BACKGROUND CONTEXT: The development of muscle fat infiltration (MFI) in the neck muscles is associated with poor functional recovery following whiplash injury. Custom software and time-consuming manual segmentation of magnetic resonance imaging (MRI) is required for quantitative analysis and presents as a barrier for clinical translation. PURPOSE: The purpose of this work was to establish a qualitative MRI measure for MFI and evaluate its ability to differentiate between individuals with severe whiplash-associated disorder (WAD), mild or moderate WAD, and healthy controls. STUDY DESIGN/SETTING: This is a cross-sectional study. PATIENT SAMPLE: Thirty-one subjects with WAD and 31 age-and sex-matched controls were recruited from an ongoing randomized controlled trial. OUTCOME MEASURES: The cervical multifidus was visually identified and segmented into eighths in the axial fat/water images (C4-C7). Muscle fat infiltration was assessed on a visual scale: 0 for no or marginal MFI, 1 for light MFI, and 2 for distinct MFI. The participants with WAD were divided in two groups: mild or moderate and severe based on Neck Disability Index % scores. METHODS: The mean regional MFI was compared between the healthy controls and each of the WAD groups using the Mann-Whitney U test. Receiver operator characteristic (ROC) analyses were carried out to evaluate the validity of the qualitative method. RESULTS: Twenty (65%) patients had mild or moderate disability and 11 (35%) were considered severe. Inter- and intra-rater reliability was excellent when grading was averaged by level or when frequency of grade II was considered. Statistically significant differences (pamp;lt;.05) in regional MFI were particularly notable between the severe WAD group and healthy controls. The ROC curve, based on detection of distinct MFI, showed an area-under-the curve of 0.768 (95% confidence interval 0.59-0.94) for discrimination of WAD participants. CONCLUSIONS: These preliminary results suggest a qualitative MRI measure for MFI is reliable and valid, and may prove useful toward the classification of WAD in radiology practice. (C) 2017 Elsevier Inc. All rights reserved.

Inflammation is one of the hallmarks of carcinogenesis. High mammographic density has been associated with increased risk of breast cancer but the mechanisms behind are poorly understood. We evaluated whether breasts with different mammographic densities exhibited differences in the inflammatory microenvironment.Postmenopausal women attending the mammography-screening program were assessed having extreme dense, n = 20, or entirely fatty breasts (nondense), n = 19, on their regular mammograms. Thereafter, the women were invited for magnetic resonance imaging (MRI), microdialysis for the collection of extracellular molecules in situ and a core tissue biopsy for research purposes. On the MRI, lean tissue fraction (LTF) was calculated for a continuous measurement of breast density. LTF confirmed the selection from the mammograms and gave a continuous measurement of breast density. Microdialysis revealed significantly increased extracellular in vivo levels of IL-6, IL-8, vascular endothelial growth factor, and CCL5 in dense breast tissue as compared with nondense breasts. Moreover, the ratio IL-1Ra/IL-1 was decreased in dense breasts. No differences were found in levels of IL-1, IL-1Ra, CCL2, leptin, adiponectin, or leptin:adiponectin ratio between the two breast tissue types. Significant positive correlations between LTF and the pro-inflammatory cytokines as well as between the cytokines were detected. Stainings of the core biopsies exhibited increased levels of immune cells in dense breast tissue.Our data show that dense breast tissue in postmenopausal women is associated with a pro-inflammatory microenvironment and, if confirmed in a larger cohort, suggests novel targets for prevention therapies for women with dense breast tissue.

Background

Fruit has since long been advocated as a healthy source of many nutrients, however, the high content of sugars in fruit might be a concern.

Objectives

To study effects of an increased fruit intake compared with similar amount of extra calories from nuts in humans.

Methods

Thirty healthy non-obese participants were randomized to either supplement the diet with fruits or nuts, each at +7 kcal/kg bodyweight/day for two months. Major endpoints were change of hepatic fat content (HFC, by magnetic resonance imaging, MRI), basal metabolic rate (BMR, with indirect calorimetry) and cardiovascular risk markers.

Results

Weight gain was numerically similar in both groups although only statistically significant in the group randomized to nuts (fruit: from 22.15±1.61 kg/m2 to 22.30±1.7 kg/m2, p = 0.24 nuts: from 22.54±2.26 kg/m2 to 22.73±2.28 kg/m2, p = 0.045). On the other hand BMR increased in the nut group only (p = 0.028). Only the nut group reported a net increase of calories (from 2519±721 kcal/day to 2763±595 kcal/day, p = 0.035) according to 3-day food registrations. Despite an almost three-fold reported increased fructose-intake in the fruit group (from 9.1±6.0 gram/day to 25.6±9.6 gram/day, p<0.0001, nuts: from 12.4±5.7 gram/day to 6.5±5.3 gram/day, p = 0.007) there was no change of HFC. The numerical increase in fasting insulin was statistical significant only in the fruit group (from 7.73±3.1 pmol/l to 8.81±2.9 pmol/l, p = 0.018, nuts: from 7.29±2.9 pmol/l to 8.62±3.0 pmol/l, p = 0.14). Levels of vitamin C increased in both groups while α-tocopherol/cholesterol-ratio increased only in the fruit group.

Conclusions

Although BMR increased in the nut-group only this was not linked with differences in weight gain between groups which potentially could be explained by the lack of reported net caloric increase in the fruit group. In healthy non-obese individuals an increased fruit intake seems safe from cardiovascular risk perspective, including measurement of HFC by MRI.

