| 1. |
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| 2. |
- Ahmad, Nouman, et al.
(author)
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Automatic segmentation of large-scale CT image datasets for detailed body composition analysis
- 2023
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In: BMC BIOINFORMATICS. - : BioMed Central (BMC). - 1471-2105. ; 24:1
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Journal article (peer-reviewed)abstract
- BackgroundBody composition (BC) is an important factor in determining the risk of type 2-diabetes and cardiovascular disease. Computed tomography (CT) is a useful imaging technique for studying BC, however manual segmentation of CT images is time-consuming and subjective. The purpose of this study is to develop and evaluate fully automated segmentation techniques applicable to a 3-slice CT imaging protocol, consisting of single slices at the level of the liver, abdomen, and thigh, allowing detailed analysis of numerous tissues and organs.MethodsThe study used more than 4000 CT subjects acquired from the large-scale SCAPIS and IGT cohort to train and evaluate four convolutional neural network based architectures: ResUNET, UNET++, Ghost-UNET, and the proposed Ghost-UNET++. The segmentation techniques were developed and evaluated for automated segmentation of the liver, spleen, skeletal muscle, bone marrow, cortical bone, and various adipose tissue depots, including visceral (VAT), intraperitoneal (IPAT), retroperitoneal (RPAT), subcutaneous (SAT), deep (DSAT), and superficial SAT (SSAT), as well as intermuscular adipose tissue (IMAT). The models were trained and validated for each target using tenfold cross-validation and test sets.ResultsThe Dice scores on cross validation in SCAPIS were: ResUNET 0.964 (0.909-0.996), UNET++ 0.981 (0.927-0.996), Ghost-UNET 0.961 (0.904-0.991), and Ghost-UNET++ 0.968 (0.910-0.994). All four models showed relatively strong results, however UNET++ had the best performance overall. Ghost-UNET++ performed competitively compared to UNET++ and showed a more computationally efficient approach.ConclusionFully automated segmentation techniques can be successfully applied to a 3-slice CT imaging protocol to analyze multiple tissues and organs related to BC. The overall best performance was achieved by UNET++, against which Ghost-UNET++ showed competitive results based on a more computationally efficient approach. The use of fully automated segmentation methods can reduce analysis time and provide objective results in large-scale studies of BC.
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| 3. |
- Ahmad, Nouman, et al.
(author)
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Voxel-wise body composition analysis using image registration of a three-slice CT imaging protocol : methodology and proof-of-concept studies
- 2024
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In: Biomedical engineering online. - : Springer Nature. - 1475-925X. ; 23:1
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Journal article (peer-reviewed)abstract
- Background Computed tomography (CT) is an imaging modality commonly used for studies of internal body structures and very useful for detailed studies of body composition. The aim of this study was to develop and evaluate a fully automatic image registration framework for inter-subject CT slice registration. The aim was also to use the results, in a set of proof-of-concept studies, for voxel-wise statistical body composition analysis (Imiomics) of correlations between imaging and non-imaging data.Methods The current study utilized three single-slice CT images of the liver, abdomen, and thigh from two large cohort studies, SCAPIS and IGT. The image registration method developed and evaluated used both CT images together with image-derived tissue and organ segmentation masks. To evaluate the performance of the registration method, a set of baseline 3-single-slice CT images (from 2780 subjects including 8285 slices) from the SCAPIS and IGT cohorts were registered. Vector magnitude and intensity magnitude error indicating inverse consistency were used for evaluation. Image registration results were further used for voxel-wise analysis of associations between the CT images (as represented by tissue volume from Hounsfield unit and Jacobian determinant) and various explicit measurements of various tissues, fat depots, and organs collected in both cohort studies.Results Our findings demonstrated that the key organs and anatomical structures were registered appropriately. The evaluation parameters of inverse consistency, such as vector magnitude and intensity magnitude error, were on average less than 3 mm and 50 Hounsfield units. The registration followed by Imiomics analysis enabled the examination of associations between various explicit measurements (liver, spleen, abdominal muscle, visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), thigh SAT, intermuscular adipose tissue (IMAT), and thigh muscle) and the voxel-wise image information.Conclusion The developed and evaluated framework allows accurate image registrations of the collected three single-slice CT images and enables detailed voxel-wise studies of associations between body composition and associated diseases and risk factors.
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| 4. |
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| 5. |
- Ahmed, Fozia, et al.
(author)
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ESR2 expression in subcutaneous adipose tissue is related to body fat distribution in women, and knockdown impairs preadipocyte differentiation
- 2022
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In: Adipocyte. - : Informa UK Limited. - 2162-3945 .- 2162-397X. ; 11:1, s. 434-447
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Journal article (peer-reviewed)abstract
- Oestrogen receptor 2 (ESR2) expression has been shown to be higher in subcutaneous adipose tissue (SAT) from postmenopausal compared to premenopausal women. The functional significance of altered ESR2 expression is not fully known. This study investigates the role of ESR2 for adipose tissue lipid and glucose metabolism. SAT biopsies were obtained from 44 female subjects with or without T2D. Gene expression of ESR2 and markers of adipose function and metabolism was assessed. ESR2 knockdown was performed using CRISPR/Cas9 in preadipocytes isolated from SAT of females, and differentiation rate, lipid storage, and glucose uptake were measured. ESR2 expression was inversely correlated with measures of central obesity and expression of some fatty acid oxidation markers, and positively correlated with lipid storage and glucose transport markers. Differentiation was reduced in ESR2 knockdown preadipocytes. This corresponded to reduced expression of markers of differentiation and lipogenesis. Glucose uptake was reduced in knockdown adipocytes. Our results indicate that ESR2 deficiency in women is associated with visceral adiposity and impaired subcutaneous adipocyte differentiation as well as glucose and lipid utilization. High ESR2 expression, as seen after menopause, could be a contributing factor to SAT expansion. This may support a possible target to promote a healthy obesity phenotype.
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| 6. |
- Alexanderson, Camilla, 1978, et al.
(author)
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A single early postnatal estradiol injection affects morphology and gene expression of the ovary and parametrial adipose tissue in adult female rats.
- 2010
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In: The Journal of steroid biochemistry and molecular biology. - : Elsevier BV. - 1879-1220 .- 0960-0760. ; 122:1-3, s. 82-90
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Journal article (peer-reviewed)abstract
- Events during early life can affect reproductive and metabolic functions in adulthood. We evaluated the programming effects of a single early postnatal estradiol injection (within 3h after birth) in female rats. We assessed ovarian and parametrial adipose tissue morphology, evaluated gene expression related to follicular development and adipose tissue metabolism, and developed a non-invasive volumetric estimation of parametrial adipose tissue by magnetic resonance imaging. Estradiol reduced ovarian weight, increased antral follicle size and number of atretic antral follicles, and decreased theca interna thickness in atretic antral follicles. Adult estradiol-injected rats also had malformed vaginal openings and lacked corpora lutea, confirming anovulation. Estradiol markedly reduced parametrial adipose tissue mass. Adipocyte size was unchanged, suggesting reduced adipocyte number. Parametrial adipose tissue lipoprotein lipase activity was increased. In ovaries, estradiol increased mRNA expression of adiponectin, complement component 3, estrogen receptor alpha, and glucose transporter 3 and 4; in parametrial adipose tissue, expression of complement component 3 was increased, expression of estrogen receptor alpha was decreased, and expression of leptin, lipoprotein lipase, and hormone-sensitive lipase was unaffected. These findings suggest that early postnatal estradiol exposure of female rats result in long-lasting effects on the ovary and parametrial adipose tissue at adult age.
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| 7. |
- Andersson, Jonathan, et al.
(author)
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Estimating the cold-induced brown adipose tissue glucose uptake rate measured by 18F-FDG PET using infrared thermography and water-fat separated MRI
- 2019
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In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9
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Journal article (peer-reviewed)abstract
- Brown adipose tissue (BAT) expends chemical energy to produce heat, which makes it a potential therapeutic target for combating metabolic dysfunction and overweight/obesity by increasing its metabolic activity. The most well-established method for measuring BAT metabolic activity is glucose uptake rate (GUR) measured using 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET). However, this is expensive and exposes the subjects to potentially harmful radiation. Cheaper and safer methods are warranted for large-scale or longitudinal studies. Potential alternatives include infrared thermography (IRT) and magnetic resonance imaging (MRI). The aim of this study was to evaluate and further develop these techniques. Twelve healthy adult subjects were studied. The BAT GUR was measured using 18F-FDG PET during individualized cooling. The temperatures of the supraclavicular fossae and a control region were measured using IRT during a simple cooling protocol. The fat fraction and effective transverse relaxation rate of BAT were measured using MRI without any cooling intervention. Simple and multiple linear regressions were employed to evaluate how well the MRI and IRT measurements could estimate the GUR. Results showed that both IRT and MRI measurements correlated with the GUR. This suggest that these measurements may be suitable for estimating the cold-induced BAT GUR in future studies.
