Search

Investigation of the effect on accuracy and precision of different parameter settings is important for quantitative MRI. The purpose of this study was to investigate T1 bias and precision for muscle fat infiltration (MFI) measurements using fat‐referenced chemical shift MFI measurements at flip angles of 5° and 10°. The fat‐referenced measurements were compared with fat fractions, which is a more commonly used measure of MFI. This retrospective study was performed on data from a clinical intervention study including 40 postmenopausal women. Test and retest images were acquired with a 3‐T scanner using four‐point 3D spoiled gradient multiecho acquisition. Postprocessing included T2* correction and fat‐referenced calibration, where the fat signal was calibrated using adipose tissue as reference. The mean MFI was calculated in six different muscle regions using both the fat‐referenced fat signal and the fat fraction, defined as the fat signal divided by the sum of the fat and water signals. Both methods used the same fat and water images as input. The variance of the difference between mean MFI from test and retest was used as the measure of precision. The signal‐to‐noise ratio (SNR) characteristics were analyzed by measuring the full width at half maximum (FWHM) of the fat signal distribution. There was no difference in the mean MFI at different flip angles for the fat‐referenced technique (p = 0.66), while the measured fat fractions were 3.3 percentage points larger for 10° compared with 5° (p < 0.001). No significant difference in the precision was found in any of the muscles analyzed. However, the FWHM of the fat signal distribution was significantly (p = 0.01) lower at 10°. This strenghtens the hypothesis that fat‐referenced MFI is insensitive to flip angle‐induced T1 bias in CSE‐MRI, enabling usage of a higher and more SNR‐effective flip angle. The lower FWHM in fat‐referenced MFI at 10° indicates that high flip angle acquisition is advantageous even although no significant differences in precision were observed comparing 5° and 10°. [ABSTRACT FROM AUTHOR]

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 vendor's 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. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to investigate the value of imaging-based multivariable body composition profiling by describing its association with coronary heart disease (CHD), type 2 diabetes (T2D), and metabolic health on individual and population levels.Methods: The first 6,021 participants scanned by UK Biobank were included. Body composition profiles (BCPs) were calculated, including abdominal subcutaneous adipose tissue, visceral adipose tissue (VAT), thigh muscle volume, liver fat, and muscle fat infiltration (MFI), determined using magnetic resonance imaging. Associations between BCP and metabolic status were investigated using matching procedures and multivariable statistical modeling.Results: Matched control analysis showed that higher VAT and MFI were associated with CHD and T2D (P < 0.001). Higher liver fat was associated with T2D (P < 0.001) and lower liver fat with CHD (P < 0.05), matching on VAT. Multivariable modeling showed that lower VAT and MFI were associated with metabolic health (P < 0.001), and liver fat was nonsignificant. Associations remained significant adjusting for sex, age, BMI, alcohol, smoking, and physical activity.Conclusions: Body composition profiling enabled an intuitive visualization of body composition and showed the complexity of associations between fat distribution and metabolic status, stressing the importance of a multivariable approach. Different diseases were linked to different BCPs, which could not be described by a single fat compartment alone. [ABSTRACT FROM AUTHOR]

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 MRI. Earlier published studies of this method are summarized, and a previously unpublished validation study, based on 4753 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 MRIs show excellent agreement with linear correlation of 0.99 and 0.97, and coefficient of variation (CV) of 4.5 and 4.6 per cent for fat (computed from AT) and LT, respectively, but the agreement was found significantly lower for visceral adipose tissue, with a CV of >20 per cent. 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, makes quantitative MRI a powerful tool for advanced body composition assessment. [ABSTRACT FROM AUTHOR]

