the reconstruction of field maps, R 2 ∗ maps, water images, and fat images. Data acquired from ten healthy subjects and ten subjects with clinically diagnosed nonalcoholic fatty liver disease (NAFLD) were selected for training. Data acquired from one healthy subject and two NAFLD subjects were selected for validation. Data acquired from five healthy subjects and five NAFLD subjects were selected for testing. A three-dimensional (3D) blipped golden-angle stack-of-stars multi-gradient-echo pulse sequence was designed to accelerate the data acquisition. The retrospectively undersampled data were used for training, and the prospectively undersampled data were used for testing. The performance of the HMDDL was evaluated in comparison with the compressed sensing-based water-fat separation (CS-WF) algorithm and a parallel non-Cartesian recurrent neural network (PNCRNN) algorithm.

Results

Four-dimensional water-fat images with ten motion states for whole-liver are demonstrated at several R values. In comparison with the CS-WF and PNCRNN, the HMDDL improved the mean peak signal-to-noise ratio (PSNR) of images by 9.93 and 2.20 dB, respectively, and improved the mean structure similarity (SSIM) of images by 0.058 and 0.009, respectively, at R=10. The paired t-test shows that there was no significant difference between HMDDL and ground truth for proton-density fat fraction (PDFF) and R 2 ∗ values at R up to 10.

Conclusions

The proposed HMDDL enables features of water images and fat images from the highly undersampled multi-echo data along spatial, respiratory motion, and echo dimensions, to improve the performance of accelerated four-dimensional (4D) free-breathing water-fat imaging.

Method for cycle detection in sparse, irregularly sampled, long-term neuro-behavioral timeseries: Basis pursuit denoising with polynomial detrending of long-term, inter-ictal epileptiform activity

Numerous physiological processes are cyclical, but sampling these processes densely enough to perform frequency decomposition and subsequent analyses can be challenging. Mathematical approaches for decomposition and reconstruction of sparsely and irregularly sampled signals are well established but have been under-utilized in physiological applications. We developed a basis pursuit denoising with polynomial detrending (BPWP) model that recovers oscillations and trends from sparse and irregularly sampled timeseries. We validated this model on a unique dataset of long-term inter-ictal epileptiform discharge (IED) rates from human hippocampus recorded with a novel investigational device with continuous local field potential sensing. IED rates have well established circadian and multiday cycles related to sleep, wakefulness, and seizure clusters. Given sparse and irregular samples of IED rates from multi-month intracranial EEG recordings from ambulatory humans, we used BPWP to compute narrowband spectral power and polynomial trend coefficients and identify IED rate cycles in three subjects. In select cases, we propose that random and irregular sampling may be leveraged for frequency decomposition of physiological signals. Trial Registration: NCT03946618.

Bi-component dictionary matching for MR fingerprinting for efficient quantification of fat fraction and water T1 in skeletal muscle

PURPOSE

To propose an efficient bi-component MR fingerprinting (MRF) fitting method using a Variable Projection (VARPRO) strategy, applied to the quantification of fat fraction (FF) and water T1 (T 1 H 2 0 $$ \mathrm{T}{1}_{{\mathrm{H}}_20} $$ ) in skeletal muscle tissues.

METHODS

The MRF signals were analyzed in a two-step process by comparing them to the elements of separate water and fat dictionaries (bi-component dictionary matching). First, each pair of water and fat dictionary elements was fitted to the acquired signal to determine an optimal FF that was used to merge the fingerprints in a combined water/fat dictionary. Second, standard dictionary matching was applied to the combined dictionary for determining the remaining parameters. A clustering method was implemented to further accelerate the fitting. Accuracy, precision, and matching time of this approach were evaluated on both numerical and in vivo datasets, and compared to the reference dictionary-matching approach that includes FF as a dictionary parameter.

RESULTS

In numerical phantoms, all MRF parameters showed high correlation with ground truth for the reference and the bi-component method (R2  > 0.98). In vivo, the estimated parameters from the proposed method were highly correlated with those from the reference approach (R2  > 0.997). The bi-component method achieved an acceleration factor of up to 360 compared to the reference dictionary matching.

CONCLUSION

The proposed bi-component fitting approach enables a significant acceleration of the reconstruction of MRF parameter maps for fat-water imaging, while maintaining comparable precision and accuracy to the reference on FF andT 1 H 2 0 $$ \mathrm{T}{1}_{{\mathrm{H}}_20} $$ estimation.

SPARCQ: A new approach for fat fraction mapping using asymmetries in the phase-cycled balanced SSFP signal profile

PURPOSE

To develop SPARCQ (Signal Profile Asymmetries for Rapid Compartment Quantification), a novel approach to quantify fat fraction (FF) using asymmetries in the phase-cycled balanced SSFP (bSSFP) profile.

METHODS

SPARCQ uses phase-cycling to obtain bSSFP frequency profiles, which display asymmetries in the presence of fat and water at certain TRs. For each voxel, the measured signal profile is decomposed into a weighted sum of simulated profiles via multi-compartment dictionary matching. Each dictionary entry represents a single-compartment bSSFP profile with a specific off-resonance frequency and relaxation time ratio. Using the results of dictionary matching, the fractions of the different off-resonance components are extracted for each voxel, generating quantitative maps of water and FF and banding-artifact-free images for the entire image volume. SPARCQ was validated using simulations, experiments in a water-fat phantom and in knees of healthy volunteers. Experimental results were compared with reference proton density FFs obtained with 1 H-MRS (phantoms) and with multiecho gradient-echo MRI (phantoms and volunteers). SPARCQ repeatability was evaluated in six scan-rescan experiments.

RESULTS

Simulations showed that FF quantification is accurate and robust for SNRs greater than 20. Phantom experiments demonstrated good agreement between SPARCQ and gold standard FFs. In volunteers, banding-artifact-free quantitative maps and water-fat-separated images obtained with SPARCQ and ME-GRE demonstrated the expected contrast between fatty and non-fatty tissues. The coefficient of repeatability of SPARCQ FF was 0.0512.

CONCLUSION

SPARCQ demonstrates potential for fat quantification using asymmetries in bSSFP profiles and may be a promising alternative to conventional FF quantification techniques.

Reducing the ambiguity of field inhomogeneity and chemical shift effect for fat-water separation by field factor

PURPOSE

To reduce the ambiguity between chemical shift and field inhomogeneity with flexible TE combinations by introducing a variable (field factor).

THEORY AND METHODS

The ambiguity between chemical shift and field inhomogeneity can be eliminated directly from the multiple in-phase images acquired at different TEs; however, it is only applicable to few echo combinations. In this study, we accommodated such an implementation in flexible TE combinations by introducing a new variable (field factor). The effects of the chemical shift were removed from the field inhomogeneity in the candidate solutions, thus reducing the ambiguity problem. To validate this concept, multi-echo MRI data acquired from various anatomies with different imaging parameters were tested. The derived fat and water images were compared with those of the state-of-the-art fat-water separation algorithms.

RESULTS

Robust fat-water separation was achieved with the accurate solution of field inhomogeneity, and no apparent fat-water swap was observed. In addition to the good performance, the proposed method is applicable to various fat-water separation applications, including different sequence types and flexible TE choices.

CONCLUSION

We propose an algorithm to reduce the ambiguity of chemical shift and field inhomogeneity and achieved robust fat-water separation in various applications.