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| 8. |
- Andersson, Jonathan, et al.
(author)
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MRI estimates of brown adipose tissue in children - Associations to adiposity, osteocalcin, and thigh muscle volume
- 2019
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In: Magnetic Resonance Imaging. - : Elsevier BV. - 0730-725X .- 1873-5894. ; 58, s. 135-142
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Journal article (peer-reviewed)abstract
- Context Brown adipose tissue is of metabolic interest. The tissue is however poorly explored in children. Methods: Sixty-three 7-year old subjects from the Swedish birth-cohort Halland Health and Growth Study were recruited. Care was taken to include both normal weight and overweight children, but the subjects were otherwise healthy. Only children born full term were included. Water-fat separated whole-body MRI scans, anthropometric measurements, and measurements of fasting glucose and levels of energy homeostasis related hormones, including the insulin-sensitizer osteocalcin, were performed. The fat fraction (FF) and effective transverse relaxation time (T-2(star)) of suspected brown adipose tissue in the cervical-supraclavicular-axillary fat depot (sBAT) and the FFs of abdominal visceral (VAT) and subcutaneous adipose tissue (SAT) were measured. Volumes of sBAT, abdominal VAT and SAT, and thigh muscle volumes were measured. Results: The FF in the sBAT depot was lower than in VAT and SAT for all children. In linear correlations including sex and age as explanatory variables, sBAT FF correlated positively with all measures of adiposity (p < 0.01), except for VAT FF and weight, positively with sBAT T-2* (p = 0.036), and negatively with osteocalcin (p = 0.017). When adding measures of adiposity as explanatory variables, sBAT FF also correlated negatively with thigh muscle volume (p < 0.01). Conclusions: Whole-body water-fat MRI of children allows for measurements of sBAT. The FF of sBAT was lower than that of VAT and SAT, indicating presence of BAT. Future studies could confirm whether the observed correlations corresponds to a hormonally active BAT.
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| 9. |
- Andersson, Jonathan, et al.
(author)
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Separation of water and fat signal in whole-body gradient echo scans using convolutional neural networks
- 2019
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In: Magnetic Resonance in Medicine. - : Wiley. - 0740-3194 .- 1522-2594. ; 82:3, s. 1177-1186
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Journal article (peer-reviewed)abstract
- Purpose: To perform and evaluate water–fat signal separation of whole‐body gradient echo scans using convolutional neural networks.Methods: Whole‐body gradient echo scans of 240 subjects, each consisting of 5 bipolar echoes, were used. Reference fat fraction maps were created using a conventional method. Convolutional neural networks, more specifically 2D U‐nets, were trained using 5‐fold cross‐validation with 1 or several echoes as input, using the squared difference between the output and the reference fat fraction maps as the loss function. The outputs of the networks were assessed by the loss function, measured liver fat fractions, and visually. Training was performed using a graphics processing unit (GPU). Inference was performed using the GPU as well as a central processing unit (CPU).Results: The loss curves indicated convergence, and the final loss of the validation data decreased when using more echoes as input. The liver fat fractions could be estimated using only 1 echo, but results were improved by use of more echoes. Visual assessment found the quality of the outputs of the networks to be similar to the reference even when using only 1 echo, with slight improvements when using more echoes. Training a network took at most 28.6 h. Inference time of a whole‐body scan took at most 3.7 s using the GPU and 5.8 min using the CPU.Conclusion: It is possible to perform water–fat signal separation of whole‐body gradient echo scans using convolutional neural networks. Separation was possible using only 1 echo, although using more echoes improved the results.
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| 10. |
- Andersson, Jonathan, et al.
(author)
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Water-fat separation incorporating spatial smoothing is robust to noise
- 2018
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In: Magnetic Resonance Imaging. - : Elsevier BV. - 0730-725X .- 1873-5894. ; 50, s. 78-83
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Journal article (peer-reviewed)abstract
- PURPOSE: To develop and evaluate a noise-robust method for reconstruction of water and fat images for spoiled gradient multi-echo sequences.METHODS: The proposed method performs water-fat separation by using a graph cut to minimize an energy function consisting of unary and binary terms. Spatial smoothing is incorporated to increase robustness to noise. The graph cut can fail to find a solution covering the entire image, in which case the relative weighting of the unary term is iteratively increased until a complete solution is found. The proposed method was compared to two previously published methods. Reconstructions were performed on 16 cases taken from the 2012 ISMRM water-fat reconstruction challenge dataset, for which reference reconstructions were provided. Robustness towards noise was evaluated by reconstructing images with different levels of noise added. The percentage of water-fat swaps were calculated to measure performance.RESULTS: At low noise levels the proposed method produced similar results to one of the previously published methods, while outperforming the other. The proposed method significantly outperformed both of the previously published methods at moderate and high noise levels.CONCLUSION: By incorporating spatial smoothing, an increased robustness towards noise is achieved when performing water-fat reconstruction of spoiled gradient multi-echo sequences.
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| 11. |
- Andersson, Jonathan
(author)
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Water–fat separation in magnetic resonance imaging and its application in studies of brown adipose tissue
- 2019
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Doctoral thesis (other academic/artistic)abstract
- Virtually all the magnetic resonance imaging (MRI) signal of a human originates from water and fat molecules. By utilizing the property chemical shift the signal can be separated, creating water- and fat-only images. From these images it is possible to calculate quantitative fat fraction (FF) images, where the value of each voxel is equal to the percentage of its signal originating from fat. In papers I and II methods for water–fat signal separation are presented and evaluated.The method in paper I utilizes a graph-cut to separate the signal and was designed to perform well even for a low signal-to-noise ratio (SNR). The method was shown to perform as well as previous methods at high SNRs, and better at low SNRs.The method presented in paper II uses convolutional neural networks to perform the signal separation. The method was shown to perform similarly to a previous method using a graph-cut when provided non-undersampled input data. Furthermore, the method was shown to be able to separate the signal using undersampled data. This may allow for accelerated MRI scans in the future.Brown adipose tissue (BAT) is a thermogenic organ with the main purpose of expending chemical energy to prevent the body temperature from falling too low. Its energy expending capability makes it a potential target for treating overweight/obesity and metabolic dysfunctions, such as type 2 diabetes. The most well-established way of estimating the metabolic potential of BAT is through measuring glucose uptake using 18F-fludeoxyglucose (18F-FDG) positron emission tomography (PET) during cooling. This technique exposes subjects to potentially harmful ionizing radiation, and alternative methods are desired. One alternative method is measuring the BAT FF using MRI.In paper III the BAT FF in 7-year olds was shown to be negatively associated with blood serum levels of the bone-specific protein osteocalcin and, after correction for adiposity, thigh muscle volume. This may have implications for how BAT interacts with both bone and muscle tissue.In paper IV the glucose uptake of BAT during cooling of adult humans was measured using 18F-FDG PET. Additionally, their BAT FF was measured using MRI, and their skin temperature during cooling near a major BAT depot was measured using infrared thermography (IRT). It was found that both the BAT FF and the temperature measured using IRT correlated with the BAT glucose uptake, meaning these measurements could be potential alternatives to 18F-FDG PET in future studies of BAT.
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| 12. |
- Andreou, Dimitrios, et al.