Aramchol, an oral stearoyl-coenzyme-A-desaturase-1 inhibitor, has been shown to reduce hepatic fat content in patients with primary nonalcoholic fatty liver disease (NAFLD); however, its effect in patients with human immunodeficiency virus (HIV)-associated NAFLD is unknown. The aramchol for HIV-associated NAFLD and lipodystrophy (ARRIVE) trial was a double-blind, randomized, investigator-initiated, placebo-controlled trial to test the efficacy of 12 weeks of treatment with aramchol versus placebo in HIV-associated NAFLD. Fifty patients with HIV-associated NAFLD, defined by magnetic resonance imaging (MRI)-proton density fat fraction (PDFF) amp;gt;= 5%, were randomized to receive either aramchol 600 mg daily (n = 25) or placebo (n = 25) for 12 weeks. The primary endpoint was a change in hepatic fat as measured by MRI-PDFF in colocalized regions of interest. Secondary endpoints included changes in liver stiffness using magnetic resonance elastography (MRE) and vibration-controlled transient elastography (VCTE), and exploratory endpoints included changes in total-body fat and muscle depots on dual-energy X-ray absorptiometry (DXA), whole-body MRI, and cardiac MRI. The mean (+/- standard deviation) of age and body mass index were 48.2 +/- 10.3 years and 30.7 +/- 4.6 kg/m(2), respectively. There was no difference in the reduction in mean MRI-PDFF between the aramchol group at -1.3% (baseline MRI-PDFF 15.6% versus end-of-treatment MRI-PDFF 14.4%, P = 0.24) and the placebo group at -1.4% (baseline MRI-PDFF 13.3% versus end-of-treatment MRI-PDFF 11.9%, P = 0.26). There was no difference in the relative decline in mean MRI-PDFF between the aramchol and placebo groups (6.8% versus 1.1%, P = 0.68). There were no differences in MRE-derived and VCTE-derived liver stiffness and whole-body (fat and muscle) composition analysis by MRI or DXA. Compared to baseline, end-of-treatment aminotransferases were lower in the aramchol group but not in the placebo arm. There were no significant adverse events. Conclusion: Aramchol, over a 12-week period, did not reduce hepatic fat or change body fat and muscle composition by using MRI-based assessment in patients with HIV-associated NAFLD (clinicaltrials.gov ID:NCT02684591).

Objective: This study aims to investigate whether antidepressant users display differences in fat distribution and muscle composition relative to non-users and to explore risk factors for developing cardiovascular disease (CVD) and type 2 diabetes. Methods: The study used quantitative adipose and muscle tissue measures derived from magnetic resonance imaging data from UK Biobank (N = 40,174). Fat distribution and muscle composition of selective serotonin reuptake inhibitor (SSRI) and tricyclic antidepressant (TCA) users were compared with sex-, age-, and BMI-matched control individuals. Cox regression models were used to test for increased risk of developing CVD and type 2 diabetes. Results: SSRI users had more visceral fat, smaller muscle volume, and higher muscle fat infiltration compared with matched control individuals. Female users showed a larger increase in BMI over time compared with male users. However, male users displayed an unhealthier body composition profile. Male SSRI users also had an increased risk of developing CVD. Both male and female TCA users showed lower muscle volume and an increased risk of developing type 2 diabetes. Conclusions: Adverse changes in body composition of antidepressant users are not captured by tracking the body weight or the BMI of the patients. These changes may lead to a worsened cardiometabolic risk profile.

Atlas-based segmentation is often used to segment medical image regions. For intensity-normalized data, the quality of these segmentations is highly dependent on the similarity between the atlas and the target under the used registration method. We propose a geodesic registration method for interactive atlas-based segmentation using empirical multi-scale anatomical manifolds. The method utilizes unlabeled images together with the labeled atlases to learn empirical anatomical manifolds. These manifolds are defined on distinct scales and regions and are used to propagate the labeling information from the atlases to the target along anatomical geodesics. The resulting competing segmentations from the different manifolds are then ranked according to an image-based similarity measure. We used image volumes acquired using magnetic resonance imaging from 36 subjects. The performance of the method was evaluated using a liver segmentation task. The result was then compared to the corresponding performance of direct segmentation using Dice Index statistics. The method shows a significant improvement in liver segmentation performance between the proposed method and direct segmentation. Furthermore, the standard deviation in performance decreased significantly. Using competing complementary manifolds defined over a hierarchy of region of interests gives an additional improvement in segmentation performance compared to the single manifold segmentation.

PURPOSE:

To quantitatively and qualitatively evaluate the water-signal performance of the consistent intensity inhomogeneity correction (CIIC) method to correct for intensity inhomogeneities METHODS: Water-fat volumes were acquired using 1.5 Tesla (T) and 3.0T symmetrically sampled 2-point Dixon three-dimensional MRI. Two datasets: (i) 10 muscle tissue regions of interest (ROIs) from 10 subjects acquired with both 1.5T and 3.0T whole-body MRI. (ii) Seven liver tissue ROIs from 36 patients imaged using 1.5T MRI at six time points after Gd-EOB-DTPA injection. The performance of CIIC was evaluated quantitatively by analyzing its impact on the dispersion and bias of the water image ROI intensities, and qualitatively using side-by-side image comparisons.

RESULTS:

CIIC significantly ( P1.5T≤2.3×10-4,P3.0T≤1.0×10-6) decreased the nonphysiological intensity variance while preserving the average intensity levels. The side-by-side comparisons showed improved intensity consistency ( Pint⁡≤10-6) while not introducing artifacts ( Part=0.024) nor changed appearances ( Papp≤10-6).

CONCLUSION:

CIIC improves the spatiotemporal intensity consistency in regions of a homogenous tissue type. J. Magn. Reson. Imaging 2014.