Feasibility of joint mapping of triglyceride saturation and water longitudinal relaxation in a single breath hold applied to high fat-fraction adipose depots in the periclavicular anatomy

INTRODUCTION

Simultaneous mapping of triglyceride (TAG) saturation and tissue water relaxation may improve the characterization of the structure and function of anatomies with significant adipose tissue. While several groups have demonstrated in vivo TAG saturation imaging using MRI, joint mapping of relaxation and TAG saturation is understudied. Such mappings may avoid bias from physiological motion, if they can be done within a single breath-hold, and also account for static and applied magnetic field heterogeneity.

METHODS

We propose a transient-state/MR fingerprinting single breath-hold sequence at 3 T, a low-rank reconstruction, and a parameter estimation pipeline that jointly estimates the number of double bonds (NDB), number of methylene interrupted double bonds (NMIDB), and tissue water T1, while accounting for non-ideal radiofrequency transmit scaling and off-resonance effects. We test the proposed method in simulations, in phantom against MR spectroscopy (MRS), and in vivo regions in and around high fat fraction (FF) periclavicular adipose tissue. Partial volume and multi-peak transverse relaxation effects are explored.

RESULTS

The simulation results demonstrate accurate NDB, NMIDB, and water T1 estimates across a range of NDB, NMIDB, and T1 values. In phantoms, the proposed method's estimates of NDB and NMIDB correlate with those from MR spectroscopy (Pearson correlation ≥0.98), while the water T1 estimates are concordant with a standard phantom. The NDB and NMIDB are sensitive to partial volumes of water, showing increasing bias at FF < 40%. This bias is found to be due to noise and transverse relaxation effects. The in vivo periclavicular adipose tissue has high FF (>90%). The adipose tissue NDB and NMIDB, and muscle T1 estimates are comparable to those reported in the literature.

CONCLUSION

Robust estimation of NDB, NMIDB at high FF and water T1 across a broad range of FFs are feasible using the proposed methods. Further reduction of noise and model bias are needed to employ the proposed technique in low FF anatomies and pathologies.

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.

Off-resonance artifact correction for MRI: A review

In magnetic resonance imaging (MRI), inhomogeneity in the main magnetic field used for imaging, referred to as off-resonance, can lead to image artifacts ranging from mild to severe depending on the application. Off-resonance artifacts, such as signal loss, geometric distortions, and blurring, can compromise the clinical and scientific utility of MR images. In this review, we describe sources of off-resonance in MRI, how off-resonance affects images, and strategies to prevent and correct for off-resonance. Given recent advances and the great potential of low-field and/or portable MRI, we also highlight the advantages and challenges of imaging at low field with respect to off-resonance.

Estimation of field inhomogeneity map following magnitude-based ambiguity-resolved water-fat separation

Magnitude-based PDFF (Proton Density Fat Fraction) and R2∗ mapping with resolved water-fat ambiguity is extended to calculate field inhomogeneity (field map) using the phase images. The estimation is formulated in matrix form, resolving the field map in a least-squares sense. PDFF and R2∗ from magnitude fitting may be updated using the estimated field maps. The limits of quantification of our voxel-independent implementation were assessed. Bland-Altman was used to compare PDFF and field maps from our method against a reference complex-based method on 152 UK Biobank subjects (1.5 T Siemens). A separate acquisition (3 T Siemens) presenting field inhomogeneities was also used. The proposed field mapping was accurate beyond double the complex-based limit range. High agreement was obtained between the proposed method and the reference in UK. Robust field mapping was observed at 3 T, for inhomogeneities over 400 Hz including rapid variation across edges. Field mapping following unambiguous magnitude-based water-fat separation was demonstrated in-vivo and showed potential at 3 T.

On the water-fat in-phase assumption for quantitative susceptibility mapping

PURPOSE

To (a) define multi-peak fat model-based effective in-phase echo times for quantitative susceptibility mapping (QSM) in water-fat regions, (b) analyze the relationship between fat fraction, field map quantification bias and susceptibility bias, and (c) evaluate the susceptibility mapping performance of the proposed effective in-phase echoes in comparison to single-peak in-phase echoes and water-fat separation for regions where both water and fat are present.

METHODS

Effective multipeak in-phase echo times for a bone marrow and a liver fat spectral model were derived from a single voxel simulation. A Monte Carlo simulation was performed to assess the field map estimation error as a function of fat fraction for the different in-phase echoes. Additionally, a phantom scan and in vivo scans in the liver, spine, and breast were performed and evaluated with respect to quantification accuracy.

RESULTS

The use of single-peak in-phase echoes can introduce a worst-case susceptibility bias of 0.43 $$ 0.43 $$  ppm. The use of effective multipeak in-phase echoes shows a similar quantitative performance in the numerical simulation, the phantom and in all in vivo anatomies when compared to water-fat separation-based QSM.

CONCLUSION

QSM based on the proposed effective multipeak in-phase echoes can alleviate the quantification bias present in QSM based on single-peak in-phase echoes. When compared to water-fat separation-based QSM the proposed effective in-phase echo times achieve a similar quantitative performance while drastically reducing the computational expense for field map estimation.

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.

Deep Learning-Based Water-Fat Separation from Dual-Echo Chemical Shift-Encoded Imaging

Conventional water–fat separation approaches suffer long computational times and are prone to water/fat swaps. To solve these problems, we propose a deep learning-based dual-echo water–fat separation method. With IRB approval, raw data from 68 pediatric clinically indicated dual echo scans were analyzed, corresponding to 19382 contrast-enhanced images. A densely connected hierarchical convolutional network was constructed, in which dual-echo images and corresponding echo times were used as input and water/fat images obtained using the projected power method were regarded as references. Models were trained and tested using knee images with 8-fold cross validation and validated on out-of-distribution data from the ankle, foot, and arm. Using the proposed method, the average computational time for a volumetric dataset with ~400 slices was reduced from 10 min to under one minute. High fidelity was achieved (correlation coefficient of 0.9969, l1 error of 0.0381, SSIM of 0.9740, pSNR of 58.6876) and water/fat swaps were mitigated. I is of particular interest that metal artifacts were substantially reduced, even when the training set contained no images with metallic implants. Using the models trained with only contrast-enhanced images, water/fat images were predicted from non-contrast-enhanced images with high fidelity. The proposed water–fat separation method has been demonstrated to be fast, robust, and has the added capability to compensate for metal artifacts.

Accelerating multi-echo chemical shift encoded water-fat MRI using model-guided deep learning

PURPOSE

To accelerate chemical shift encoded (CSE) water-fat imaging by applying a model-guided deep learning water-fat separation (MGDL-WF) framework to the undersampled k-space data.

METHODS

A model-guided deep learning water-fat separation framework is proposed for the acceleration using Cartesian/radial undersampling data. The proposed MGDL-WF combines the power of CSE water-fat imaging model and data-driven deep learning by jointly using a multi-peak fat model and a modified residual U-net network. The model is used to guide the image reconstruction, and the network is used to capture the artifacts induced by the undersampling. A data consistency layer is used in MGDL-WF to ensure the output images to be consistent with the k-space measurements. A Gauss-Newton iteration algorithm is adapted for the gradient updating of the networks.

RESULTS

Compared with the compressed sensing water-fat separation (CS-WF) algorithm/2-step procedure algorithm, the MGDL-WF increased peak signal-to-noise ratio (PSNR) by 5.31/5.23, 6.11/4.54, and 4.75 dB/1.88 dB with Cartesian sampling, and by 4.13/6.53, 2.90/4.68, and 1.68 dB/3.48 dB with radial sampling, at acceleration rates (R) of 4, 6, and 8, respectively. By using MGDL-WF, radial sampling increased the PSNR by 2.07 dB at R = 8, compared with Cartesian sampling.

