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- Abbott, Rebecca, et al.
(författare)
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The qualitative grading of muscle fat infiltration in whiplash using fat and water magnetic resonance imaging
- 2018
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Ingår i: The spine journal. - : ELSEVIER SCIENCE INC. - 1529-9430 .- 1878-1632. ; 18:5, s. 717-725
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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- Borga, Magnus, 1965-, et al.
(författare)
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Advanced body composition assessment: From body mass index to body composition profiling
- 2018
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Ingår i: Journal of Investigative Medicine. - : BMJ Publishing Group Ltd. - 1081-5589 .- 1708-8267. ; 66:5, s. 887-895
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Forskningsöversikt (refereegranskat)abstract
- 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.
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| 3. |
- Karlsson, Anette, 1986-
(författare)
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Quantitative Muscle Composition Analysis Using Magnetic Resonance Imaging
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Changes in muscle tissue composition, e.g. decrease in volume and/or increase of fat infiltration, are related to adverse health conditions such as sarcopenia, inflammation, muscular dystrophy, and chronic pain. However, the onset and progression of disease and the effect of potential intervention effects are not fully understood, partly due to insufficient measurement tools. For advanced knowledge regarding these diseases, an accurate and precise measurement tool for detecting changes in muscle composition is needed. The tool must be able to detect both local changes on specific muscles for investigating local injuries and generalized muscle composition changes on a whole-body level. Magnetic resonance imaging is an excellent tool due to its superior soft tissue contrast but is normally not quantitative, making it challenging to produce reproducible results. Furthermore, manual analysis of the vast amount of images produced is extremely time consuming and therefore expensive. The aim of this thesis was to develop and validate a new magnetic resonance imaging method for muscle volume quantification and fat infiltration estimation that would have the potential to be used in both large-scale studies and for analyzing small individual muscles.The method development was divided into four main steps: 1) Rapid acquisition and reconstruction of data with sufficient resolution and calibration giving quantitative images where the relative fat content of each voxel (related to pure fat voxels) is attainable; 2) Automated muscle tissue classification based on non-rigid multi-atlas segmentation followed by probability voting to acquire the region of interest for each muscle; 3) Quantification of muscle tissue volume and fat infiltration from the classification step and the local fat signal; 4) Evaluation of the potential of the method in clinical studies.In Paper I, a method for automatic muscle volume quantification of both whole-body and regional muscles, i.e. involving steps 1–3, is presented. The automated method showed good agreement compared to manual segmentation. It was robust to an 8-fold resolution difference using two different scanner field strengths. Papers II and III evaluated the clinical relevance and the need for developing methods with high-resolution images to answer the research questions regarding the effect of a whiplash trauma on the multifidus muscles. This involved steps 1–4. The method enabled acquisition of high-resolution data to distinguish the small multifidus muscles (Paper II). The paper also showed a higher fat infiltration in the multifidus muscles in individuals with severe self-reported disability compared to individuals with milder symptoms and to healthy controls. Furthermore, the local fat infiltration was also related to widespread muscle fat infiltration (Paper III). However, the difference in widespread muscle fat infiltration could not alone distinguish between the three different groups. Paper IV showed the robustness of fat infiltration estimation when changing flip angle, and thereby the T1 weighting, of the acquired images (steps 1–3). The higher flip angle also provided better noise characteristics. Therefore, this quantitative method can be used with higher flip angle, and thus a potentially better anatomical contrast, without losing accuracy or precision.To conclude, this thesis presents a method that quantifies muscle volume and estimates fat infiltration robustly and reproducibly. The versatility of the method allows for both high-resolution images of small muscles and rapid acquisition of whole-body data. The method can be a useful tool in clinical studies regarding small individual muscles. Furthermore, the combination of being quantitative and automatic means that the method has potential to be used in longitudinal, multi-center, and large-scale studies for advanced understanding of muscular diseases.
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| 4. |
- Karlsson, Anette, 1986-, et al.