(author)
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Cardiac left ventricular ejection fraction in men and women with schizophrenia on long-term antipsychotic treatment
- 2020
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In: Schizophrenia Research. - : Elsevier BV. - 0920-9964 .- 1573-2509. ; 218, s. 226-232
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Journal article (peer-reviewed)abstract
- Patients with schizophrenia exhibit a higher cardiovascular mortality compared to the general population which has been attributed to life-style factors, genetic susceptibility and antipsychotic medication. Recent echocardiographic studies have pointed to an association between clozapine treatment and reduced left ventricular ejection fraction (LVEF), a measure that has been inversely associated with adverse outcomes including all-cause mortality. Cardiovascular magnetic resonance (CMR) is considered the reference method for LVEF measurement. The aim of the present study was to investigate the LVEF in patients with schizophrenia on long-term treatment with antipsychotics and healthy controls. Twenty-nine adult patients with schizophrenia on long-term medication with antipsychotics and 27 age-, sex- and body mass index-matched healthy controls (mean ages 44 and 45 years, respectively) were recruited from outpatient psychiatric clinics in Uppsala, Sweden. The participants were interviewed and underwent physical examination, biochemical analyses, electrocardiogram and CMR. Men with schizophrenia on long-term antipsychotic treatment showed significantly lower LVEF than controls (p = 0.0076), whereas no such difference was evident among women (p = 0.44). Specifically, clozapine-treated male patients had 10.6% lower LVEF than male controls (p = 0.0064), whereas the LVEF was 5.5% below that of controls among male patients treated with non-clozapine antipsychotics (p = 0.047). Among medicated men with schizophrenia, we found significantly lower LVEF compared to healthy individuals, suggesting the need of routine cardiac monitoring in this patient group. This is the first study showing a significant negative association between treatment with non-clozapine antipsychotics and LVEF.
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| 13. |
- Benedict, Christian, et al.
(author)
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Association between physical activity and brain health in older adults
- 2013
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In: Neurobiology of Aging. - : Elsevier BV. - 0197-4580 .- 1558-1497. ; 34:1, s. 83-90
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Journal article (peer-reviewed)abstract
- In the present cross-sectional study, we examined physical activity (PA) and its possible association with cognitive skills and brain structure in 331 cognitively healthy elderly. Based on the number of self-reported light and hard activities for at least 30 minutes per week, participants were assigned to 4 groups representing different levels of PA. The cognitive skills were assessed by the Mini Mental State Examination score, a verbal fluency task, and the Trail-making test as a measure of visuospatial orientation ability. Participants also underwent a magnetic resonance imaging of the brain. Multiple regression analysis revealed that greater PA was associated with a shorter time to complete the Trail-making test, and higher levels of verbal fluency. Further, the level of self-reported PA was positively correlated with brain volume, white matter, as well as a parietal lobe gray matter volume, situated bilaterally at the precuneus. These present cross-sectional results indicate that PA is a lifestyle factor that is linked to brain structure and function in late life.
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| 14. |
- Benedict, Christian, et al.
(author)
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Impaired Insulin Sensitivity as Indexed by the HOMA Score Is Associated With Deficits in Verbal Fluency and Temporal Lobe Gray Matter Volume in the Elderly
- 2012
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In: Diabetes Care. - : American Diabetes Association. - 0149-5992 .- 1935-5548. ; 35:3, s. 488-494
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Journal article (peer-reviewed)abstract
- OBJECTIVEImpaired insulin sensitivity is linked to cognitive deficits and reduced brain size. However, it is not yet known whether insulin sensitivity involves regional changes in gray matter volume. Against this background, we examined the association between insulin sensitivity, cognitive performance, and regional gray matter volume in 285 cognitively healthy elderly men and women aged 75 years from the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) study.RESEARCH DESIGN AND METHODSInsulin sensitivity was calculated from fasting serum insulin and plasma glucose determinations using the homeostasis model assessment of insulin resistance (HOMA-IR) method. Cognitive performance was examined by a categorical verbal fluency. Participants also underwent a magnetic resonance imaging (MRI) brain scan. Multivariate analysis using linear regression was conducted, controlling for potential confounders (sex, education, serum LDL cholesterol, mean arterial blood pressure, and abdominal visceral fat volume).RESULTSThe HOMA-IR was negatively correlated with verbal fluency performance, brain size (S1), and temporal lobe gray matter volume in regions known to be involved in speech production (Brodmann areas 21 and 22, respectively). No such effects were observed when examining diabetic (n = 55) and cognitively impaired (n = 27) elderly subjects as separate analyses.CONCLUSIONSThese cross-sectional findings suggest that both pharmacologic and lifestyle interventions improving insulin signaling may promote brain health in late life but must be confirmed in patient studies.
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| 15. |
- Berglund, Johan, et al.
(author)
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Model-based mapping of fat unsaturation and chain length by chemical shift imaging : phantom validation and in vivo feasibility
- 2012
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In: Magnetic Resonance in Medicine. - : Wiley. - 0740-3194 .- 1522-2594. ; 68:6, s. 1815-1827
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Journal article (peer-reviewed)abstract
- Knowledge about the triglyceride (fat) 1H spectrum enables quantitative determination of several triglyceride characteristics. This work describes a model-based chemical shift imaging method that separates water and fat signal and provides maps of three triglyceride quantities: fatty acid carbon chain length (CL), number of double bond pairs (ndb), and number of methylene-interrupted double bonds (nmidb). The method was validated by imaging a phantom containing ten different oils using 1.5 T and 3.0 T clinical scanners, with gas-liquid chromatography (GLC) as reference. Repeated acquisitions demonstrated high reproducibility of the method. Statistical tests of correlation and linear regression were performed to examine the accuracy of the method. Significant correlation was found at both field strengths for all three quantities, and high correlation (r2 > 0.96) was found for measuring ndb and nmidb. Feasibility of the method for in vivo imaging of the thigh was demonstrated at both field strengths. The estimates of ndb and nmidb in subcutaneous adipose tisse were in agreement with literature values, while CL appears overestimated. The method has potential use in large-scale cross-sectional and longitudinal studies of triglyceride composition, and its relation to diet and various diseases.
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| 16. |
- Berglund, Johan, 1983-
(author)
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Separation of Water and Fat Signal in Magnetic Resonance Imaging : Advances in Methods Based on Chemical Shift
- 2011
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Doctoral thesis (other academic/artistic)abstract
- Magnetic resonance imaging (MRI) is one of the most important diagnostic tools of modern healthcare. The signal in medical MRI predominantly originates from water and fat molecules. Separation of the two components into water-only and fat-only images can improve diagnosis, and is the premier non-invasive method for measuring the amount and distribution of fatty tissue. Fat-water imaging (FWI) enables fast fat/water separation by model-based estimation from chemical shift encoded data, such as multi-echo acquisitions. Qualitative FWI is sufficient for visual separation of the components, while quantitative FWI also offers reliable estimates of the fat percentage in each pixel. The major problems of current FWI methods are long acquisition times, long reconstruction times, and reconstruction errors that degrade image quality. In this thesis, existing FWI methods were reviewed, and novel fully automatic methods were developed and evaluated, with a focus on fast 3D image reconstruction. All MRI data was acquired on standard clinical scanners. A triple-echo qualitative FWI method was developed for the specific application of 3D whole-body imaging. The method was compared with two reference methods, and demonstrated superior image quality when evaluated in 39 volunteers. The problem of qualitative FWI by dual-echo data with unconstrained echo times was solved, allowing faster and more flexible image acquisition than conventional FWI. Feasibility of the method was demonstrated in three volunteers and the noise performance was evaluated. Further, a quantitative multi-echo FWI method was developed. The signal separation was based on discrete whole-image optimization. Fast 3D image reconstruction with few reconstruction errors was demonstrated by abdominal imaging of ten volunteers. Lastly, a method was proposed for quantitative mapping of average fatty acid chain length and degree of saturation. The method was validated by imaging different oils, using gas-liquid chromatography (GLC) as the reference. The degree of saturation agreed well with GLC, and feasibility of the method was demonstrated in the thigh of a volunteer. The developed methods have applications in clinical settings, and are already being used in several research projects, including studies of obesity, dietary intervention, and the metabolic syndrome.
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| 17. |
- Berglund, Johan, et al.
(author)
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Three-dimensional water/fat separation and T2* estimation based on whole-image optimization : application in breathhold liver imaging at 1.5 T
- 2012
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In: Magnetic Resonance in Medicine. - : Wiley. - 0740-3194 .- 1522-2594. ; 67:6, s. 1684-1693
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Journal article (peer-reviewed)abstract
- The chemical shift of water and fat resonances in proton MRI allows separation of water and fat signal from chemical shift encoded data. This work describes an automatic method that produces separate water and fat images as well as quantitative maps of fat signal fraction and T2* from complex multi-echo gradient recalled datasets. Accurate water and fat separation is challenging due to signal ambiguity at the voxel level. Whole-image optimization can resolve this ambiguity, but might be computationally demanding, especially for three-dimensional (3D) data. In this work, periodicity of the model fit residual as a function of the off-resonance was utilized to modify a previously proposed formulation of the problem. This gives a smaller solution space and allows rapid optimization. Feasibility and accurate separation of water and fat signal was demonstrated in breathhold 3D liver imaging of ten volunteer subjects, with both acquisition and reconstruction times below 20 seconds.