CONCLUSIONS

The proposed MGDL-WF enables exploiting features of the water images and fat images from the undersampled multi-echo data, leading to improved performance in the accelerated CSE water-fat imaging. By using MGDL-WF, radial sampling can further improve the image quality with comparable scan time in comparison with Cartesian sampling.

On quantification errors of R 2 * $$ {R}_2^{\ast } $$ and proton density fat fraction mapping in trabecularized bone marrow in the static dephasing regime

PURPOSE

To study the effect of field inhomogeneity distributions in trabecularized bone regions on the gradient echo (GRE) signal with short TEs and to characterize quantification errors on R 2 * $$ {R}_2^{\ast } $$ and proton density fat fraction (PDFF) maps when using a water-fat model with an exponential R 2 * $$ {R}_2^{\ast } $$ decay model at short TEs.

METHODS

Field distortions were simulated based on a trabecular bone micro CT dataset. Simulations were performed for different bone volume fractions (BV/TV) and for different bone-fat composition values. A multi-TE UTE acquisition was developed to acquire multiple UTEs with random order to minimize eddy currents. The acquisition was validated in phantoms and applied in vivo in a volunteer's ankle and knee. Chemical shift encoded MRI (CSE-MRI) based on a Cartesian multi-TE GRE scan was acquired in the spine of patients with metastatic bone disease.

RESULTS

Simulations showed that signal deviations from the exponential signal decay at short TEs were more prominent for a higher BV/TV. UTE multi-TE measurements reproduced in vivo the simulation-based predicted behavior. In regions with high BV/TV, the presence of field inhomogeneities induced an R 2 * $$ {R}_2^{\ast } $$ underestimation in trabecularized bone marrow when using CSE-MRI at 3T with a short TE.

CONCLUSION

R 2 * $$ {R}_2^{\ast } $$ can be underestimated when using short TEs (<2 ms at 3 T) and a water-fat model with an exponential R 2 * $$ {R}_2^{\ast } $$ decay model in multi-echo GRE acquisitions of trabecularized bone marrow.

An Anthropomorphic Digital Reference Object (DRO) for Simulation and Analysis of Breast DCE MRI Techniques

Advances in accelerated magnetic resonance imaging (MRI) continue to push the bounds on achievable spatial and temporal resolution while maintaining a clinically acceptable image quality. Validation tools, including numerical simulations, are needed to characterize the repeatability and reproducibility of such methods for use in quantitative imaging applications. We describe the development of a simulation framework for analyzing and optimizing accelerated MRI acquisition and reconstruction techniques used in dynamic contrast enhanced (DCE) breast imaging. The simulation framework, in the form of a digital reference object (DRO), consists of four modules that control different aspects of the simulation, including the appearance and physiological behavior of the breast tissue as well as the MRI acquisition settings, to produce simulated k-space data for a DCE breast exam. The DRO design and functionality are described along with simulation examples provided to show potential applications of the DRO. The included simulation results demonstrate the ability of the DRO to simulate a variety of effects including the creation of simulated lesions, tissue enhancement modeled by the generalized kinetic model, T1-relaxation, fat signal precession and saturation, acquisition SNR, and changes in temporal resolution.

Free-breathing multitasking multi-echo MRI for whole-liver water-specific T1 , proton density fat fraction, and R2∗ quantification

PURPOSE

To develop a 3D multitasking multi-echo (MT-ME) technique for the comprehensive characterization of liver tissues with 5-min free-breathing acquisition; whole-liver coverage; a spatial resolution of 1.5 × 1.5 × 6 mm³ ; and simultaneous quantification of T₁ , water-specific T₁ (T_1w ), proton density fat fraction (PDFF), and R2∗ .

METHODS

Six-echo bipolar spoiled gradient echo readouts following inversion recovery preparation was performed to generate T₁ , water/fat, and R2∗ contrast. MR multitasking was used to reconstruct the MT-ME images with 3 spatial dimensions: 1 T₁ recovery dimension, 1 multi-echo dimension, and 1 respiratory dimension. A basis function-based approach was developed for T_1w quantification, followed by the estimation of R2∗ and T₁ -corrected PDFF. The intrasession repeatability and agreement against references of MT-ME measurements were tested on a phantom and 15 clinically healthy subjects. In addition, 4 patients with confirmed liver diseases were recruited, and the agreement between MT-ME measurements and references was assessed.

RESULTS

MT-ME produced high-quality, coregistered T₁ , T_1w , PDFF, and R2∗ maps with good intrasession repeatability and substantial agreement with references on phantom and human studies. The intra-class coefficients of T₁ , T_1w , PDFF, and R2∗ from the repeat MT-ME measurements on clinically healthy subjects were 0.989, 0.990, 0.999, and 0.988, respectively. The intra-class coefficients of T₁ , PDFF, and R2∗ between the MT-ME and reference measurements were 0.924, 0.987, and 0.975 in healthy subjects and 0.980, 0.999, and 0.998 in patients. The T_1w was independent to PDFF (R = -0.029, P = .904).

CONCLUSION

The proposed MT-ME technique quantifies T₁ , T_1w , PDFF, and R2∗ simultaneously and is clinically promising for the comprehensive characterization of liver tissue properties.

Fast multi-parametric imaging in abdomen by B 1 + corrected dual-flip angle sequence with interleaved echo acquisition

PURPOSE

To achieve simultaneous T_{1, w} /proton density fat fraction (PDFF)/ R 2 ∗ mapping in abdomen within a single breadth-hold, and validate the accuracy using state-of-art measurement.

THEORY AND METHODS

An optimized multiple echo gradient echo (GRE) sequence with dual flip-angle acquisition was used to realize simultaneous water T₁ (T_{1, w} )/PDFF/ R 2 ∗ quantification. A new method, referred to as "solving the fat-water ambiguity based on their T₁ difference" (SORT), was proposed to address the fat-water separation problem. This method was based on the finding that compared to the true solution, the wrong (or aliased) solution to fat-water separation problem showed extra dependency on the applied flip angle due to the T₁ difference between fat and water. The B 1 + measurement sequence was applied to correct the B 1 + inhomogeneity for T_{1, w} relaxometry. The 2D parallel imaging was incorporated to enable the acquisition within a single breath-hold in abdomen.

RESULTS

The multi-parametric quantification results of the proposed method were consistent with the results of reference methods in phantom experiments (PDFF quantification: R²  = 0.993, mean error 0.73%; T_{1, w} quantification: R²  = 0.999, mean error 4.3%; R 2 ∗ quantification: R²  = 0.949, mean error 4.07 s^-1 ). For volunteer studies, robust fat-water separation was achieved without evident fat-water swaps. Based on the accurate fat-water separation, simultaneous T_{1, w} /PDFF/ R 2 ∗ quantification was realized for whole liver within a single breath-hold.

CONCLUSION

The proposed method accurately quantified T_{1, w} /PDFF/ R 2 ∗ for the whole liver within a single breath-hold. This technique serves as a quantitative tool for disease management in patients with hepatic steatosis.