Objectives: To determine precision of magnetic resonance imaging (MRI) based fat and muscle quantification in a group of postmenopausal women. Furthermore, to extend the method to individual muscles relevant to upper-body exercise. Materials and methods: This was a sub-study to a randomized control trial investigating effects of resistance training to decrease hot flushes in postmenopausal women. Thirty-six women were included, mean age 56 ± 6 years. Each subject was scanned twice with a 3.0T MR-scanner using a whole-body Dixon protocol. Water and fat images were calculated using a 6-peak lipid model including R2*-correction. Body composition analyses were performed to measure visceral and subcutaneous fat volumes, lean volumes and muscle fat infiltration (MFI) of the muscle groups’ thigh muscles, lower leg muscles, and abdominal muscles, as well as the three individual muscles pectoralis, latissimus, and rhomboideus. Analysis was performed using a multi-atlas, calibrated water-fat separated quantification method. Liver-fat was measured as average proton density fat-fraction (PDFF) of three regions-of-interest. Precision was determined with Bland-Altman analysis, repeatability, and coefficient of variation. Results: All of the 36 included women were successfully scanned and analysed. The coefficient of variation was 1.1% to 1.5% for abdominal fat compartments (visceral and subcutaneous), 0.8% to 1.9% for volumes of muscle groups (thigh, lower leg, and abdomen), and 2.3% to 7.0% for individual muscle volumes (pectoralis, latissimus, and rhomboideus). Limits of agreement for MFI was within ± 2.06% for muscle groups and within ± 5.13% for individual muscles. The limits of agreement for liver PDFF was within ± 1.9%. Conclusion: Whole-body Dixon MRI could characterize a range of different fat and muscle compartments with high precision, including individual muscles, in the study-group of postmenopausal women. The inclusion of individual muscles, calculated from the same scan, enables analysis for specific intervention programs and studies. [ABSTRACT FROM AUTHOR]

STUDY DESIGN: Cross-sectional study. BACKGROUND: Findings of fat infiltration in cervical spine multifidus, as a sign of degenerative morphometric changes due to whiplash injury, need to be verified. OBJECTIVES: To develop a method using water/fat magnetic resonance imaging (MRI) to investigate fat infiltration and cross-sectional area of multifidus muscle in individuals with whiplash-associated disorders (WADs) compared to healthy controls. METHODS: Fat infiltration and cross-sectional area in the multifidus muscles spanning the C4 to C7 segmental levels were investigated by manual segmentation using water/fat-separated MRI in 31 participants with WAD and 31 controls, matched for age and sex. RESULTS: Based on average values for data spanning C4 to C7, participants with severe disability related to WAD had 38% greater muscular fat infiltration compared to healthy controls (P = .03) and 45% greater fat infiltration compared to those with mild to moderate disability related to WAD (P = .02). There were no significant differences between those with mild to moderate disability and healthy controls. No significant differences between groups were found for multifidus cross-sectional area. Significant differences were observed for both cross-sectional area and fat infiltration between segmental levels. TCONCLUSION: Participants with severe disability after a whiplash injury had higher fat infiltration in the multifidus compared to controls and to those with mild/moderate disability secondary to WAD. Earlier reported findings using T1-weighted MRI were reproduced using refined imaging technology. The results of the study also indicate a risk when segmenting single cross-sectional slices, as both cross-sectional area and fat infiltration differ between cervical levels. [ABSTRACT FROM AUTHOR]

Introduction: Quantitative and accurate measurements of fat and muscle in the body are important for prevention and diagnosis of diseases related to obesity and muscle degeneration. Manually segmenting muscle and fat compartments in MR body-images is laborious and time-consuming, hindering implementation in large cohorts. In the present study, the feasibility and success-rate of a Dixon-based MR scan followed by an intensity-normalised, non-rigid, multi-atlas based segmentation was investigated in a cohort of 3,000 subjects. Materials and Methods: 3,000 participants in the in-depth phenotyping arm of the UK Biobank imaging study underwent a comprehensive MR examination. All subjects were scanned using a 1.5 T MR-scanner with the dual-echo Dixon Vibe protocol, covering neck to knees. Subjects were scanned with six slabs in supine position, without localizer. Automated body composition analysis was performed using the AMRA Profiler™ system, to segment and quantify visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (ASAT) and thigh muscles. Technical quality assurance was performed and a standard set of acceptance/rejection criteria was established. Descriptive statistics were calculated for all volume measurements and quality assurance metrics. Results: Of the 3,000 subjects, 2,995 (99.83%) were analysable for body fat, 2,828 (94.27%) were analysable when body fat and one thigh was included, and 2,775 (92.50%) were fully analysable for body fat and both thigh muscles. Reasons for not being able to analyse datasets were mainly due to missing slabs in the acquisition, or patient positioned so that large parts of the volume was outside of the field-of-view. Discussion and Conclusions: In conclusion, this study showed that the rapid UK Biobank MR-protocol was well tolerated by most subjects and sufficiently robust to achieve very high success-rate for body composition analysis. This research has been conducted using the UK Biobank Resource. [ABSTRACT FROM AUTHOR]