There is an intimate body-brain connection in ageing, and obesity is a key risk factor for poor cardiometabolic health and neurodegenerative conditions. Although research has demonstrated deleterious effects of obesity on brain structure and function, the majority of studies have used conventional measures such as waist-to-hip ratio, waist circumference, and body mass index. While sensitive to gross features of body composition, such global anthropometric features fail to describe regional differences in body fat distribution and composition. The sample consisted of baseline brain magnetic resonance imaging (MRI) acquired from 790 healthy participants aged 18-94 years (mean +/- standard deviation (SD) at baseline: 46.8 +/- 16.3), and follow-up brain MRI collected from 272 of those individuals (two time-points with 19.7 months interval, on average (min = 9.8, max = 35.6). Of the 790 included participants, cross-sectional body MRI data was available from a subgroup of 286 participants, with age range 19-86 (mean = 57.6, SD = 15.6). Adopting a mixed cross-sectional and longitudinal design, we investigated cross-sectional body magnetic resonance imaging measures of adipose tissue distribution in relation to longitudinal brain structure using MRI-based morphometry (T1) and diffusion tensor imaging (DTI). We estimated tissue-specific brain age at two time points and performed Bayesian multilevel modelling to investigate the associations between adipose measures at follow-up and brain age gap (BAG) - the difference between actual age and the prediction of the brains biological age - at baseline and follow-up. We also tested for interactions between BAG and both time and age on each adipose measure. The results showed credible associations between T1-based BAG and liver fat, muscle fat infiltration (MFI), and weight-to-muscle ratio (WMR), indicating older-appearing brains in people with higher measures of adipose tissue. Longitudinal evidence supported interaction effects between time and MFI and WMR on T1-based BAG, indicating accelerated ageing over the course of the study period in people with higher measures of adipose tissue. The results show that specific measures of fat distribution are associated with brain ageing and that different compartments of adipose tissue may be differentially linked with increased brain ageing, with potential to identify key processes involved in age-related transdiagnostic disease processes.

Ageing is a heterogeneous multisystem process involving different rates of decline in physiological integrity across biological systems. The current study dissects the unique and common variance across body and brain health indicators and parses inter-individual heterogeneity in the multisystem ageing process. Using machine-learning regression models on the UK Biobank data set (N = 32,593, age range 44.6-82.3, mean age 64.1 years), we first estimated tissue-specific brain age for white and gray matter based on diffusion and T1-weighted magnetic resonance imaging (MRI) data, respectively. Next, bodily health traits, including cardiometabolic, anthropometric, and body composition measures of adipose and muscle tissue from bioimpedance and body MRI, were combined to predict 'body age'. The results showed that the body age model demonstrated comparable age prediction accuracy to models trained solely on brain MRI data. The correlation between body age and brain age predictions was 0.62 for the T1 and 0.64 for the diffusion-based model, indicating a degree of unique variance in brain and bodily ageing processes. Bayesian multilevel modelling carried out to quantify the associations between health traits and predicted age discrepancies showed that higher systolic blood pressure and higher muscle-fat infiltration were related to older-appearing body age compared to brain age. Conversely, higher hand-grip strength and muscle volume were related to a younger-appearing body age. Our findings corroborate the common notion of a close connection between somatic and brain health. However, they also suggest that health traits may differentially influence age predictions beyond what is captured by the brain imaging data, potentially contributing to heterogeneous ageing rates across biological systems and individuals. A 'body age' model trained on health traits demonstrated comparable age prediction accuracy to models trained solely on brain MRI data. Health traits may differentially influence age predictions beyond what is captured by the brain imaging data, revealing a degree of unique variance in brain and bodily ageing processes. image

Background and aim: Quantification of body compartments, particularly the interaction between adipose tissue and skeletal muscle, is emerging as novel a biomarker of metabolic health. The present study evaluated the impact of liver transplant (LT) on body compartments. Methods: Totally 66 adult LT recipients were enrolled in whom body compartments including visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (ASAT), muscle fat infiltration (MFI), fat-free muscle volume (FFMV), and liver fat (LF) were quantified via whole body magnetic resonance imaging (MRI). To provide non-LT comparison, each LT recipient was matched to at least 150 non-LT controls for same sex, age, and body mass index (BMI) from the UK Biobank registry. Results: LT recipients (vs matched non-LT controls) had significantly higher subcutaneous (13.82 +/- 5.47 vs 12.10 +/- 5.10 L, P &lt; 0.001) and visceral fat (7.59 +/- 3.75 vs 6.72 +/- 3.06 L, P = 0.003) and lower LF (5.88 +/- 7.14 vs 8.75 +/- 6.50%, P &lt; 0.001) and muscle volume (11.69 +/- 2.95 vs 12.12 +/- 2.90 L, P = 0.027). In subgroup analysis, patients transplanted for metabolic dysfunction-associated steatohepatitis (MASH) cirrhosis (vs non-MASH cirrhosis) had higher ASAT, VAT, and MFI. A trend toward higher LF content was noted; however, this did not reach statistical significance (6.90 +/- 7.35 vs 4.04 +/- 6.23%, P = 0.189). Finally, compared with matched non-LT controls, patients transplanted for MASH cirrhosis had higher ASAT and VAT; however, FFMV and MFI were similar. Conclusion: Using non-LT controls, the current study established the higher-than-expected adiposity burden among LT recipients, which is even higher among patients transplanted for MASH cirrhosis. These findings provide data needed to design future studies developing radiomics-based risk-stratification strategies in LT recipients.

Purpose There is an absence of reproducibility studies on MRI-based body composition analysis in current literature. Therefore, the aim of this study was to investigate the between-scanner reproducibility and the repeatability of a method for MRI-based body composition analysis. Methods Eighteen healthy volunteers of varying body mass index and adiposity were each scanned twice on five different 1.5T and 3T scanners from three different vendors. Two-point Dixon neck-to knee images and two additional liver scans were acquired with similar protocols. Visceral adipose tissue (VAT) volume, abdominal subcutaneous adipose tissue (ASAT) volume, thigh muscle volume, and muscle fat infiltration (MFI) in the thigh muscle were measured. Liver proton density fat fraction (PDFF) was assessed using two different methods, the scanner vendors 6-point method and an in-house 2-point method. Within-scanner test-retest repeatability and between-scanner reproducibility were calculated using analysis of variance. Results Repeatability coefficients were 13 centiliters (cl) (VAT), 24 cl (ASAT), 17 cl (total thigh muscle volume), 0.53% (MFI), and 1.27-1.37% for liver PDFF. Reproducibility coefficients were 24 cl (VAT), 42 cl (ASAT), 31 cl (total thigh muscle volume), 1.44% (MFI), and 2.37-2.40% for liver PDFF. Conclusion For all measures except MFI, the within-scanner repeatability explained much of the overall reproducibility. The two methods for measuring liver fat had similar reproducibility. This study showed that the investigated method eliminates effects due to scanner differences. The results can be used for power calculations in clinical studies or to better understand the scanner-induced variability in clinical applications.