Advances in spiral fMRI: A high-resolution study with single-shot acquisition

Spiral fMRI has been put forward as a viable alternative to rectilinear echo-planar imaging, in particular due to its enhanced average k-space speed and thus high acquisition efficiency. This renders spirals attractive for contemporary fMRI applications that require high spatiotemporal resolution, such as laminar or columnar fMRI. However, in practice, spiral fMRI is typically hampered by its reduced robustness and ensuing blurring artifacts, which arise from imperfections in both static and dynamic magnetic fields. Recently, these limitations have been overcome by the concerted application of an expanded signal model that accounts for such field imperfections, and its inversion by iterative image reconstruction. In the challenging ultra-high field environment of 7 Tesla, where field inhomogeneity effects are aggravated, both multi-shot and single-shot 2D spiral imaging at sub-millimeter resolution was demonstrated with high depiction quality and anatomical congruency. In this work, we further these advances towards a time series application of spiral readouts, namely, single-shot spiral BOLD fMRI at 0.8 mm in-plane resolution. We demonstrate that high-resolution spiral fMRI at 7 T is not only feasible, but delivers both excellent image quality, BOLD sensitivity, and spatial specificity of the activation maps, with little artifactual blurring. Furthermore, we show the versatility of the approach with a combined in/out spiral readout at a more typical resolution (1.5 mm), where the high acquisition efficiency allows to acquire two images per shot for improved sensitivity by echo combination.

Quantification of Liver Fat Content with CT and MRI: State of the Art

Hepatic steatosis is defined as pathologically elevated liver fat content and has many underlying causes. Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide, with an increasing prevalence among adults and children. Abnormal liver fat accumulation has serious consequences, including cirrhosis, liver failure, and hepatocellular carcinoma. In addition, hepatic steatosis is increasingly recognized as an independent risk factor for the metabolic syndrome, type 2 diabetes, and, most important, cardiovascular mortality. During the past 2 decades, noninvasive imaging-based methods for the evaluation of hepatic steatosis have been developed and disseminated. Chemical shift-encoded MRI is now established as the most accurate and precise method for liver fat quantification. CT is important for the detection and quantification of incidental steatosis and may play an increasingly prominent role in risk stratification, particularly with the emergence of CT-based screening and artificial intelligence. Quantitative imaging methods are increasingly used for diagnostic work-up and management of steatosis, including treatment monitoring. The purpose of this state-of-the-art review is to provide an overview of recent progress and current state of the art for liver fat quantification using CT and MRI, as well as important practical considerations related to clinical implementation.

Evaluation of liver T1 using MOLLI gradient echo readout under the influence of fat

BACKGROUND

The effect of hepatic steatosis on the gradient-echo (GRE) based Modified Look-Locker Inversion Recovery (MOLLI) technique for T1 mapping has not been evaluated. The purpose of this study was to evaluate a GRE based MOLLI technique for hepatic T1 mapping and determine the relationship of T1 differences (ΔT1) on in-phase (IP) and out-of-phase (OP) to fat fraction (FF) measurement.

MATERIALS AND METHODS

3 T MRI included MOLLI T1 mapping with TE = 1.3 (OP), 2.4 (IP), and 1.8 ms, and chemical-shift-encoded sequence with spectral modeling of fat to generate FF map as a reference. Bloch simulations and oil/water phantoms were used to characterize the response of the MOLLI T1 in various FF < 30% since MOLLI T1 estimation was erratic beyond this limit. Curve fit between ΔT1 and FF from simulation was applied to validate the phantom and the in-vivo results. Thirty-eight normal volunteers were included (16 women, Age 44 ± 12 years, BMI 27 ± 5.3 kg/m²). MOLLI water images were reconstructed by the average of OP and IP images, and the T1 values on water images served as the reference for T1 bias calculation defined as the percent difference between OP, IP, TE = 1.8 ms and the referenced water T1. Linear regression was performed to correlate the FF quantified by the reference and MOLLI methods.

RESULTS

Phantom results were consistent with the Bloch simulations. The simulated relationship between FF (0-30%) and ΔT1 could be modeled precisely by a cubic equation with R2 = 1. In-vivo MOLLI ΔT1 and estimated FF were correlated to the reference FF (both R2 ≥ 0.96 and P < 0.001). TE = 1.8 ms demonstrated less T1 bias (-1.34%) compared to TE = OP (5.32%) or IP (-3.8%, both P < 0.001).

CONCLUSION

At 3 T, TE of 1.8 ms can be used to reduce the T1 bias and deliver consistent T1 values when FF is <30%.

Double spectral attenuated inversion recovery (DSPAIR)-an efficient fat suppression technique for late gadolinium enhancement at 3 tesla

Despite clinical use of late gadolinium enhancement (LGE) for two decades, an efficient, robust fat suppression (FS) technique still does not exist for this CMR mainstay. In ischemic and non-ischemic heart disease, differentiating fibrotic tissue from infiltrating and adjacent fat is crucial. Multiple groups have independently developed an FS technique for LGE, double spectral attenuated inversion recovery (DSPAIR), but no comprehensive evaluation was performed. This study aims to fill this gap. DSPAIR uses two SPAIR pulses and one non-selective IR pulse to enable FS LGE, including compatibility with phase sensitive inversion recovery (PSIR). We implemented a magnitude (MAGN) and a PSIR variant and compared them with LGE without FS (CONTROL) and with spectral presaturation with inversion recovery (SPIR) in simulations, phantoms, and patients. Fat magnetization by SPIR, MAGN DSPAIR, and PSIR DSPAIR was simulated as a function of pulse B₁ , readout (RO) pulse number, and fat T_I . A phantom with fat, fibrosis, and myocardium compartments was imaged using all FS methods and modifying pulse B₁ , RO pulse number, and heart rate. Signal was measured in SNR units. Fat, myocardium, and fibrosis SNR and fibrosis-to-fat CNR were obtained. Patient images were acquired with all FS techniques. Fat, myocardium, and fibrosis SNR, fibrosis-to-fat CNR, and image and FS quality were assessed. In the phantom, both DSPAIR variants provided superior FS compared with SPIR, independent of heart rate and RO pulse number. MAGN DSPAIR reduced fat signal by 99% compared with CONTROL, PSIR DSPAIR by 116%, and SPIR by 67% (25 RO pulses). In patients, both DSPAIR variants substantially reduced fat signal (MAGN DSPAIR by 87.1% ± 10.0%, PSIR DSPAIR by 130.5% ± 36.3%), but SPIR did not (35.8% ± 25.5%). FS quality was good to excellent for MAGN and PSIR DSPAIR, and moderate to poor for SPIR. DSPAIR provided highly effective FS across a wide range of parameters. PSIR DSPAIR performed best.

Regularized joint water-fat separation with B0 map estimation in image space for 2D-navigated interleaved EPI based diffusion MRI

Purpose

To develop a new water–fat separation and B₀ estimation algorithm to effectively suppress the multiple resonances of fat signal in EPI. This is especially relevant for DWI where fat is often a confounding factor.

Methods

Water–fat separation based on chemical‐shift encoding enables robust fat suppression in routine MRI. However, for EPI the different chemical‐shift displacements of the multiple fat resonances along the phase‐encoding direction can be problematic for conventional separation algorithms. This work proposes a suitable model approximation for EPI under B₀ and fat off‐resonance effects, providing a feasible multi‐peak water–fat separation algorithm. Simulations were performed to validate the algorithm. In vivo validation was performed in 6 volunteers, acquiring spin‐echo EPI images in the leg (B₀ homogeneous) and head‐neck (B₀ inhomogeneous) regions, using a TE‐shifted interleaved EPI sequence with/without diffusion sensitization. The results are numerically and statistically compared with voxel‐independent water–fat separation and fat saturation techniques to demonstrate the performance of the proposed algorithm.

Results

The reference separation algorithm without the proposed spatial shift correction caused water–fat ambiguities in simulations and in vivo experiments. Some spectrally selective fat saturation approaches also failed to suppress fat in regions with severe B₀ inhomogeneities. The proposed algorithm was able to achieve improved fat suppression for DWI data and ADC maps in the head–neck and leg regions.