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| 18. |
- Berglund, Johan, et al.
(author)
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Three-point Dixon method enables whole-body water and fat imaging of obese subjects
- 2010
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In: Magnetic Resonance in Medicine. - : Wiley. - 0740-3194 .- 1522-2594. ; 63:6, s. 1659-1668
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Journal article (peer-reviewed)abstract
- Dixon imaging techniques derive chemical shift-separated water and fat images, enabling the quantification of fat content and forming an alternative to fat suppression. Whole-body Dixon imaging is of interest in studies of obesity and the metabolic syndrome, and possibly in oncology. A three-point Dixon method is proposed where two solutions are found analytically in each voxel. The true solution is identified by a multiseed three-dimensional region-growing scheme with a dynamic path, allowing confident regions to be solved before unconfident regions, such as background noise. 2 pi-Phase unwrapping is not required. Whole-body datasets (256 x 184 x 252 voxels) were collected from 39 subjects (body mass index 19.8-45.4 kg/m(2)), in a mean scan time of 5 min 15 sec. Water and fat images were reconstructed offline, using the proposed method and two reference methods. The resulting images were subjectively graded on a four-grade scale by two radiologists, blinded to the method used. The proposed method was found superior to the reference methods. It exclusively received the two highest grades, implying that only mild reconstruction failures were found. The computation time for a whole-body dataset was 1 min 51.5 sec +/- 3.0 sec. It was concluded that whole-body water and fat imaging is feasible even for obese subjects, using the proposed method.
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| 19. |
- Berglund, Johan, et al.
(author)
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Two-point dixon method with flexible echo times
- 2011
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In: Magnetic Resonance in Medicine. - : Wiley. - 0740-3194 .- 1522-2594. ; 65:4, s. 994-1004
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Journal article (peer-reviewed)abstract
- The two-point Dixon method is a proton chemical shift imaging technique that produces separated water-only and fat-only images from a dual-echo acquisition. It is shown how this can be achieved without the usual constraints on the echo times. A signal model considering spectral broadening of the fat peak is proposed for improved water/fat separation. Phase errors, mostly due to static field inhomogeneity, must be removed prior to least-squares estimation of water and fat. To resolve ambiguity of the phase errors, a corresponding global optimization problem is formulated and solved using a message-passing algorithm. It is shown that the noise in the water and fat estimates matches the Cramér-Rao bounds, and feasibility is demonstrated for in vivo abdominal breath-hold imaging. The water-only images were found to offer superior fat suppression compared with conventional spectrally fat suppressed images.
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| 20. |
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| 21. |
- Bjermo, Helena, et al.
(author)
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Effects of n-6 PUFAs compared with SFAs on liver fat, lipoproteins, and inflammation in abdominal obesity : a randomized controlled trial
- 2012
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In: American Journal of Clinical Nutrition. - : Elsevier BV. - 0002-9165 .- 1938-3207. ; 95:5, s. 1003-1012
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Journal article (peer-reviewed)abstract
- BACKGROUND: Replacing SFAs with vegetable PUFAs has cardiometabolic benefits, but the effects on liver fat are unknown. Increased dietary n-6 PUFAs have, however, also been proposed to promote inflammation-a yet unproven theory. OBJECTIVE: We investigated the effects of PUFAs on liver fat, systemic inflammation, and metabolic disorders. DESIGN: We randomly assigned 67 abdominally obese subjects (15% had type 2 diabetes) to a 10-wk isocaloric diet high in vegetable n-6 PUFA (PUFA diet) or SFA mainly from butter (SFA diet), without altering the macronutrient intake. Liver fat was assessed by MRI and magnetic resonance proton (1H) spectroscopy (MRS). Proprotein convertase subtilisin/kexin type-9 (PCSK9, a hepatic LDL-receptor regulator), inflammation, and adipose tissue expression of inflammatory and lipogenic genes were determined. RESULTS: A total of 61 subjects completed the study. Body weight modestly increased but was not different between groups. Liver fat was lower during the PUFA diet than during the SFA diet [between-group difference in relative change from baseline; 16% (MRI; P < 0.001), 34% (MRS; P = 0.02)]. PCSK9 (P = 0.001), TNF receptor-2 (P < 0.01), and IL-1 receptor antagonist (P = 0.02) concentrations were lower during the PUFA diet, whereas insulin (P = 0.06) tended to be higher during the SFA diet. In compliant subjects (defined as change in serum linoleic acid), insulin, total/HDL-cholesterol ratio, LDL cholesterol, and triglycerides were lower during the PUFA diet than during the SFA diet (P < 0.05). Adipose tissue gene expression was unchanged. CONCLUSIONS: Compared with SFA intake, n-6 PUFAs reduce liver fat and modestly improve metabolic status, without weight loss. A high n-6 PUFA intake does not cause any signs of inflammation or oxidative stress. Downregulation of PCSK9 could be a novel mechanism behind the cholesterol-lowering effects of PUFAs.
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| 22. |
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| 23. |
- Björk, Marcus, et al.
(author)
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Signal Modeling and the Cramér-Rao Bound for Absolute Magnetic Resonance Thermometry in Fat Tissue
- 2011
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In: Proc. 45th Asilomar Conference on Signals, Systems, and Computers. ; , s. 80-84
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Conference paper (peer-reviewed)abstract
- Magnetic Resonance Imaging of tissues with both fat and water resonances allows for absolute temperature mapping through parametric modeling. The fat resonance is used as a reference to determine the absolute water resonance frequency which is linearly related to the temperature. The goal of thispaper is to assess whether or not resonance frequency based absolute temperature mapping is feasible in fat tissue. This is done by examining identifiability conditions and analyzing the obtainable performance in terms of the Cramér-Rao Bound of the temperature estimates. We develop the model by including multiple fat peaks, since even small fat resonances can be significant compared to the small water component in fat tissue. It is showed that a high signal to noise ratio is needed for practical use on a 1.5 T scanner, and that higher field strengths can improve the bound significantly. It is also shown that the choice of sampling interval is important to avoid aliasing. In sum, this type of magnetic resonance thermometry is feasible for fat tissuein applications where high field strength is used or when high signal to noise ratio can be obtained.
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| 24. |
- Björnson, Elias, 1988, et al.
(author)
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Mediating role of atherogenic lipoproteins in the relationship between liver fat and coronary artery calcification
- 2023
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In: Scientific Reports. - : Springer Nature. - 2045-2322. ; 13:1
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Journal article (peer-reviewed)abstract
- Non-alcoholic fatty liver disease (NAFLD) is associated with increased secretion of apoB-containing lipoproteins and increased risk of coronary heart disease (CHD). ApoB-containing lipoproteins include low-density lipoproteins (LDLs) and triglyceride-rich lipoproteins (TRLs); and since both LDLs and TRLs are causally related to CHD, they may mediate a portion of the increased risk of atherosclerosis seen in people with NAFLD. In a cohort of 4161 middle aged men and women, we performed mediation analysis in order to quantify the mediating effect of apoB-containing lipoproteins in the relationship between liver fat and atherosclerosis-as measured by coronary artery calcium score (CACS). We found plasma apoB to mediate 17.6% (95% CI 11-24) of the association between liver fat and CACS. Plasma triglycerides and TRL-cholesterol (both proximate measures of TRL particles) mediated 22.3% (95% CI 11-34) and 21.6% (95% CI 10-33) of the association respectively; whereas LDL-cholesterol mediated 5.4% (95% CI 2.0-9.4). In multivariable models, the mediating effect of TRL-cholesterol and plasma triglycerides showed, again, a higher degree of mediation than LDL-cholesterol, corroborating the results seen in the univariable models. In summary, we find around 20% of the association between liver fat and CACS to be mediated by apoB-containing lipoproteins. In addition, we find that TRLs mediate the majority of this effect whereas LDLs mediate a smaller effect. These results explain part of the observed CAD-risk burden for people with NAFLD and further suggest that TRL-lowering may be particularly beneficial to mitigate NAFLD-associated coronary artery disease risk.