This paper presents a novel method for atlas-based segmentation of medical images. The method uses semi- supervised learning of a graph describing a manifold of anatom- ical variations of whole-body images, where unlabelled data are used to find a path with small deformations from the labelled atlas to the target image. The method is evaluated on 36 whole-body magnetic resonance images with manually segmented livers as ground truth. Significant improvement (p < 0.001) was obtained compared to direct atlas-based registration. 

Present invention discloses systems and methods for improvement of magnetic resonance images. Correction of a chemical shift artefact in an image acquired from a magnetic resonance imaging system is obtained by a system and a method involving iterative - compensation for the misregistration effect in an image domain. Correction of an intensity inhomogeneity in such images is obtained by a system and a method involving locating voxels corresponding to pure adipose tissue and estimating correction field from these points.

Central obesity is the hallmark of a number of non-inheritable disorders. The advent of imaging techniques such as magnetic resonance imaging (MRI) has allowed for a fast and accurate assessment of body fat content and distribution. However, image analysis continues to be one of the major obstacles for the use of MRI in large scale studies. In this study we assess the validity of the recently proposed fat-muscle-quantitation-system (AMRA^TM Profiler) for the quantification of intra-abdominal adipose tissue (IAAT) and abdominal subcutaneous adipose tissue (ASAT) from abdominal MR images.  Abdominal MR images were acquired from 23 volunteers with a broad range of BMIs and analysed using SliceOmatic, the current gold-standard, and the AMRA^TM Profiler based on a non-rigid image registration of a library of segmented atlases. The results show that there was a highly significant correlation between the fat volumes generated by both analysis methods, (Pearson correlation r = 0.97 p<0.001), with the AMRA^TM Profiler analysis being significantly faster (~3 mins) than the conventional SliceOmatic approach (~40 mins). There was also excellent agreement between the methods for the quantification of IAAT (AMRA 4.73 ± 1.99 vs SliceOmatic 4.73 ± 1.75 litres, p=0.97). For the AMRA^TM Profiler analysis, the intra-observer coefficient of variation was 1.6 % for IAAT and 1.1 % for ASAT, the inter-observer coefficient of variation was 1.4 % for IAAT and 1.2 % for ASAT, the intra-observer correlation was 0.998 for IAAT and 0.999 for ASAT, and the inter-observer correlation was 0.999 for both IAAT and ASAT. These results indicate that precise and accurate measures of body fat content and distribution can be obtained in a fast and reliable form by the AMRA^TM Profiler, opening up the possibility of large-scale human phenotypic studies.

Research with the aim to translate findings of the beneficial effects induced by brown adipose tissue (BAT) on metabolism, as seen in various non-human experimental systems to also include human metabolism requires tools that accurately measure how BAT influences human metabolism. This review sets out to discuss such techniques, how they can be used, what they can measure and also some of their limitations. The focus is on detection and functional analysis of human BAT and how this can be facilitated by applying advanced imaging technology such as:  PET (Positron Emission Tomography), MRI (Magnetic Resonance Imaging), and DECT (Dual Energy Computed Tomography).

This paper gives a brief overview of common non-invasive techniques for body composition analysis and a more in-depth review of a body composition assessment method based on fat-referenced quantitative magnetic resonance imaging (MRI). Earlier published studies of this method are summarized, and a previously un-published validation study, based on 4.753 subjects from the UK Biobank imaging cohort, comparing the quantitative MRI method with dual-energy x-ray absorptiometry (DXA) is presented. For whole-body measurements of adipose tissue (AT) or fat and lean tissue (LT), DXA and quantitative MRI show excellent agreement with linear correlation of 0.99 and 0.97, and coefficient of variation (CV) of 4.5 % and 4.6 % for fat (computed from AT) and lean tissue respectively, but the agreement was found significantly lower for visceral adipose tissue, with a CV of more than 20 %. The additional ability of MRI to also measure muscle volumes, muscle AT infiltration and ectopic fat in combination with rapid scanning protocols and efficient image analysis tools make quantitative MRI a powerful tool for advanced body composition assessment. 

A novel method of high -spatial -resolution, 3D B1 -field distribution measurements is presented. The method is independent of the MR -scanner, and it allows for automated acquisitions of complete maps of all magnetic field vector components for both proton and heteronuclear MR coils of arbitrary geometrical shapes. The advantage of the method proposed here, compared with methods based on measurements with an MR -scanner, is that a complete image of both receive and transmit B1 -fields, including the phase of the B1 -field, can be acquired. The B1 field maps obtained in this manner can be used for absolute quantification of metabolites in MRS experiments, as well as for intensity compensations in imaging experiments, both of which are important concepts in biological and medical MR applications. Another use might be in coil development and testing. A comparison with B1 field magnitude maps obtained with an MR -scanner was included to validate the accuracy of the proposed method.