Conclusion

The proposed algorithm shows improved suppression of the multi‐peak fat components in multi‐shot interleaved EPI applications compared to the conventional fat saturation approaches and separation algorithms.

Comparison of Ketogenic Diets with and without Ketone Salts versus a Low-Fat Diet: Liver Fat Responses in Overweight Adults

Ketogenic diets (KDs) often contain high levels of saturated fat, which may increase liver fat, but the lower carbohydrate intake may have the opposite effect. Using a controlled feeding design, we compared liver fat responses to a hypocaloric KD with a placebo (PL) versus an energy-matched low-fat diet (LFD) in overweight adults. We also examined the added effect of a ketone supplement (KS). Overweight adults were randomized to a 6-week KD (KD + PL) or a KD with KS (KD + KS); an LFD group was recruited separately. All diets were estimated to provide 75% of energy expenditure. Weight loss was similar between groups (p > 0.05). Liver fat assessed by magnetic resonance imaging decreased after 6 week (p = 0.004) with no group differences (p > 0.05). A subset with nonalcoholic fatty liver disease (NAFLD) (liver fat > 5%, n = 12) showed a greater reduction in liver fat, but no group differences. In KD participants with NAFLD, 92% of the variability in change in liver fat was explained by baseline liver fat (p < 0.001). A short-term hypocaloric KD high in saturated fat does not adversely impact liver health and is not impacted by exogenous ketones. Hypocaloric low-fat and KDs can both be used in the short-term to significantly reduce liver fat in individuals with NAFLD.

Proton MR Spectroscopy Measurements of White and Brown Adipose Tissue in Healthy Humans: Relaxation Parameters and Unsaturated Fatty Acids

Background Activation of brown adipose tissue (BAT) in rodents increases lipolysis in white adipose tissue (WAT) and improves glucose tolerance. Adult humans can have metabolically active BAT. Implications for diabetes and obesity in humans require a better characterization of BAT in humans. Purpose To study fat depots with localized proton MR spectroscopy relaxometry and to identify differences between WAT and fluorine 18 fluorodeoxyglucose (FDG) PET/CT proven cold-activated BAT in humans. Materials and Methods Participants were consecutively enrolled in this prospective study (ClinicalTrials.gov identifiers: NCT01568671 and NCT01399385) from August 2016 to May 2019. Supraclavicular potential BAT regions were localized with MRI. Proton densities, T1, and T2 were measured with localized MR spectroscopy in potential BAT and in subcutaneous WAT. FDG PET/CT after cold stimulation was used to retrospectively identify active supraclavicular BAT or supraclavicular quiescent adipose tissue (QAT) regions. MR spectroscopy results from BAT and WAT were compared with grouped and paired tests. Results Of 21 healthy participants (mean age, 36 years ± 16 [standard deviation]; 13 men) FDG PET/CT showed active BAT in 24 MR spectroscopy-targeted regions in 16 participants (eight men). Four men had QAT. The T2 for methylene protons was shorter in BAT (mean, 69 msec ± 6, 24 regions) than in WAT (mean, 83 msec ± 3, 18 regions, P < .01) and QAT (mean, 78 msec ± 2, five regions, P < .01). A T2 cut-off value of 76 msec enabled the differentiation of BAT from WAT or QAT with a sensitivity of 85% and a specificity of 95%. Densities of protons adjacent and between double bonds were 33% and 24% lower, respectively, in BAT compared with those in WAT (P = .01 and P = .03, respectively), indicating a lower content of unsaturated and polyunsaturated fatty acids, respectively, in BAT compared with WAT. Conclusion Proton MR spectroscopy showed shorter T2 and lower unsaturated fatty acids in brown adipose tissue (BAT) than that in white adipose tissue in healthy humans. It was feasible to identify BAT with MR spectroscopy without the use of PET/CT or cold stimulation. © RSNA, 2021 See also the editorial by Barker in this issue. Online supplemental material is available for this article.

Joint image and field map estimation for multi-echo hyperpolarized 13 C metabolic imaging of the heart

PURPOSE

Image reconstruction of metabolic images from hyperpolarized ¹³ C multi-echo data acquisition is sensitive to susceptibility-induced phase offsets, which are particularly challenging in the heart. A model-based framework for joint estimation of metabolite images and field map from echo shift-encoded data is proposed. Using simulations, it is demonstrated that correction of signal spilling due to incorrect decomposition of metabolites and geometrical distortions over a wide range of off-resonance gradients is possible. In vivo feasibility is illustrated using hyperpolarized [1-¹³ C]pyruvate in the pig heart.

METHODS

The model-based reconstruction for multi-echo, multicoil data was implemented as a nonconvex minimization problem jointly optimizing for metabolic images and B₀ . A comprehensive simulation framework for echo shift-encoded hyperpolarized [1-¹³ C]pyruvate imaging was developed and applied to assess reconstruction performance and distortion correction of the proposed method. In vivo data were obtained in four pigs using hyperpolarized [1-¹³ C]pyruvate on a clinical 3T MR system with a six-channel receiver coil. Dynamic images were acquired during suspended ventilation using cardiac-triggered multi-echo single-shot echo-planar imaging in short-axis orientation.

RESULTS

Simulations revealed that off-resonance gradients up to ±0.26 ppm/pixel can be corrected for with reduced signal spilling and geometrical distortions yielding an accuracy of ≥90% in terms of Dice similarity index. In vivo, improved geometrical consistency (10% Dice improvement) compared to image reconstruction without field map correction and with reference to anatomical data was achieved.

CONCLUSION

Joint image and field map estimation allows addressing off-resonance-induced geometrical distortions and metabolite spilling in hyperpolarized ¹³ C metabolic imaging of the heart.

Simultaneous Multiple Resonance Frequency imaging (SMURF): Fat-water imaging using multi-band principles

PURPOSE

To develop a fat-water imaging method that allows reliable separation of the two tissues, uses established robust reconstruction methods, and requires only one single-echo acquisition.

THEORY AND METHODS

The proposed method uses spectrally selective dual-band excitation in combination with CAIPIRINHA to generate separate images of fat and water simultaneously. Spatially selective excitation without cross-contamination is made possible by the use of spatial-spectral pulses. Fat and water images can either be visualized separately, or the fat images can be corrected for chemical shift displacement and, in gradient echo imaging, for chemical shift-related phase discrepancy, and recombined with water images, generating fat-water images free of chemical shift effects. Gradient echo and turbo spin echo sequences were developed based on this Simultaneous Multiple Resonance Frequency imaging (SMURF) approach and their performance was assessed at 3Tesla in imaging of the knee, breasts, and abdomen.

RESULTS

The proposed method generated well-separated fat and water images with minimal unaliasing artefacts or cross-excitation, evidenced by the near absence of water signal attributed to the fat image and vice versa. The separation achieved was similar to or better than that using separate acquisitions with water- and fat-saturation or Dixon methods. The recombined fat-water images provided similar image contrast to conventional images, but the chemical shift effects were eliminated.

CONCLUSION

Simultaneous Multiple Resonance Frequency imaging is a robust fat-water imaging technique that offers a solution to imaging of body regions with significant amounts of fat.