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| 25. |
- Boersma, Greta J., et al.
(author)
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Altered Glucose Uptake in Muscle, Visceral Adipose Tissue, and Brain Predict Whole-Body Insulin Resistance and may Contribute to the Development of Type 2 Diabetes: A Combined PET/MR Study
- 2018
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In: Hormone and Metabolic Research. - : Georg Thieme Verlag KG. - 0018-5043 .- 1439-4286. ; 50:8
-
Journal article (peer-reviewed)abstract
- We assessed glucose uptake in different tissues in type 2 diabetes (T2D), prediabetes, and control subjects to elucidate its impact in the development of whole-body insulin resistance and T2D. Thirteen T2D, 12 prediabetes, and 10 control subjects, matched for age and BMI, underwent OGTT and abdominal subcutaneous adipose tissue (SAT) biopsies. Integrated whole-body 18F-FDG PET and MRI were performed during a hyperinsulinemic euglycemic clamp to asses glucose uptake rate (MRglu) in several tissues. MRglu in skeletal muscle, SAT, visceral adipose tissue (VAT), and liver was significantly reduced in T2D subjects and correlated positively with M-values (r = 0.884, r = 0.574, r = 0.707 and r = 0.403, respectively). Brain MRglu was significantly higher in T2D and prediabetes subjects and had a significant inverse correlation with M-values (r = -0.616). Myocardial MRglu did not differ between groups and did not correlate with the M-values. A multivariate model including skeletal muscle, brain and VAT MRglu best predicted the M-values (adjusted r2 = 0.85). In addition, SAT MRglu correlated with SAT glucose uptake ex vivo (r = 0.491). In different stages of the development of T2D, glucose uptake during hyperinsulinemia is elevated in the brain in parallel with an impairment in peripheral organs. Impaired glucose uptake in skeletal muscle and VAT together with elevated glucose uptake in brain were independently associated with whole-body insulin resistance, and these tissue-specific alterations may contribute to T2D development.
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| 26. |
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| 27. |
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| 28. |
- Bolinder, Jan, et al.
(author)
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Effects of dapagliflozin on body weight, total fat mass, and regional adipose tissue distribution in patients with type 2 diabetes mellitus with inadequate glycemic control on metformin
- 2012
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In: Journal of Clinical Endocrinology and Metabolism. - : The Endocrine Society. - 0021-972X .- 1945-7197. ; 97:3, s. 1020-1031
-
Journal article (peer-reviewed)abstract
- Context:Dapagliflozin, a selective sodium-glucose cotransporter 2 (SGLT2) inhibitor, reduces hyperglycemia in patients with type 2 diabetes mellitus (T2DM) by increasing urinary glucose excretion, and weight loss is a consistent associated finding.Objectives:Our objectives were to confirm weight loss with dapagliflozin and establish through body composition measurements whether weight loss is accounted for by changes in fat or fluid components.Design and Setting:This was a 24-wk, international, multicenter, randomized, parallel-group, double-blind, placebo-controlled study with ongoing 78-wk site- and patient-blinded extension period at 40 sites in five countries.Patients:Included were 182 patients with T2DM (mean values: women 63.3 and men 58.6 yr of age; hemoglobin A1c 7.17%, body mass index 31.9 kg/m2, and body weight 91.5 kg) inadequately controlled on metformin.Intervention:Dapagliflozin 10 mg/d or placebo was added to open-label metformin for 24 wk.Main Outcome Measures:Primary endpoint was total body weight (TBW) change from baseline at wk 24. Key secondary endpoints were waist circumference and dual-energy x-ray absorptiometry total-body fat mass (FM) changes from baseline at wk 24, and patient proportion achieving body weight reduction of at least 5% at wk 24. In a subset of patients, magnetic resonance assessment of visceral adipose tissue (VAT) and sc adipose tissue (SAT) volume and hepatic lipid content were also evaluated.Results:At wk 24, placebo-corrected changes with dapagliflozin were as follows: TBW, −2.08 kg [95% confidence interval (CI) = −2.84 to −1.31; P < 0.0001]; waist circumference, −1.52 cm (95% CI = −2.74 to −0.31; P = 0.0143); FM, −1.48 kg (95% CI = −2.22 to −0.74; P = 0.0001); proportion of patients achieving weight reduction of at least 5%, +26.2% (95% CI = 15.5 to 36.7; P < 0.0001); VAT, −258.4 cm3 (95% CI = −448.1 to −68.6; nominal P = 0.0084); SAT, −184.9 cm3 (95% CI = −359.7 to −10.1; nominal P = 0.0385). In the dapagliflozin vs. placebo groups, respectively, serious adverse events were reported in 6.6 vs. 1.1%; events suggestive of vulvovaginitis, balanitis, and related genital infection in 3.3 vs. 0%; and lower urinary tract infections in 6.6 vs. 2.2%.Conclusions:Dapagliflozin reduces TBW, predominantly by reducing FM, VAT and SAT in T2DM inadequately controlled with metformin.
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| 29. |
- Boone, Sebastiaan C., et al.
(author)
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Evaluation of the Value of Waist Circumference and Metabolomics in the Estimation of Visceral Adipose Tissue
- 2022
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In: American Journal of Epidemiology. - : Oxford University Press (OUP). - 0002-9262 .- 1476-6256. ; 191:5, s. 886-899
-
Journal article (peer-reviewed)abstract
- Visceral adipose tissue (VAT) is a strong prognostic factor for cardiovascular disease and a potential target for cardiovascular risk stratification. Because VAT is difficult to measure in clinical practice, we estimated prediction models with predictors routinely measured in general practice and VAT as outcome using ridge regression in 2,501 middle-aged participants from the Netherlands Epidemiology of Obesity study, 2008-2012. Adding waist circumference and other anthropometric measurements on top of the routinely measured variables improved the optimism-adjusted R-2 from 0.50 to 0.58 with a decrease in the root-mean-square error (RMSE) from 45.6 to 41.5 cm(2) and with overall good calibration. Further addition of predominantly lipoprotein-related metabolites from the Nightingale platform did not improve the optimism-corrected R-2 and RMSE. The models were externally validated in 370 participants from the Prospective Investigation of Vasculature in Uppsala Seniors (PIVUS, 2006-2009) and 1,901 participants from the Multi-Ethnic Study of Atherosclerosis (MESA, 2000-2007). Performance was comparable to the development setting in PIVUS (R-2 = 0.63, RMSE = 42.4 cm(2), calibration slope = 0.94) but lower in MESA (R-2 = 0.44, RMSE = 60.7 cm(2), calibration slope = 0.75). Our findings indicate that the estimation of VAT with routine clinical measurements can be substantially improved by incorporating waist circumference but not by metabolite measurements.
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| 30. |
- Breznik, Eva
(author)
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Image Processing and Analysis Methods for Biomedical Applications
- 2023
-
Doctoral thesis (other academic/artistic)abstract
- With new technologies and developments medical images can be acquired more quickly and at a larger scale than ever before. However, increased amount of data induces an overhead in the human labour needed for its inspection and analysis. To support clinicians in decision making and enable swifter examinations, computerized methods can be utilized to automate the more time-consuming tasks. For such use, methods need be highly accurate, fast, reliable and interpretable. In this thesis we develop and improve methods for image segmentation, retrieval and statistical analysis, with applications in imaging-based diagnostic pipelines. Individual objects often need to first be extracted/segmented from the image before they can be analysed further. We propose methodological improvements for deep learning-based segmentation methods using distance maps, with the focus on fully-supervised 3D patch-based training and training on 2D slices under point supervision. We show that using a directly interpretable distance prior helps to improve segmentation accuracy and training stability.For histological data in particular, we propose and extensively evaluate a contrastive learning and bag of words-based pipeline for cross-modal image retrieval. The method is able to recover correct matches from the database across modalities and small transformations with improved accuracy compared to the competitors. In addition, we examine a number of methods for multiplicity correction on statistical analyses of correlation using medical images. Evaluation strategies are discussed and anatomy-observing extensions to the methods are developed as a way of directly decreasing the multiplicity issue in an interpretable manner, providing improvements in error control. The methods presented in this thesis were developed with clinical applications in mind and provide a strong base for further developments and future use in medical practice.
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| 31. |
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| 32. |
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| 33. |
- Breznik, Eva, et al.