AimsTo describe the overall fat distribution patterns independent of body mass index (BMI) in participants with type 2 diabetes (T2D) in the SURPASS-3 MRI substudy by comparison with sex- and BMI-matched virtual control groups (VCGs) derived from the UK Biobank imaging study at baseline and Week 52. MethodsFor each study participant at baseline and Week 52 (N = 296), a VCG of &gt;= 150 participants with the same sex and similar BMI was identified from the UK Biobank imaging study (N = 40 172). Average visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (aSAT) and liver fat (LF) levels and the observed standard deviations (SDs; standardized normal z-scores: z-VAT, z-aSAT and z-LF) were calculated based on the matched VCGs. Differences in z-scores between baseline and Week 52 were calculated to describe potential shifts in fat distribution pattern independent of weight change. ResultsBaseline fat distribution patterns were similar across pooled tirzepatide (5, 10 and 15 mg) and insulin degludec (IDeg) arms. Compared with matched VCGs, SURPASS-3 participants had higher baseline VAT (mean [SD] z-VAT +0.42 [1.23]; p &lt; 0.001) and LF (z-LF +1.24 [0.92]; p &lt; 0.001) but similar aSAT (z-aSAT -0.13 [1.11]; p = 0.083). Tirzepatide-treated participants had significant decreases in z-VAT (-0.18 [0.58]; p &lt; 0.001) and z-LF (-0.54 [0.84]; p &lt; 0.001) but increased z-aSAT (+0.11 [0.50]; p = 0.012). Participants treated with IDeg had a significant change in z-LF only (-0.46 [0.90]; p = 0.001), while no significant changes were observed for z-VAT (+0.13 [0.52]; p = 0.096) and z-aSAT (+0.09 [0.61]; p = 0.303). ConclusionIn this exploratory analysis, treatment with tirzepatide in people with T2D resulted in a significant reduction of z-VAT and z-LF, while z-aSAT was increased from an initially negative value, suggesting a possible treatment-related shift towards a more balanced fat distribution pattern with prominent VAT and LF loss.

Background Quantitative-chemical-shift-encoded (CSE)-MRI methods have been applied to the liver. The feasibility and potential utility CSE-MRI in monitoring changes in pancreatic proton density fat fraction (PDFF) have not yet been demonstrated. Purpose To use quantitative CSE-MRI to estimate pancreatic fat changes during a weight-loss program in adults with severe obesity and nonalcoholic fatty liver disease (NAFLD). To explore the relationship of reduction in pancreatic PDFF with reductions in anthropometric indices. Study Type Prospective/longitudinal. Population Nine adults with severe obesity and NAFLD enrolled in a weight-loss program. Field Strength/Sequence CSE-MRI fat quantification techniques and multistation-volumetric fat/water separation techniques were performed at 3 T. Assessment PDFF values were recorded from parametric maps colocalized across timepoints. Statistical Tests Rates of change of log-transformed variables across time were determined (linear-regression), and their significance assessed compared with no change (Wilcoxon test). Rates of change were correlated pairwise (Spearmans correlation). Results Mean pancreatic PDFF decreased by 5.7% (range 0.7-17.7%) from 14.3 to 8.6%, hepatic PDFF by 11.4% (2.6-22.0%) from 14.8 to 3.4%, weight by 30.9 kg (17.3-64.2 kg) from 119.0 to 88.1 kg, body mass index by 11.0 kg/m(2) (6.3-19.1 kg/m(2)) from 44.1 to 32.9 kg/m(2), waist circumference (WC) by 25.2 cm (4.0-41.0 cm) from 133.1 to 107.9 cm, HC by 23.5 cm (4.5-47.0 cm) from 135.8 to 112.3 cm, visceral adipose tissue (VAT) by 2.9 L (1.7-5.7 L) from 7.1 to 4.2 L, subcutaneous adipose tissue (SCAT) by 4.0 L (2.9-7.4 L) from 15.0 to 11.0 L. Log-transformed rate of change for pancreatic PDFF was moderately correlated with log-transformed rates for hepatic PDFF, VAT, SCAT, and WC (rho = 0.5, 0.47, 0.45, and 0.48, respectively), although not statistically significant. Data Conclusion Changes in pancreatic PDFF can be estimated by quantitative CSE-MRI in adults undergoing a weight-loss surgery program. Pancreatic and hepatic PDFF and anthropometric indices decreased significantly. Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;50:1092-1102.

There is an unmet need to identify biomarkers sensitive to change in rare, slowly progressive neuromuscular diseases. Quantitative magnetic resonance imaging (MRI) of muscle may offer this opportunity, as it is noninvasive and can be carried out almost independent of patient cooperation and disease severity. Muscle fat content correlates with muscle function in neuromuscular diseases, and changes in fat content precede changes in function, which suggests that muscle MRI is a strong biomarker candidate to predict prognosis and treatment efficacy. In this paper, we review the evidence suggesting that muscle MRI may be an important biomarker for diagnosis and to monitor change in disease severity. ANN NEUROL 2020

Magnetic resonance (MR) has become one of the most important diagnostic tools in modern medicine. It provides superior soft tissue contrast compared to other imaging modalities, it is extremely flexible as it can be used to image all parts of the body, and it is considered to be safe for patients.

Today almost all MR is performed in a non-quantitative manner, only by comparing neighbouring tissue in the search for pathology. It is possible to quantify the MR-signals to its physical entities, but time consuming and complicated calibration procedures have prevented this in clinical routine.

In this work two different applications of quantitative MR-spectroscopy in diffuse liver and neurological disease, and a new rapid method for simultaneous quantification of proton density, T1 relaxation and T2* relaxation in MR-imaging are presented.

In Paper I, absolutely quantified phosphorus MR-spectroscopy was tested as a predictive tool in order to determine the degree of fibrosis on patients with diffuse liver disease. One group with steatosis and none to moderate inflammation (n=13), one group with severe fibrosis or cirrhosis (n=16), and one group of healthy volunteers (n=13) were included in the study.

Lower concentrations of PDE (p = 0.025), and a higher metabolic charge (AC) [42] (p < 0.001) were found in the cirrhosis group. A sensitivity and specificity of 81% and 69% respectively, were found for the discrimination between mild and advanced fibrosis using PDE concentrations, and 93% and 54% using AC. The results suggest PDE as a marker of liver fibrosis and AC as a potential clinically useful parameter in discriminating mild from advanced fibrosis.

In Paper II proton MR-spectroscopy was used to investigate if there were differences in the concentrations of the observable metabolites in normal appearing white matter in patients with clinically definite multiple sclerosis (MS), and with normal MR-images compared to healthy volunteers. This 'MRI-negative' group consisted of fourteen patients which were compared with fourteen healthy controls. Absolutely quantified proton MR-spectra were acquired from four different voxels in NAWM.