Diabesity: the combined burden of obesity and diabetes on heart disease and the role of imaging

Diabesity is a term used to describe the combined adverse health effects of obesity and diabetes mellitus. The worldwide dual epidemic of obesity and type 2 diabetes is an important public health issue. Projections estimate a sixfold increase in the number of adults with obesity in 40 years and an increase in the number of individuals with diabetes to 642 million by 2040. Increased adiposity is the strongest risk factor for developing diabetes. Early detection of the effects of diabesity on the cardiovascular system would enable the optimal implementation of effective therapies that prevent atherosclerosis progression, cardiac remodelling, and the resulting ischaemic heart disease and heart failure. Beyond conventional imaging techniques, such as echocardiography, CT and cardiac magnetic resonance, novel post-processing tools and techniques provide information on the biological processes that underlie metabolic heart disease. In this Review, we summarize the effects of obesity and diabetes on myocardial structure and function and illustrate the use of state-of-the-art multimodality cardiac imaging to elucidate the pathophysiology of myocardial dysfunction, prognosticate long-term clinical outcomes and potentially guide treatment strategies.

Improved body quantitative susceptibility mapping by using a variable-layer single-min-cut graph-cut for field-mapping

PURPOSE

To develop a robust algorithm for field-mapping in the presence of water-fat components, large B 0 field inhomogeneities and MR signal voids and to apply the developed method in body applications of quantitative susceptibility mapping (QSM).

METHODS

A framework solving the cost-function of the water-fat separation problem in a single-min-cut graph-cut based on the variable-layer graph construction concept was developed. The developed framework was applied to a numerical phantom enclosing an MR signal void, an air bubble experimental phantom, 14 large field of view (FOV) head/neck region in vivo scans and to 6 lumbar spine in vivo scans. Field-mapping and subsequent QSM results using the proposed algorithm were compared to results using an iterative graph-cut algorithm and a formerly proposed single-min-cut graph-cut.

RESULTS

The proposed method was shown to yield accurate field-map and susceptibility values in all simulation and in vivo datasets when compared to reference values (simulation) or literature values (in vivo). The proposed method showed improved field-map and susceptibility results compared to iterative graph-cut field-mapping especially in regions with low SNR, strong field-map variations and high R 2 ∗ values.

CONCLUSIONS

A single-min-cut graph-cut field-mapping method with a variable-layer construction was developed for field-mapping in body water-fat regions, improving quantitative susceptibility mapping particularly in areas close to MR signal voids.

Liver fat quantification: where do we stand?

Excessive intracellular accumulation of triglycerides in the liver, or hepatic steatosis, is a highly prevalent condition affecting approximately one billion people worldwide. In the absence of secondary cause, the term nonalcoholic fatty liver disease (NAFLD) is used. Hepatic steatosis may progress into nonalcoholic steatohepatitis, the more aggressive form of NAFLD, associated with hepatic complications such as fibrosis, liver failure and hepatocellular carcinoma. Hepatic steatosis is associated with metabolic syndrome, cardiovascular disease and represents an independent risk factor for type 2 diabetes, cardiovascular disease and malignancy. Percutaneous liver biopsy is the current reference standard for NAFLD assessment; however, it is an invasive procedure associated with complications and suffers from high sampling variability, impractical for clinical routine and drug efficiency studies. Therefore, noninvasive imaging methods are increasingly used for the diagnosis and monitoring of NAFLD. Among the methods quantifying liver fat, chemical-shift-encoded MRI (CSE-MRI)-based proton density fat-fraction (PDFF) has shown the most promise. MRI-PDFF is increasingly accepted as quantitative imaging biomarker of liver fat that is transforming daily clinical practice and influencing the development of new treatments for NAFLD. Furthermore, CT is an important imaging method for detection of incidental steatosis, and the practical advantages of quantitative ultrasound hold great promise for the future. Understanding the disease burden of NAFLD and the role of imaging may initiate important interventions aimed at avoiding the hepatic and extrahepatic complications of NAFLD. This article reviews clinical burden of NAFLD, and the role of noninvasive imaging techniques for quantification of liver fat.

B0 and B1 inhomogeneities in the liver at 1.5 T and 3.0 T

PURPOSE

The purpose of this work is to characterize the magnitude and variability of B₀ and B₁ inhomogeneities in the liver in large cohorts of patients at both 1.5 T and 3.0 T.

METHODS

Volumetric B₀ and B₁ maps were acquired over the liver of patients presenting for routine abdominal MRI. Regions of interest were drawn in the nine Couinaud segments of the liver, and the average value was recorded. Magnitude and variation of measured averages in each segment were reported across all patients.

RESULTS

A total of 316 B₀ maps and 314 B₁ maps, acquired at 1.5 T and 3.0 T on a variety of GE Healthcare MRI systems in 630 unique exams, were identified, analyzed, and, in the interest of reproducible research, de-identified and made public. Measured B₀ inhomogeneities ranged (5th-95th percentiles) from -31.7 Hz to 164.0 Hz for 3.0 T (-14.5 Hz to 81.3 Hz at 1.5 T), while measured B₁ inhomogeneities (ratio of actual over prescribed flip angle) ranged from 0.59 to 1.13 for 3.0 T (0.83 to 1.11 at 1.5 T).

CONCLUSION

This study provides robust characterization of B₀ and B₁ inhomogeneities in the liver to guide the development of imaging applications and protocols. Field strength, bore diameter, and sex were determined to be statistically significant effects for both B₀ and B₁ uniformity. Typical clinical liver imaging at 3.0 T should expect B₀ inhomogeneities ranging from approximately -100 Hz to 250 Hz (-50 Hz to 150 Hz at 1.5 T) and B₁ inhomogeneities ranging from approximately 0.4 to 1.3 (0.7 to 1.2 at 1.5 T).

Quantification of Human Central Adipose Tissue Depots: An Anatomically Matched Comparison Between DXA and MRI

Excess visceral adipose tissue (VAT) and VAT volume relative to subcutaneous adipose tissue (SAT) are associated with elevated health risks. This study compares fat measurements by dual-energy X-ray absorptiometry (DXA) and magnetic resonance imaging (MRI). In total, 21 control subjects (Control) and 16 individuals with metabolic syndrome (MetSyn) were scanned by DXA and MRI. The region measured by MRI was matched to the android region defined by DXA, and MRI reproducibility was also evaluated. In addition, liver fat fraction was quantified via MRI and whole-body fat by DXA. VAT measurements are interchangeable between DXA and MRI in the Control (R = 0.946), MetSyn (R = 0.968), and combined cohort (R = 0.983). VAT/SAT ratio did not differ in the Control group (P = .10), but VAT/SAT ratio measured by DXA was significantly higher in the MetSyn group (P < .01) and the combined (P = .03) cohort. Intraobserver (ICC = 0.998) and interobserver (ICC = 0.977) reproducibility of MRI VAT measurements was excellent. Liver fat fraction by MRI was higher (P = .001) in MetSyn (12.4% ± 7.6%) than in controls (2.6% ± 2.2%), as was whole-body fat percentage by DXA (P = .001) between the MetSyn (42.0% ± 8.1%) and Control groups (26.7% ± 6.9%). DXA and MRI VAT are interchangeable when measured over an anatomically matched region of the abdomen, while SAT and VAT/SAT ratio differ between the 2 modalities.

Extended Ketogenic Diet and Physical Training Intervention in Military Personnel

INTRODUCTION

Ketogenic diets (KDs) that elevate ketones into a range referred to as nutritional ketosis represent a possible nutrition approach to address the emerging physical readiness and obesity challenge in the military. An emerging body of evidence demonstrates broad-spectrum health benefits attributed to being in nutritional ketosis, but no studies have specifically explored the use of a KD in a military population using daily ketone monitoring to personalize the diet prescription.