(author)
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Multiple comparison correction methods for whole-body magnetic resonance imaging
- 2020
-
In: Journal of Medical Imaging. - : SPIE-Intl Soc Optical Eng. - 2329-4302 .- 2329-4310. ; 7:1
-
Journal article (peer-reviewed)abstract
- Purpose: Voxel-level hypothesis testing on images suffers from test multiplicity. Numerous correction methods exist, mainly applied and evaluated on neuroimaging and synthetic datasets. However, newly developed approaches like Imiomics, using different data and less common analysis types, also require multiplicity correction for more reliable inference. To handle the multiple comparisons in Imiomics, we aim to evaluate correction methods on whole-body MRI and correlation analyses, and to develop techniques specifically suited for the given analyses. Approach: We evaluate the most common familywise error rate (FWER) limiting procedures on whole-body correlation analyses via standard (synthetic no-activation) nominal error rate estimation as well as smaller prior-knowledge based stringency analysis. Their performance is compared to our anatomy-based method extensions. Results: Results show that nonparametric methods behave better for the given analyses. The proposed prior-knowledge based evaluation shows that the devised extensions including anatomical priors can achieve the same power while keeping the FWER closer to the desired rate. Conclusions: Permutation-based approaches perform adequately and can be used within Imiomics. They can be improved by including information on image structure. We expect such method extensions to become even more relevant with new applications and larger datasets.
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| 34. |
- Brooks, Samantha J, et al.
(author)
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Late-life obesity is associated with smaller global and regional gray matter volumes : a voxel-based morphometric study
- 2013
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In: International Journal of Obesity. - : Springer Science and Business Media LLC. - 0307-0565 .- 1476-5497. ; 37:2, s. 230-236
-
Journal article (peer-reviewed)abstract
- OBJECTIVE: Obesity adversely affects frontal lobe brain structure and function. Here we sought to show that people who are obese versus those who are of normal weight over a 5-year period have differential global and regional brain volumes.DESIGN: Using voxel-based morphometry, contrasts were done between those who were recorded as being either obese or of normal weight over two time points in the 5 years prior to the brain scan. In a post-hoc preliminary analysis, we compared scores for obese and normal weight people who completed the trail-making task.SUBJECTS: A total of 292 subjects were examined following exclusions (for example, owing to dementia, stroke and cortical infarcts) from the Prospective Investigation of the Vasculature in Uppsala Seniors cohort with a body mass index of normal weight (<25 kg m−2) or obese (30 kg m−2).RESULTS: People who were obese had significantly smaller total brain volumes and specifically, significantly reduced total gray matter (GM) volume (GMV) (with no difference in white matter or cerebrospinal fluid). Initial exploratory whole brain uncorrected analysis revealed that people who were obese had significantly smaller GMV in the bilateral supplementary motor area, bilateral dorsolateral prefrontal cortex (DLPFC), left inferior frontal gyrus and left postcentral gyrus. Secondary more stringent corrected analyses revealed a surviving cluster of GMV difference in the left DLPFC. Finally, post-hoc contrasts of scores on the trail-making task, which is linked to DLPFC function, revealed that obese people were significantly slower than those of normal weight.CONCLUSION: These findings suggest that in comparison with normal weight, people who are obese have smaller GMV, particularly in the left DLPFC. Our results may provide evidence for a potential working memory mechanism for the cognitive suppression of appetite that may lower the risk of developing obesity in later life.
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| 35. |
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| 36. |
- Bucci, Marco, et al.
(author)
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Resistance training improves skeletal muscle insulin sensitivity in elderly offspring of overweight and obese mothers.
- 2016
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In: Diabetologia. - : Springer Science and Business Media LLC. - 0012-186X .- 1432-0428. ; 59:1, s. 77-86
-
Journal article (peer-reviewed)abstract
- AIMS/HYPOTHESIS: Maternal obesity predisposes offspring to adulthood morbidities, including type 2 diabetes. Type 2 diabetes and insulin resistance have been associated with shortened telomere length. First, we aimed to investigate whether or not maternal obesity influences insulin sensitivity and its relationship with leucocyte telomere length (LTL) in elderly women. Second, we tested whether or not resistance exercise training improves insulin sensitivity in elderly frail women.METHODS: Forty-six elderly women, of whom 20 were frail offspring of lean/normal weight mothers (OLM, BMI ≤26.3 kg/m(2)) and 17 were frail offspring of overweight/obese mothers (OOM, BMI ≥28.1 kg/m(2)), were studied before and after a 4 month resistance training (RT) intervention. Muscle insulin sensitivity of glucose uptake was measured using (18)F-fluoro-2-deoxyglucose and positron emission tomography with computed tomography during a hyperinsulinaemic-euglycaemic clamp. Muscle mass and lipid content were measured using magnetic resonance and LTL was measured using real-time PCR.RESULTS: The OOM group had lower thigh muscle insulin sensitivity compared with the OLM group (p = 0.048) but similar whole body insulin sensitivity. RT improved whole body and skeletal muscle insulin sensitivity in the OOM group only (p = 0.004 and p = 0.013, respectively), and increased muscle mass in both groups (p < 0.01). In addition, in the OOM group, LTL correlated with different thigh muscle groups insulin sensitivity (ρ ≥ 0.53; p ≤ 0.05). Individuals with shorter LTL showed a higher increase in skeletal muscle insulin sensitivity after training (ρ ≥ -0.61; p ≤ 0.05).CONCLUSIONS/INTERPRETATION: Maternal obesity and having telomere shortening were associated with insulin resistance in adult offspring. A resistance exercise training programme may reverse this disadvantage among offspring of obese mothers.TRIAL REGISTRATION: ClinicalTrials.gov NCT01931540.
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| 37. |
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| 38. |
- Chu, Audrey Y, et al.
(author)
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Multiethnic genome-wide meta-analysis of ectopic fat depots identifies loci associated with adipocyte development and differentiation
- 2017
-
In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 49:1, s. 125-130
-
Journal article (peer-reviewed)abstract
- Variation in body fat distribution contributes to the metabolic sequelae of obesity. The genetic determinants of body fat distribution are poorly understood. The goal of this study was to gain new insights into the underlying genetics of body fat distribution by conducting sample-size-weighted fixed-effects genome-wide association meta-analyses in up to 9,594 women and 8,738 men of European, African, Hispanic and Chinese ancestry, with and without sex stratification, for six traits associated with ectopic fat (hereinafter referred to as ectopic-fat traits). In total, we identified seven new loci associated with ectopic-fat traits (ATXN1, UBE2E2, EBF1, RREB1, GSDMB, GRAMD3 and ENSA; P < 5 × 10(-8); false discovery rate < 1%). Functional analysis of these genes showed that loss of function of either Atxn1 or Ube2e2 in primary mouse adipose progenitor cells impaired adipocyte differentiation, suggesting physiological roles for ATXN1 and UBE2E2 in adipogenesis. Future studies are necessary to further explore the mechanisms by which these genes affect adipocyte biology and how their perturbations contribute to systemic metabolic disease.
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| 39. |
- Diamanti, Klev, 1987-, et al.
(author)
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Integration of whole-body [18F]FDG PET/MRI with non-targeted metabolomics can provide new insights on tissue-specific insulin resistance in type 2 diabetes
- 2020
-
In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 10:1
-
Journal article (peer-reviewed)abstract
- Alteration of various metabolites has been linked to type 2 diabetes (T2D) and insulin resistance. However, identifying significant associations between metabolites and tissue-specific phenotypes requires a multi-omics approach. In a cohort of 42 subjects with different levels of glucose tolerance (normal, prediabetes and T2D) matched for age and body mass index, we calculated associations between parameters of whole-body positron emission tomography (PET)/magnetic resonance imaging (MRI) during hyperinsulinemic euglycemic clamp and non-targeted metabolomics profiling for subcutaneous adipose tissue (SAT) and plasma. Plasma metabolomics profiling revealed that hepatic fat content was positively associated with tyrosine, and negatively associated with lysoPC(P-16:0). Visceral adipose tissue (VAT) and SAT insulin sensitivity (Ki), were positively associated with several lysophospholipids, while the opposite applied to branched-chain amino acids. The adipose tissue metabolomics revealed a positive association between non-esterified fatty acids and, VAT and liver Ki. Bile acids and carnitines in adipose tissue were inversely associated with VAT Ki. Furthermore, we detected several metabolites that were significantly higher in T2D than normal/prediabetes. In this study we present novel associations between several metabolites from SAT and plasma with the fat fraction, volume and insulin sensitivity of various tissues throughout the body, demonstrating the benefit of an integrative multi-omics approach.