Significant differences in absolute metabolite concentrations were observed between the two groups. The MS-patients had lower total N-acetyl compounds (tNA) (p=0.002) compared to the healthy controls and lower concentration of choline-containing compounds (Cho) compared to the healthy controls (p<0.001). EDSS showed a slightly positive correlation to myolns concentrations (0.14mM/EDSS,r² = 0.06) and a slightly negative correlation to tNA concentrations (-0.41 mM/EDSS,r² = 0.22). The finding of lower Cho concentrations has not been reported previously and was unexpected.

In Paper III a new rapid imaging method was presented for determination of proton density, B1, T2* relaxation and T1 relaxation. The method was based on a modified Look-Locker pulse sequence with two main differences. (1) The exchange of the inversion pulse in the Lock-Looker sequence to a saturation pulse in order to enable detection of the B1 field, and (2) the introduction of a multi-echo read-out to enable the detection of T2*. The signal intensity was then scaled to proton density using the estimated B1, T1, and T2* value.

The method was validated in vitro, using phantoms filled with solution of different T1 and T2* water relaxation values, and by comparing the results of the measurements to reference metcyods. In vivo the method was compared with literature values.

The validation showed that the method was highly accurate, both in vitro and in vivo, and that this method enabled quantitative imaging of MR-parameters within a clinically feasible examination time. Potential applications of the method are, among a great range of possibilities, to rapidly provide all the necessary quantification parameters in MR-spectroscopy, and to simultaneously provide fast quantitative diagnostic imaging.

Introduction: Magnetic resonance (MR) imaging is one of the most important diagnostic tools in modern medicine. Compared to other imaging modalities, it provides superior soft tissue contrast of all parts of the body and it is considered to be safe for patients. Today almost all MR is performed in a nonquantitative manner, only comparing neighboring tissue in the search for pathology. It is possible to quantify MR-signals and relate them to their physical entities, but time consuming and complicated calibration procedures have prevented this being used in a practical manner for clinical routines. The aim of this work is to develop and improve quantification methods in MRspectroscopy (MRS) and MR-imaging (MRI). The techniques are intended to be applied to diffuse diseases, where conventional imaging methods are unable to perform accurate staging or to reveal metabolic changes associated with disease development.

Methods: Proton (1H) MRS was used to characterize the white matter in the brain of multiple sclerosis (MS) patients. Phosphorus (31P) MRS was used to evaluate the energy metabolism in patients with diffuse liver disease. A new quantitative MRI (qMRI) method was invented for accurate, rapid and simultaneous quantification of B1, T1, T2, and proton density. A method for automatic assessment of visceral adipose tissue volume based on an in- and out-ofphase imaging protocol was developed. Finally, a method for quantification of the hepatobiliary uptake of liver specific T1 enhancing contrast agents was demonstrated on healthy subjects.

Results: The 1H MRS investigations of white matter in MS-patients revealed a significant correlation between tissue concentrations of Glutamate and Creatine on the one hand and the disease progression rate on the other, as measured using the MSSS. High accuracy, both in vitro and in vivo, of the measured MR-parameters from the qMRI method was observed. 31P MRS showed lower concentrations of phosphodiesters, and a higher metabolic charge in patients with cirrhosis, compared to patients with mild fibrosis and to controls. The adipose tissue quantification method agreed with estimates obtained using manual segmentation, and enabled measurements which were insensitive to partial volume effects. The hepatobiliary uptake of Gd-EOB-DTPA and Gd-BOPTA was significantly correlated in healthy subjects.

Conclusion: In this work, new methods for accurate quantification of MR parameters in diffuse diseases in the liver and the brain were demonstrated. Several applications were shown where quantitative MR improves the interpretation of observed signal changes in MRI and MRS in relation to underlying differences in physiology and pathophysiology.

Objectives   To develop and evaluate a procedure for quantifying the hepatocyte-specific uptake of Gd-BOPTA and Gd-EOB-DTPA using dynamic contrast-enhanced (DCE) MRI. Methods   Ten healthy volunteers were prospectively recruited and 21 patients with suspected hepatobiliary disease were retrospectively evaluated. All subjects were examined with DCE-MRI using 0.025 mmol/kg of Gd-EOB-DTPA. The healthy volunteers underwent an additional examination using 0.05 mmol/kg of Gd-BOPTA. The signal intensities (SI) of liver and spleen parenchyma were obtained from unenhanced and enhanced acquisitions. Using pharmacokinetic models of the liver and spleen, and an SI rescaling procedure, a hepatic uptake rate, K _Hep, estimate was derived. The K _Hep values for Gd-EOB-DTPA were then studied in relation to those for Gd-BOPTA and to a clinical classification of the patient’s hepatobiliary dysfunction. Results   K _Hep estimated using Gd-EOB-DTPA showed a significant Pearson correlation with K _Hep estimated using Gd-BOPTA (r = 0.64; P < 0.05) in healthy subjects. Patients with impaired hepatobiliary function had significantly lower K _Hep than patients with normal hepatobiliary function (K _Hep = 0.09 ± 0.05 min^-1 versus K _Hep = 0.24 ± 0.10 min⁻¹; P < 0.01). Conclusions   A new procedure for quantifying the hepatocyte-specific uptake of T ₁-enhancing contrast agent was demonstrated and used to show that impaired hepatobiliary function severely influences the hepatic uptake of Gd-EOB-DTPA. Key Points   • The liver uptake of contrast agents may be measured with standard clinical MRI. • Calculation of liver contrast agent uptake is improved by considering splenic uptake. • Liver function affects the uptake of the liver-specific contrast agent Gd-EOB-DTPA. • Hepatic uptake of two contrast agents (Gd-EOB-DTPA, Gd-BOPTA) is correlated in healthy individuals. • This method can be useful for determining liver function, e.g. before hepatic surgery

Background: The multiple sclerosis (MS) severity scale (MSSS) is a new scoring procedure to clinically characterize the rate of disease progression in MS, rather than the disability of the patient. The latter is often characterized using the expanded disability status score (EDSS). The progress rate of the disease, magnetic resonance imaging (MRI)-based measures of ‘black hole lesions’, and atrophy have all been shown to be predicted well by MSSS. In this study we investigated possible relationships between brain metabolite concentrations, measured using proton (1H) magnetic resonance spectroscopy (MRS), and MSSS.