MATERIALS AND METHODS

To evaluate the feasibility, metabolic, and performance responses of an extended duration KD, healthy adults (n = 29) from various military branches participated in a supervised 12-wk exercise training program. Fifteen participants self-selected to an ad libitum KD guided by daily measures of capillary blood ketones and 14 continued their normal mixed diet (MD). A battery of tests were performed before and after the intervention to assess changes in body mass, body composition, visceral fat, liver fat, insulin sensitivity, resting energy metabolism, and physical performance.

RESULTS

All KD subjects were in nutritional ketosis during the intervention as assessed by daily capillary beta-hydroxybutyrate (βHB) (mean βHB 1.2 mM reported 97% of all days) and showed higher rates of fat oxidation indicative of keto-adaptation. Despite no instruction regarding caloric intake, the KD group lost 7.7 kg body mass (range -3.5 to -13.6 kg), 5.1% whole-body percent fat (range -0.5 to -9.6%), 43.7% visceral fat (range 3.0 to -66.3%) (all p < 0.001), and had a 48% improvement in insulin sensitivity; there were no changes in the MD group. Adaptations in aerobic capacity, maximal strength, power, and military-specific obstacle course were similar between groups (p > 0.05).

CONCLUSIONS

US military personnel demonstrated high adherence to a KD and showed remarkable weight loss and improvements in body composition, including loss of visceral fat, without compromising physical performance adaptations to exercise training. Implementation of a KD represents a credible strategy to enhance overall health and readiness of military service members who could benefit from weight loss and improved body composition.

Test-Retest Performance of a 1-Hour Multiparametric MR Image Acquisition Pipeline With Orthotopic Triple-Negative Breast Cancer Patient-Derived Tumor Xenografts

Preclinical imaging is critical in the development of translational strategies to detect diseases and monitor response to therapy. The National Cancer Institute Co-Clinical Imaging Resource Program was launched, in part, to develop best practices in preclinical imaging. In this context, the objective of this work was to develop a 1-hour, multiparametric magnetic resonance image-acquisition pipeline with triple-negative breast cancer patient-derived xenografts (PDXs). The 1-hour, image-acquisition pipeline includes T1- and T2-weighted scans, quantitative T1, T2, and apparent diffusion coefficient (ADC) parameter maps, and dynamic contrast-enhanced (DCE) time-course images. Quality-control measures used phantoms. The triple-negative breast cancer PDXs used for this study averaged 174 ± 73 μL in volume, with region of interest–averaged T1, T2, and ADC values of 1.9 ± 0.2 seconds, 62 ± 3 milliseconds, and 0.71 ± 0.06 μm²/ms (mean ± SD), respectively. Specific focus was on assessing the within-subject test–retest coefficient-of-variation (CV_WS) for each of the magnetic resonance imaging metrics. Determination of PDX volume via manually drawn regions of interest is highly robust, with ∼1% CV_WS. Determination of T2 is also robust with a ∼3% CV_WS. Measurements of T1 and ADC are less robust with CV_WS values in the 6%–11% range. Preliminary DCE test–retest time-course determinations, as quantified by area under the curve and K^trans from 2-compartment exchange (extended Tofts) modeling, suggest that DCE is the least robust protocol, with ∼30%–40% CV_WS.

Myocardial T1 and T2 quantification and water-fat separation using cardiac MR fingerprinting with rosette trajectories at 3T and 1.5T

PURPOSE

This work aims to develop an approach for simultaneous water-fat separation and myocardial T₁ and T₂ quantification based on the cardiac MR fingerprinting (cMRF) framework with rosette trajectories at 3T and 1.5T.

METHODS

Two 15-heartbeat cMRF sequences with different rosette trajectories designed for water-fat separation at 3T and 1.5T were implemented. Water T₁ and T₂ maps, water image, and fat image were generated with B₀ inhomogeneity correction using a B₀ map derived from the cMRF data themselves. The proposed water-fat separation rosette cMRF approach was validated in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI system phantom and water/oil phantoms. It was also applied for myocardial tissue mapping of healthy subjects at both 3T and 1.5T.

RESULTS

Water T₁ and T₂ values measured using rosette cMRF in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology phantom agreed well with the reference values. In the water/oil phantom, oil was well suppressed in the water images and vice versa. Rosette cMRF yielded comparable T₁ but 2~3 ms higher T₂ values in the myocardium of healthy subjects than the original spiral cMRF method. Epicardial fat deposition was also clearly shown in the fat images.

CONCLUSION

Rosette cMRF provides fat images along with myocardial T₁ and T₂ maps with significant fat suppression. This technique may improve visualization of the anatomical structure of the heart by separating water and fat and could provide value in diagnosing cardiac diseases associated with fibrofatty infiltration or epicardial fat accumulation. It also paves the way toward comprehensive myocardial tissue characterization in a single scan.

An Efficient Method for Multi-Parameter Mapping in Quantitative MRI Using B-Spline Interpolation

Quantitative MRI methods that estimate multiple physical parameters simultaneously often require the fitting of a computational complex signal model defined through the Bloch equations. Repeated Bloch simulations can be avoided by matching the measured signal with a precomputed signal dictionary on a discrete parameter grid (i.e. lookup table) as used in MR Fingerprinting. However, accurate estimation requires discretizing each parameter with a high resolution and consequently high computational and memory costs for dictionary generation, storage, and matching. Here, we reduce the required parameter resolution by approximating the signal between grid points through B-spline interpolation. The interpolant and its gradient are evaluated efficiently which enables a least-squares fitting method for parameter mapping. The resolution of each parameter was minimized while obtaining a user-specified interpolation accuracy. The method was evaluated by phantom and in-vivo experiments using fully-sampled and undersampled unbalanced (FISP) MR fingerprinting acquisitions. Bloch simulations incorporated relaxation effects (T₁,T₂) , proton density (PD ) , receiver phase ( φ₀ ), transmit field inhomogeneity ( B₁⁺ ), and slice profile. Parameter maps were compared with those obtained from dictionary matching, where the parameter resolution was chosen to obtain similar signal (interpolation) accuracy. For both the phantom and the in-vivo acquisition, the proposed method approximated the parameter maps obtained through dictionary matching while reducing the parameter resolution in each dimension ( T₁,T₂,B₁⁺ ) by - on average - an order of magnitude. In effect, the applied dictionary was reduced from 1.47GB to 464KB . Furthermore, the proposed method was equally robust against undersampling artifacts as dictionary matching. Dictionary fitting with B-spline interpolation reduces the computational and memory costs of dictionary-based methods and is therefore a promising method for multi-parametric mapping.

MR-based PET attenuation correction using a combined ultrashort echo time/multi-echo Dixon acquisition

PURPOSE

To develop a magnetic resonance (MR)-based method for estimation of continuous linear attenuation coefficients (LACs) in positron emission tomography (PET) using a physical compartmental model and ultrashort echo time (UTE)/multi-echo Dixon (mUTE) acquisitions.

METHODS

We propose a three-dimensional (3D) mUTE sequence to acquire signals from water, fat, and short T₂ components (e.g., bones) simultaneously in a single acquisition. The proposed mUTE sequence integrates 3D UTE with multi-echo Dixon acquisitions and uses sparse radial trajectories to accelerate imaging speed. Errors in the radial k-space trajectories are measured using a special k-space trajectory mapping sequence and corrected for image reconstruction. A physical compartmental model is used to fit the measured multi-echo MR signals to obtain fractions of water, fat, and bone components for each voxel, which are then used to estimate the continuous LAC map for PET attenuation correction.