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| 40. |
- Diamanti, Klev, 1987-, et al.
(author)
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Integration of whole-body PET/MRI with non-targeted metabolomics provides new insights into insulin sensitivity of various tissues
-
Other publication (other academic/artistic)abstract
- Background: Alteration of various metabolites has been linked to type 2 diabetes (T2D) and insulin resistance. However, identifying significant associations between metabolites and tissue-specific alterations is challenging and requires a multi-omics approach. In this study, we aimed at discovering associations of metabolites from subcutaneous adipose tissue (SAT) and plasma with the volume, the fat fraction (FF) and the insulin sensitivity (Ki) of specific tissues using [18F]FDG PET/MRI.Materials and Methods: In a cohort of 42 subjects with different levels of glucose tolerance (normal, prediabetes and T2D) matched for age and body-mass-index (BMI) we calculated associations between parameters of whole-body FDG PET/MRI during clamp and non-targeted metabolomics profiling for SAT and blood plasma. We also used a rule-based classifier to identify a large collection of prevalent patterns of co-dependent metabolites that characterize non-diabetes (ND) and T2D.Results: The plasma metabolomics profiling revealed that hepatic fat content was positively associated with tyrosine, and negatively associated with lysoPC(P-16:0). Ki in visceral adipose tissue (VAT) and SAT, was positively associated with several species of lysophospholipids while the opposite applied to branched-chain amino acids (BCAA) and their intermediates. The adipose tissue metabolomics revealed a positive association between non-esterified fatty acids and, VAT and liver Ki. On the contrary, bile acids and carnitines in adipose tissue were inversely associated with VAT Ki. Finally, we presented a transparent machine-learning model that predicted ND or T2D in “unseen” data with an accuracy of 78%.Conclusions: Novel associations of several metabolites from SAT and plasma with the FF, volume and insulin senstivity of various tissues throughout the body were discovered using PET/MRI and a new integrative multi-omics approach. A promising computational model that predicted ND and T2D with high certainty, suggested novel non-linear interdependencies of metabolites.
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| 41. |
- Edholm, David, et al.
(author)
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Changes in liver volume and body composition during 4 weeks of low calorie diet before laparoscopic gastric bypass
- 2015
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In: Surgery for Obesity and Related Diseases. - : Elsevier BV. - 1550-7289 .- 1878-7533. ; 11:3, s. 602-606
-
Journal article (peer-reviewed)abstract
- BACKGROUND:Weight loss before laparoscopic Roux-en-Y gastric bypass (LRYGB) is desirable, because it can reduce liver volume and thereby facilitate the procedure. The optimal duration of a low-calorie diet (LCD) has not been established. The objective of this study was to assess changes in liver volume and body composition during 4 weeks of LCD.METHODS:Ten women (aged 43±8.9 years, 114±12.1 kg, and body mass index 42±2.6 kg/m2) were examined on days 0, 3, 7, 14, and 28 after commencing the LCD. At each evaluation, body composition was assessed through bioelectric impedance analysis, and liver volume and intrahepatic fat content were assessed by magnetic resonance imaging. Serum and urine samples were obtained. Questionnaires regarding quality of life and LCD-related symptoms were administered.RESULTS:In total, mean weight decreased by 7.4±1.2 kg (range 5.7-9.1 kg), and 71% of the weight loss consisted of fat mass according to bioelectric impedance analysis. From day 0 to day 3, the weight loss (2.0 kg) consisted mainly of water. Liver volume decreased by 18%±6.2%, from 2.1 to 1.7 liters (P<.01), during the first 2 weeks with no further change thereafter. A continuous 51%±16% decrease was seen in intrahepatic fat content. Systolic blood pressure, insulin, and lipids improved, while liver enzymes, glucose levels, and quality of life were unaffected.CONCLUSION:A significant decrease in liver volume (18%) occurred during the first 2 weeks of LCD treatment, and intrahepatic fat gradually decreased throughout the study period. A preoperative 2-week LCD treatment seems sufficient in similar patients.
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| 42. |
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| 43. |
- Edholm, David, et al.
(author)
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Preoperative 4-week low-calorie diet reduces liver volume and intrahepatic fat, and facilitates laparoscopic gastric bypass in morbidly obese
- 2011
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In: Obesity Surgery. - : Springer Science and Business Media LLC. - 0960-8923 .- 1708-0428. ; 21:3, s. 345-350
-
Journal article (peer-reviewed)abstract
- BACKGROUND: The aim of this study was to explore changes in liver volume and intrahepatic fat in morbidly obese patients during 4 weeks of low-calorie diet (LCD) before surgery and to investigate if these changes would facilitate the following laparoscopic gastric bypass.METHODS: Fifteen female patients (121.3 kg, BMI 42.9) were treated preoperatively in an open study with LCD (800-1,100 kcal/day) during 4 weeks. Liver volume and fat content were assessed by magnetic resonance imaging and spectroscopy before and after the LCD treatment.RESULTS: Liver appearance and the complexity of the surgery were scored at the operation. Eighteen control patients (114.4 kg, BMI 40.8), without LCD were scored similarly. Average weight loss in the LCD group was 7.5 kg, giving a mean weight of 113.9 kg at surgery. Liver volume decreased by 12% (p < 0.001) and intrahepatic fat by 40% (p < 0.001). According to the preoperative scoring, the size of the left liver lobe, sharpness of the liver edge, and exposure of the hiatal region were improved in the LCD group compared to the controls (all p < 0.05).CONCLUSIONS: The overall complexity of the surgery was perceived lower in the LCD group (p < 0.05), due to improved exposure and reduced psychological stress (both p < 0.05). Four weeks of preoperative LCD resulted in a significant decrease in liver volume and intrahepatic fat content, and facilitated the subsequent laparoscopic gastric bypass as scored by the surgeon
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| 44. |
- Ekström, Simon, 1991-, et al.
(author)
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Deformable Image Registration of Volumetric Whole-body MRI: An Evaluation
-
Other publication (other academic/artistic)abstract
- Whole-body imaging presents a variety of interesting applications and combining these information rich images with image registration enables detailed large scale analysis. Whole-body image registration, with the large variability present in human anatomy, introduces a range of challenges that need to be dealt with. This paper aims to present two new extensions to a previously published registration method based on compositive updates and voxel-wise regularization. The new extensions are evaluated against a previously presented pipeline for whole-body registration and a learning-based approach using the Voxel Morph framework. The methods are evaluated on Dice overlap, smoothness of produced displacement fields, and the inverse consistency error. The presented extensions are shown to improve upon previous method both in terms of computation time and registration quality. The voxel-wise regularization produces a mean Dice overlap of 0.828 for the 10 segmented regions and a mean computation time of 320 seconds per subject. The learning-based approach had an inference time of only 3 seconds but a training time of 16 hours per reference subject. This approach produced a mean Dice overlap of only 0.797 but it was shown that the issues in overlap score were limited to the kidneys. In conclusion, both the extensions and VoxelMorph has presented great promise for the task of whole-body registration compared to previous method. However, the choice of method will be highly dependent upon the task. VoxelMorph provides results of lower quality and reduced flexibility but a computation time of only a few seconds.
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| 45. |
- Ekström, Simon, 1991-
(author)
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Efficient GPU-based Image Registration : for Detailed Large-Scale Whole-body Analysis
- 2020
-
Doctoral thesis (other academic/artistic)abstract
- Imaging has become an important aspect of medicine, enabling visualization of internals in a non-invasive manner. The rapid advancement and adoption of imaging techniques have led to a demand for tools able to take advantage of the information that is produced. Medical image analysis aims to extract relevant information from acquired images to aid diagnostics in healthcare and increase the understanding within medical research. The main subject of this thesis, image registration, is a widely used tool in image analysis that can be employed to find a spatial transformation aligning a set of images. One application, that is described in detail in this thesis, is the use of image registration for large-scale analysis of whole-body images through the utilization of the correspondences defined by the resulting transformations. To produce detailed results, the correspondences, i.e. transformations, need to be of high resolution and the quality of the result has a direct impact on the quality of the analysis. Also, this type of application aims to analyze large cohorts and the value of a registration method is not only weighted by its ability to produce an accurate result but also by its efficiency. This thesis presents two contributions on the subject; a new method for efficient image registration with the ability to produce dense deformable transformations, and the application of the presented method in large-scale analysis of a whole-body dataset acquired using an integrated positron emission tomography (PET) and magnetic resonance imaging (MRI) system. In this thesis, it is shown that efficient and detailed image registration can be performed by employing graph cuts and a heuristic where the optimization is performed on subregions of the image. The performance can be improved further by the efficient utilization of a graphics processing unit (GPU). It is also shown that the method can be employed to produce a model on health based on a PET-MRI dataset which can be utilized to automatically detect pathology in the imaging.