Purpose: Our aims were to quantitatively investigate the metabolite concentrations in normal appearing white matter (NAWM) in MS-patients, and also to investigate possible correlations between disease subtype, EDSS and MSSS and metabolite concentrations. To minimize the interference from lesion contamination in the MRS measurement, a refined novel analysis procedure had to be developed in order to correct for partial volume effects in tissues near plaques.

Materials and Methods: Forty eight patients with Clinically Definite MS (CDMS), and 18 normal control subjects (NC) were included retrospectively from several MRS studies. T1, T2, and proton density MRI, and four white matter 1H MRS single voxel PRESS (Point-REsolved SpectroScopy) spectra were acquired in each subject using echo time 35 ms and repetition time 6000 ms on a 1.5 T MR-scanner. A total of 108 examinations were acquired from patients and 18 from NC. Absolutely quantified NAWM metabolite concentrations were determined using a mixed linear model (MLM) analysis that included the degree of T2 lesion contamination in each voxel. The T2 lesion contamination of the MRS voxels was also used as an estimate of ‘lesion load’ at each exam. The corrected metabolite concentrations were then correlated with clinical measures of the patients’ status, including EDSS and MSSS.

Results: The axonal marker N-acetyl aspartate (NAA) did not correlate with either EDSS or MSSS. The glial cell markers creatine and myo-inositol correlated positively with EDSS. Creatine and glutamate correlated positively with MSSS. The ‘estimated lesion load’ correlated positively not only with EDSS, but also with the number of bouts since disease onset. Importantly, it did not correlate with MSSS.

Conclusion: The most interesting findings were the unchanged concentrations of NAA, and the concomitant increase of creatine and myo-inositol during the course of disease progression in MSpatients. These not only indicated a constant axonal density, but also that a simultaneous development of gliosis occurred. These processes are most likely linked to demyelination, as well as development of white matter atrophy, a process in which the demyelinated volume is replaced by the surrounding tissue leading to a net loss of white matter. As a consequence of this process, axons in NAWM are probably damaged, which leads to a higher concentration of glia cells relative to the axonal volume. The positive correlation that was found between MSSS, and the glutamate and creatine concentrations in NAWM, in combination with a complete lack of correlation between lesion load and MSSS, suggests that altered glutamate metabolism, and subsequent demyelination and gliosis, is an important pathophysiological mechanism in MS.

There is an increasing demand for imaging methods that can be used for automatic, accurate and quantitative determination of the amounts of abdominal fat. Such methods are important as they will allow the evaluation of some of the risk factors underlying the ’metabolic syndrome’. The metabolic syndrome is becoming common in large parts of the world, and it appears that a dominant risk factor for developing this syndrome is abdominal obesity. Subjects that are afflicted with the metabolic syndrome are exposed to a high risk for developing a large range of diseases such as type 2 diabetes, cardiac failure, and stroke. The aim of this work

PURPOSE

To describe the distribution of MRI-derived body composition measurements in subjects with cardiovascular disease (CVD) compared to subjects without any history of CVD.

METHOD AND MATERIALS

1864 males and 2036 females with an age range from 45 to 78 years from the UK Biobank imaging study were included in the study. Visceral adipose tissue volume normalized with height² (VATi), total abdominal adipose tissue volume normalized with height² (ATATi), total lean thigh muscle volume normalized with body weight (muscle ratio) and liver proton density fat fraction (PDFF) were measured with a 2-point Dixon imaging protocol covering neck to knee and a 10-point Dixon single slice protocol positioned within the liver using a 1.5T MR-scanner (Siemens, Germany). The MR-images were analyzed using AMRA® Profiler research (AMRA, Sweden). 213 subjects with history of cardiovascular events (angina, heart attack, or stroke) (event group) were age and gender matched to subjects with high blood pressure (HBP group), and subjects without CVD (controls).Kruskal-Wallis and Mann-Whitney U tests were used to test the observed differences for each measurement and group without correction for multiple comparisons.

RESULTS

VATi in the event group was 1.73 (1.13 - 2.32) l/m² (median, 25%-75% percentile) compared to 1.68 (1.19 - 2.23) in the HBP group, and 1.30 (0.82-1.87) in the controls. ATATi in the event group was 4.31 (2.90-5.39) l/m² compared to 4.05 (3.07-5.12) in the HBP group, and 3.48 (2.48-4.61) in the controls. Muscle ratio in the event group was 0.13 (0.12 - 0.15) l/kg as well as in the HBP group, compared to 0.14 (0.12 - 0.15) in the controls. Liver PDFF in the event group was 2.88 (1.77 - 7.72) % compared to 3.44 (2.04-6.18) in the HBP group, and 2.50 (1.58 - 5.15) in the controls. Kruskal-Wallis test showed significant differences for all variables and group comparisons (p<0.007). The post hoc test showed significant differences comparing the controls to both the event group and the HBP group. These were more significant for VATi and ATATi (p<10-4) than for muscle ratio and PDFF (p<0.03). No significant differences were detected between the event group and the HBP group.

CONCLUSION

Cardiovascular disease is strongly associated with high VATi, liver fat, and ATATi, and with low muscle ratio.

CLINICAL RELEVANCE/APPLICATION

The metabolic syndrome component in CVD can be effectively described using MRI-based body composition profiling.

PURPOSE

To describe the distribution of MRI derived body composition measurements in subjects with diabetes mellitus (DM) compared to subjects without diabetes.