RESULTS

The performance of the proposed method was evaluated via phantom and in vivo human studies, using LACs from computed tomography (CT) as reference. Compared to Dixon- and atlas-based MRAC methods, the proposed method yielded PET images with higher correlation and similarity in relation to the reference. The relative absolute errors of PET activity values reconstructed by the proposed method were below 5% in all of the four lobes (frontal, temporal, parietal, and occipital), cerebellum, whole white matter, and gray matter regions across all subjects (n = 6).

CONCLUSIONS

The proposed mUTE method can generate subject-specific, continuous LAC map for PET attenuation correction in PET/MR.

Generalized parameter estimation in multi-echo gradient-echo-based chemical species separation

To develop a generalized formulation for multi-echo gradient-echo-based chemical species separation for all MR signal models described by a weighted sum of complex exponentials with phases linear in the echo time. Constraints between estimation parameters in the signal model were abstracted into a matrix formulation of a generic parameter gradient. The signal model gradient was used in a parameter estimation algorithm and the Fisher information matrix. The general formulation was tested in numerical simulations and against literature and in vivo results. The proposed gradient-based parameter estimation and experimental design framework is universally applicable over the whole class of signal models using the matrix abstraction of the signal model-specific parameter constraints as input. Several previous results in magnetic-field mapping and water-fat imaging with different models could successfully be replicated with the same framework and only different input matrices. A framework for generalized parameter estimation in multi-echo gradient-echo MR signal models of multiple chemical species was developed and validated and its software version is freely available online.

Low-level fat fraction quantification at 3 T: comparative study of different tools for water-fat reconstruction and MR spectroscopy

OBJECTIVES

Chemical Shift Encoded Magnetic Resonance Imaging (CSE-MRI)-based quantification of low-level (< 5% of proton density fat fraction-PDFF) fat infiltration requires highly accurate data reconstruction for the assessment of hepatic or pancreatic fat accumulation in diagnostics and biomedical research.

MATERIALS AND METHODS

We compare three software tools available for water/fat image reconstruction and PDFF quantification with MRS as the reference method. Based on the algorithm exploited in the tested software, the accuracy of fat fraction quantification varies. We evaluate them in phantom and in vivo MRS and MRI measurements.

RESULTS

The signal model of Intralipid 20% emulsion used for phantoms was established for 3 T and 9.4 T fields. In all cases, we noticed a high coefficient of determination (R-squared) between MRS and MRI-PDFF measurements: in phantoms <0.9924-0.9990>; and in vivo <0.8069-0.9552>. Bland-Altman analysis was applied to phantom and in vivo measurements.

DISCUSSION

Multi-echo MRI in combination with an advanced algorithm including multi-peak spectrum modeling appears as a valuable and accurate method for low-level PDFF quantification over large FOV in high resolution, and is much faster than MRS methods. The graph-cut algorithm (GC) showed the fewest water/fat swaps in the PDFF maps, and hence stands out as the most robust method of those tested.

Arrhythmogenic Left Ventricular Cardiomyopathy: A Clinical and CMR Study

The clinical features, CMR characteristics and outcomes of arrhythmogenic left ventricular cardiomyopathy (ALVC), which is a very rare nonischemic cardiomyopathy, are currently not well studied. The purpose of the study is to investigate the clinical and cardiovascular magnetic resonance (CMR) imaging characteristics of arrhythmogenic left ventricular cardiomyopathy (ALVC). Fifty-three consecutive patients with ALVC were divided into two groups: ALVC patients without right ventricular (RV) involvement (n = 36, group 1) and those with RV involvement (n = 17, group 2). Clinical symptoms, cardiac electrophysiological findings, and CMR parameters (morphology, ventricular function, and myocardial fibrosis and fatty infiltration) were evaluated in both groups. The two groups showed no significant difference in age, gender, or presenting symptoms (P > 0.05). Right bundle branch block ventricular arrhythmia was less common in patients without RV involvement (50.0% vs.64.7%, P = 0.031). There were no significant differences in left ventricular function between the two groups, however right ventricular ejection fraction was significantly lower in group 2 (40.1 ± 4.0% vs. 48.7 ± 3.9%, P < 0.001). Inverse correlations of left ventricular ejection fraction with fat volume (r = −0.883, p = 0.001), late gadolinium enhancement (LGE) volume (r = −0.892, 0.013), ratio of fat/LGE (r = −0.848, p < 0.001), indexed left ventricular end diastolic volume (r = −0.877, p < 0.001) and indexed left ventricular end systolic volume (r = −0.943, p < 0.001) were all significant. ALVC is a rare disease with fibro-fatty replacement predominantly in the left ventricle, impaired left ventricular systolic function, and ventricular arrhythmias originating from the left ventricle. ALVC with right ventricular involvement may have a worse prognosis.

Efficient Regularized Field Map Estimation in 3D MRI

Magnetic field inhomogeneity estimation is important in some types of magnetic resonance imaging (MRI), including field-corrected reconstruction for fast MRI with long readout times, and chemical shift based water-fat imaging. Regularized field map estimation methods that account for phase wrapping and noise involve nonconvex cost functions that require iterative algorithms. Most existing minimization techniques were computationally or memory intensive for 3D datasets, and are designed for single-coil MRI. This paper considers 3D MRI with optional consideration of coil sensitivity, and addresses the multi-echo field map estimation and water-fat imaging problem. Our efficient algorithm uses a preconditioned nonlinear conjugate gradient method based on an incomplete Cholesky factorization of the Hessian of the cost function, along with a monotonic line search. Numerical experiments show the computational advantage of the proposed algorithm over state-of-the-art methods with similar memory requirements.

Measurement of spleen fat on MRI-proton density fat fraction arises from reconstruction of noise

PURPOSE

This study compares splenic proton density fat fraction (PDFF) measured using confounder-corrected chemical shift-encoded (CSE)-MRI to magnetic resonance spectroscopy (MRS) in human patients at 3T.

METHODS

This was a prospectively designed ancillary study to various previously described single-center studies performed in adults and children with known or suspected nonalcoholic fatty liver disease. Patients underwent magnitude-based MRI (MRI-M), complex-based MRI (MRI-C), high signal-to-noise variants (Hi-SNR MRI-M and Hi-SNR MRI-C), and MRS at 3T for spleen PDFF estimation. PDFF from CSE-MRI methods were compared to MRS-PDFF using Wilcoxon signed-rank tests. Demographics were summarized descriptively. Spearman's rank correlations were computed pairwise between CSE-MRI methods. Individual patient measurements were plotted for qualitative assessment. A significance level of 0.05 was used.

RESULTS

Forty-seven patients (20 female, 27 male) including 12 adults (median 55 years old) and 35 children (median 12 years old). Median PDFF estimated by MRS, MRI-M, Hi-SNR MRI-M, MRI-C, and Hi-SNR MRI-C was 1.0, 2.3, 1.9, 2.2, and 2.0%. The four CSE-MRI methods estimated statistically significant higher spleen PDFF values compared to MRS (p < 0.0001 for all). Pairwise associations in spleen PDFF values measured by different CSE-MRI methods were weak, with the highest Spearman's rank correlations being 0.295 between MRI-M and Hi-SNR MRI-M; none were significant after correction for multiple comparisons. No qualitative relationship was observed between PDFF measurements among the various methods.

CONCLUSION

Overestimation of PDFF by CSE-MRI compared to MRS and poor agreement between related CSE-MRI methods suggest that non-zero PDFF values in human spleen are artifactual.