(författare)
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The effect on precision and T1 bias comparing two flip angles when estimating muscle fat infiltration using fat-referenced chemical shift-encoded imaging
- 2021
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Ingår i: NMR in Biomedicine. - : John Wiley & Sons. - 0952-3480 .- 1099-1492. ; 34:11
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Tidskriftsartikel (refereegranskat)abstract
- Investigation of the effect on accuracy and precision of different parameter settings is important for quantitative Magnetic Resonance Imaging. The purpose of this study was to investigate T1-bias and precision for muscle fat infiltration (MFI) using fat-referenced chemical shift magnetic resonance imaging at 5° and 10° flip angle. This [MB1] experimental study was done on forty postmenopausal women using 3T MRI test and retest images using 4-point 3D spoiled gradient multi-echo acquisition including real and imaginary images for reconstruction acquired at Flip angles 5° and 10°. Post-processing included T2* correction and fat-referenced calibration of the fat signal. The mean MFI was calculated in six different automatically segmented muscle regions using both the fat-referenced fat signal and the fat fraction calculated from the fat and water image pair for each acquisition. The variance of the difference between mean MFI from test and retest was used as measure of precision. The SNR characteristics were analyzed by measuring difference of the full width half maximum of the fat signal distribution using Student’s t-test.There was no difference in the mean fat-referenced MFI at different flip angles with the fat-referenced technique, which was the case using the fat fraction. No significant difference in the precision was found in any of the muscles analyzed. However, the full width half maximum of the fat signal distribution was significantly lower at 10° flip angle compared to 5°. Fat-referenced MFI is insensitive to T1 bias in chemical shift magnetic resonance imaging enabling usage of a higher and more SNR effective flip angle. The lower full-width-at half-maximum in fat-referenced MFI at 10° indicates that high flip angle acquisition is advantageous although no significant differences in precision was observed comparing 5° and 10°.
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| 5. |
- Linge, Jennifer, et al.
(författare)
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Body Composition Profiling in the UK Biobank Imaging Study
- 2018
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Ingår i: Obesity. - : WILEY. - 1930-7381 .- 1930-739X. ; 26:11, s. 1785-1795
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Tidskriftsartikel (refereegranskat)abstract
- ObjectiveMethodsThis 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. 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. ResultsConclusionsMatched control analysis showed that higher VAT and MFI were associated with CHD and T2D (Pamp;lt;0.001). Higher liver fat was associated with T2D (Pamp;lt;0.001) and lower liver fat with CHD (Pamp;lt;0.05), matching on VAT. Multivariable modeling showed that lower VAT and MFI were associated with metabolic health (Pamp;lt;0.001), and liver fat was nonsignificant. Associations remained significant adjusting for sex, age, BMI, alcohol, smoking, and physical activity. 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.
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| 17. |
- West, Janne, 1982-, et al.
(författare)
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Application of Quantitative MRI for Brain Tissue Segmentation at 1.5 T and 3.0 T Field Strengths
- 2013
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Ingår i: PLOS ONE. - United States : Public Library of Science. - 1932-6203. ; 8:9
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundBrain 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.MethodsIn 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.ResultsStatistically 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.ConclusionsMost of the brain was identically classified at the two field strengths, although some regional differences were observed.
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| 19. |
- West, Janne, 1982-, et al.
(författare)
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Novel whole brain segmentation and volume estimation using quantitative MRI
- 2012
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Ingår i: European Radiology. - : Springer. - 0938-7994 .- 1432-1084. ; 22:5, s. 998-1007
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVES: Brain segmentation and volume estimation of grey matter (GM), white matter (WM) and cerebro-spinal fluid (CSF) are important for many neurological applications. Volumetric changes are observed in multiple sclerosis (MS), Alzheimer's disease and dementia, and in normal aging. A novel method is presented to segment brain tissue based on quantitative magnetic resonance imaging (qMRI) of the longitudinal relaxation rate R(1), the transverse relaxation rate R(2) and the proton density, PD. METHODS: Previously reported qMRI values for WM, GM and CSF were used to define tissues and a Bloch simulation performed to investigate R(1), R(2) and PD for tissue mixtures in the presence of noise. Based on the simulations a lookup grid was constructed to relate tissue partial volume to the R(1)-R(2)-PD space. The method was validated in 10 healthy subjects. MRI data were acquired using six resolutions and three geometries. RESULTS: Repeatability for different resolutions was 3.2% for WM, 3.2% for GM, 1.0% for CSF and 2.2% for total brain volume. Repeatability for different geometries was 8.5% for WM, 9.4% for GM, 2.4% for CSF and 2.4% for total brain volume. CONCLUSION: We propose a new robust qMRI-based approach which we demonstrate in a patient with MS. KEY POINTS : • A method for segmenting the brain and estimating tissue volume is presented • This method measures white matter, grey matter, cerebrospinal fluid and remaining tissue • The method calculates tissue fractions in voxel, thus accounting for partial volume • Repeatability was 2.2% for total brain volume with imaging resolution <2.0 mm.
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| 20. |
- West, Janne, 1982-, et al.
(författare)
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Precision of MRI-based body composition measurements of postmenopausal women
- 2018
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Ingår i: PLOS ONE. - San Francisco, United States : Public Library of Science. - 1932-6203. ; 13:2
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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