METHOD AND MATERIALS

3900 subjects (1864 males and 2036 females) from the UK Biobank imaging study were included in the study. The age range was 45 to 78 years. Visceral adipose tissue volume normalized with height² (VATi), total abdominal adipose tissue volume normalized with height² (ATATi), total lean thigh muscle volume normalized with body weight (muscle ratio) and liver proton density fat fraction (PDFF) were measured with a 6 minutes 2-point Dixon imaging protocol covering neck to knee and a 10-point Dixon single axial slice protocol positioned within the liver using a 1.5T MR-scanner (Siemens, Germany). The MR-images were analyzed using AMRA® Profiler research (AMRA, Sweden). 194 subjects with clinically diagnosed DM (DM group) were age and gender matched to subjects without DM (control group). For each variable and group, the median, 25%-percentile and 75%-percentile was calculated. Mann-Whitney U test was used to test the observed differences.

RESULTS

VATi in the DM group was 2.13 (1.43-2.62) l/m² (median, 25% - 75% percentile) compared to 1.32 (0.86 - 1.79) l/m² in the control group. ATATi in the DM group was 4.94 (3.86-6.19) l/m² compared to 3.40 (2.56 - 4.70) l/m² in the control group. Muscle ratio in the DM group was 0.13 (0.11 - 0.14) l/kg compared to 0.14 (0.12 - 0.15) l/kg in the control group. Liver PDFF in the DM group was 7.23 (2.68 - 13.26) % compared to 2.49 (1.53 - 4.73) % in the control group. Mann-Whitney U test detected significant differences between the DM group and the control group for all variables (p<10-5).

CONCLUSION

DM is strongly associated with high visceral fat, liver fat, and total abdominal fat, and low muscle ratio.

CLINICAL RELEVANCE/APPLICATION

Body composition profiling shows high potential to provide direct biomarkers to improve characterization and early diagnosis of DM.

Background: Different regional depots of fat have distinct metabolic properties and may relate differently to adverse cardiac remodeling. We sought to quantify regional depots of body fat and to investigate their relationship to cardiac structure and function in Type 2 Diabetes (T2D) and controls.

Methods: From the SCAPIS cohort in Linköping, Sweden, we recruited 92 subjects (35% female, mean age 59.5 ± 4.6 years): 46 with T2D and 46 matched controls. In addition to the core SCAPIS data collection, participants underwent a comprehensive magnetic resonance imaging examination at 1.5 T for assessment of left ventricular (LV) structure and function (end-diastolic volume, mass, concentricity, ejection fraction), as well as regional body composition (liver proton density fat fraction, visceral adipose tissue, abdominal subcutaneous adipose tissue, thigh muscle fat infiltration, fat tissue-free thigh muscle volume and epicardial adipose tissue).

Results: Compared to the control group, the T2D group had increased: visceral adipose tissue volume index (P < 0.001), liver fat percentage (P < 0.001), thigh muscle fat infiltration percentage (P = 0.02), LV concentricity (P < 0.001) and LV E/e'-ratio (P < 0.001). In a multiple linear regression analysis, a negative association between liver fat percentage and LV mass (St Beta -0.23, P < 0.05) as well as LV end-diastolic volume (St Beta -0.27, P < 0.05) was found. Epicardial adipose tissue volume and abdominal subcutaneous adipose tissue volume index were the only parameters of fat associated with LV diastolic dysfunction (E/e'-ratio) (St Beta 0.24, P < 0.05; St Beta 0.34, P < 0.01, respectively). In a multivariate logistic regression analysis, only visceral adipose tissue volume index was significantly associated with T2D, with an odds ratio for T2D of 3.01 (95% CI 1.28-7.05, P < 0.05) per L/m² increase in visceral adipose tissue volume.

Conclusions: Ectopic fat is predominantly associated with cardiac remodeling, independently of type 2 diabetes. Intriguingly, liver fat appears to be related to LV structure independently of VAT, while epicardial fat is linked to impaired LV diastolic function. Visceral fat is associated with T2D independently of liver fat and abdominal subcutaneous adipose tissue.

We prospectively studied the effects of fast food-based hyperalimentation on insulin sensitivity and components of the metabolic syndrome and analyzed this with respect to sex. Twelve nonobese men and 6 nonobese women (26 +/- 6.6 years old), and an age-matched control group were recruited. Subjects in the intervention group aimed for 5% to 15% weight increase by doubling their regular caloric intake based on at least 2 fast food meals a day while also adopting a sedentary lifestyle for 4 weeks (andlt;5000 steps a day). Weight of Subjects in the intervention group increased from 67.6 +/- 9.1 to 74.0 +/- 11 kg (P andlt;.001), with no sex difference with regard to this or with respect to changes of total abdominal fat volumes or waist circumferences. Fasting insulin (men: before, 3.8 +/- 1.7 mu U/mL, after, 7.4 +/- 3.1 mu U/mL; P=.004; women: before, 4.9 +/- 2.3 mu U/mL; after, 5.9 +/- 2.8 mu U/mL; P =.17), systolic blood pressure (men: before, 117 +/- 13 mm Hg; after, 127 +/- 9.1 mm Hg; P =.002; women: before, 102 +/- 5.1 mm Hg; after, 98 +/- 5.4 mm Hg; P =.39), serum low-density lipoprotein cholesterol, and apolipoprotein B increased only in the men of the intervention group. The sex differences in the metabolic responses to the intervention were linked to a considerable difference in the fat accumulation pattern; 41.4% +/- 9.2% of the increase of the fat volume in the abdominal region was accumulated intraabdominally in men and 22.7 +/- 6.5% in women (P andlt;.0001). This Study thus showed that women are protected, compared with men, against developing intraabdominal obesity when adopting a standardized obesity-provoking lifestyle. Our findings suggest that it is not different lifestyles and/or behaviors that underlie the fact that men have a higher cardiovascular risk at the same level of percentage of body fat than women.