Introduction: Magnetic Resonance Imaging is a sensitive technique for detecting white matter (WM) MS lesions, but the relation with clinical disability is low. Because of this, changes in both ‘normal appearing white matter’ (NAWM) and ‘diffusely abnormal white matter’ (DAWM) have been of interest in recent years. MR techniques, including quantitative magnetic resonance imaging (qMRI) and quantitative magnetic resonance spectroscopy (qMRS), have been developed in order to detect and quantify such changes. In this study, qMRI and qMRS were used to investigate NAWM and DAWM in typical MS patients and in MS patients with low number of WM lesions. Patient data were compared to ‘normal white matter’ (NWM) in healthy controls. Methods: QMRI and qMRS measurements were performed on a 1.5 T Philips MR-scanner. 35 patients with clinically definite MS and 20 healthy controls were included. Twenty of the patients fulfilled the ‘Barkhof-Tintoré criteria’ for MS, (‘MRIpos’), whereas 15 showed radiologically atypical findings with few WM lesions (‘MRIneg’). QMRI properties were determined in ROIs of NAWM, DAWM and lesions in the MS groups and of NWM in controls. Descriptive statistical analysis and comparisons were performed. Correlations were calculated between qMRI measurements and (1) clinical parameters and (2) WM metabolite concentrations. Regression analyses were performed with brain parenchyma fraction and MSSS. Results: NAWM in the MRIneg group was significantly different from NAWM in the MRIpos group and NWM. In addition, R1 and R2 of NAWM in the MRIpos group correlated negatively with EDSS and MSSS. DAWM was significantly different from NWM, but similar in the MS groups. N-acetyl aspartate correlated negatively with R1 and R2 in MRIneg. R2 of DAWM was associated with BPF. Conclusions: Changes in NAWM and DAWM are independent pathological entities in the disease. The correlation between qMRI and clinical status may shed new light on the clinicoradiological paradox. [ABSTRACT FROM AUTHOR]

Background:Brain tissue segmentation of white matter (WM), grey matter (GM), and cerebrospinal fluid (CSF) are important in neuroradiological applications. Quantitative Mri (qMRI) allows segmentation based on physical tissue properties, and the dependencies on MR scanner settings are removed. Brain tissue groups into clusters in the three dimensional space formed by the qMRI parameters R1, R2 and PD, and partial volume voxels are intermediate in this space. The qMRI parameters, however, depend on the main magnetic field strength. Therefore, longitudinal studies can be seriously limited by system upgrades. The aim of this work was to apply one recently described brain tissue segmentation method, based on qMRI, at both 1.5 T and 3.0 T field strengths, and to investigate similarities and differences. Methods:In vivo qMRI measurements were performed on 10 healthy subjects using both 1.5 T and 3.0 T MR scanners. The brain tissue segmentation method was applied for both 1.5 T and 3.0 T and volumes of WM, GM, CSF and brain parenchymal fraction (BPF) were calculated on both field strengths. Repeatability was calculated for each scanner and a General Linear Model was used to examine the effect of field strength. Voxel-wise t-tests were also performed to evaluate regional differences. Results:Statistically significant differences were found between 1.5 T and 3.0 T for WM, GM, CSF and BPF (p<0.001). Analyses of main effects showed that WM was underestimated, while GM and CSF were overestimated on 1.5 T compared to 3.0 T. The mean differences between 1.5 T and 3.0 T were -66 mL WM, 40 mL GM, 29 mL CSF and -1.99% BPF. Voxel-wise t-tests revealed regional differences of WM and GM in deep brain structures, cerebellum and brain stem. Conclusions:Most of the brain was identically classified at the two field strengths, although some regional differences were observed. [ABSTRACT FROM AUTHOR]

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 MRI. Earlier published studies of this method are summarized, and a previously unpublished validation study, based on 4753 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 MRIs show excellent agreement with linear correlation of 0.99 and 0.97, and coefficient of variation (CV) of 4.5 and 4.6 per cent for fat (computed from AT) and LT, respectively, but the agreement was found significantly lower for visceral adipose tissue, with a CV of >20 per cent. 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, makes quantitative MRI a powerful tool for advanced body composition assessment., Competing Interests: Competing interests: MB, JW, TR and ODL are employees and stockholders of AMRA Medical AB., (© American Federation for Medical Research (unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)