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| 46. |
- Ekström, Simon, 1991-, et al.
(author)
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Fast graph-cut based optimization for practical dense deformable registration of volume images
- 2020
-
In: Computerized Medical Imaging and Graphics. - : Elsevier. - 0895-6111 .- 1879-0771. ; 84
-
Journal article (peer-reviewed)abstract
- Deformable image registration is a fundamental problem in medical image analysis, with applications such as longitudinal studies, population modeling, and atlas-based image segmentation. Registration is often phrased as an optimization problem, i.e., finding a deformation field that is optimal according to a given objective function. Discrete, combinatorial, optimization techniques have successfully been employed to solve the resulting optimization problem. Specifically, optimization based on α-expansion with minimal graph cuts has been proposed as a powerful tool for image registration. The high computational cost of the graph-cut based optimization approach, however, limits the utility of this approach for registration of large volume images. Here, we propose to accelerate graph-cut based deformable registration by dividing the image into overlapping sub-regions and restricting the α-expansion moves to a single sub-region at a time. We demonstrate empirically that this approach can achieve a large reduction in computation time - from days to minutes - with only a small penalty in terms of solution quality. The reduction in computation time provided by the proposed method makes graph-cut based deformable registration viable for large volume images. Graph-cut based image registration has previously been shown to produce excellent results, but the high computational cost has hindered the adoption of the method for registration of large medical volume images. Our proposed method lifts this restriction, requiring only a small fraction of the computational cost to produce results of comparable quality.
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| 47. |
- Ekström, Simon, 1991-, et al.
(author)
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Faster dense deformable image registration by utilizing both CPU and GPU
-
Other publication (other academic/artistic)abstract
- Purpose: Image registration is an important aspect of medical image analysis and a key component in many analysis concepts. Applications include fusion of multimodal images, multi-atlas segmentation, and whole-body analysis. Deformable image registration is often computationally expensive, and the need for efficient registration methods is highlighted by the emergence of large-scale image databases, e.g., the UK Biobank, providing imaging from 100 000 participants.Approach: We present a heterogeneous computing approach, utilizing both the CPU and the GPU, to accelerate a previously proposed image registration method. The parallelizable task of computing the matching criterion is offloaded to the GPU, where it can be computed efficiently, while the more complex optimization task is performed on the CPU. To lessen the impact of data synchronization between the CPU and GPU we propose a pipeline model, effectively overlapping computational tasks with data synchronization. The performance is evaluated on a brain labeling task and compared with a CPU implementation of the same method and the popular Advanced Normalization Tools (ANTs) software.Results: The proposed method presents a speed-up by a factor of 4 and 8 against the CPU implementation and the ANTs software respectively. A significant improvement in labeling quality was also observed, with measured mean Dice overlaps of 0.712 and 0.701 for our method and ANTs respectively.Conclusions: We showed that the proposed method compares favorably to the ANTs software yielding both a significant speed-up and an improvement in labeling quality. The registration method together with the proposed parallelization strategy is implemented as an open-source software package, deform.
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| 48. |
- Ekström, Simon, 1991-, et al.
(author)
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Faster dense deformable image registration by utilizing both CPU and GPU
- 2021
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In: Journal of Medical Imaging. - 2329-4302 .- 2329-4310. ; 8:1
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Journal article (peer-reviewed)abstract
- Purpose: Image registration is an important aspect of medical image analysis and a key component in many analysis concepts. Applications include fusion of multimodal images, multi-atlas segmentation, and whole-body analysis. Deformable image registration is often computationally expensive, and the need for efficient registration methods is highlighted by the emergence of large-scale image databases, e.g., the UK Biobank, providing imaging from 100,000 participants. Approach: We present a heterogeneous computing approach, utilizing both the CPU and the graphics processing unit (GPU), to accelerate a previously proposed image registration method. The parallelizable task of computing the matching criterion is offloaded to the GPU, where it can be computed efficiently, while the more complex optimization task is performed on the CPU. To lessen the impact of data synchronization between the CPU and GPU, we propose a pipeline model, effectively overlapping computational tasks with data synchronization. The performance is evaluated on a brain labeling task and compared with a CPU implementation of the same method and the popular advanced normalization tools (ANTs) software. Results: The proposed method presents a speed-up by factors of 4 and 8 against the CPU implementation and the ANTs software, respectively. A significant improvement in labeling quality was also observed, with measured mean Dice overlaps of 0.712 and 0.701 for our method and ANTs, respectively. Conclusions: We showed that the proposed method compares favorably to the ANTs software yielding both a significant speed-up and an improvement in labeling quality. The registration method together with the proposed parallelization strategy is implemented as an open-source software package, deform.
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| 49. |
- Elmsjö, Albert, et al.
(author)
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NMR-based metabolic profiling in healthy individuals overfed different types of fat : links to changes in liver fat accumulation and lean tissue mass.
- 2015
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In: Nutrition & Diabetes. - : Springer Science and Business Media LLC. - 2044-4052. ; 5:19, s. e182-
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Journal article (peer-reviewed)abstract
- BACKGROUND: Overeating different dietary fatty acids influence the amount of liver fat stored during weight gain, however, the mechanisms responsible are unclear. We aimed to identify non-lipid metabolites that may differentiate between saturated (SFA) and polyunsaturated fatty acid (PUFA) overfeeding using a non-targeted metabolomic approach. We also investigated the possible relationships between plasma metabolites and body fat accumulation.METHODS: In a randomized study (LIPOGAIN study), n=39 healthy individuals were overfed with muffins containing SFA or PUFA. Plasma samples were precipitated with cold acetonitrile and analyzed by nuclear magnetic resonance (NMR) spectroscopy. Pattern recognition techniques were used to overview the data, identify variables contributing to group classification and to correlate metabolites with fat accumulation.RESULTS: We previously reported that SFA causes a greater accumulation of liver fat, visceral fat and total body fat, whereas lean tissue levels increases less compared with PUFA, despite comparable weight gain. In this study, lactate and acetate were identified as important contributors to group classification between SFA and PUFA (P<0.05). Furthermore, the fat depots (total body fat, visceral adipose tissue and liver fat) and lean tissue correlated (P(corr)>0.5) all with two or more metabolites (for example, branched amino acids, alanine, acetate and lactate). The metabolite composition differed in a manner that may indicate higher insulin sensitivity after a diet with PUFA compared with SFA, but this needs to be confirmed in future studies.CONCLUSION: A non-lipid metabolic profiling approach only identified a few metabolites that differentiated between SFA and PUFA overfeeding. Whether these metabolite changes are involved in depot-specific fat storage and increased lean tissue mass during overeating needs further investigation.
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| 50. |
- Eriksson, Jan W, et al.
(author)
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Tissue-specific glucose partitioning and fat content in prediabetes and type 2 diabetes: whole-body PET/MRI during hyperinsulinemia
- 2021
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In: European journal of endocrinology. - : Bioscientifica. - 0804-4643 .- 1479-683X. ; 184:6, s. 879-899
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Journal article (peer-reviewed)abstract
- Objective: To obtain direct quantifications of glucose turnover, volumes an d fat content of several tissues in the development of type 2 diabetes (T2D) using a novel integrated a pproach for whole-body imaging. Design and methods: Hyperinsulinemic-euglycemic clamps and simultaneous whole-body integrated [18F]FDG-PET/MRI with automated analyses were performed in control (n = 12), prediabetes (n = 16) and T2D (n = 13) subjects matched for age, sex and BMI. Results: Whole-body glucose uptake (Rd) was reduced by approximately 25% in T2D vs control subjects, and partitioning to brain was increased from 3.8% of total Rd in co ntrols to 7.1% in T2D. In liver, subcutaneous AT, thigh muscle, total tissue glucose metabolic rates (MRglu) and their % of total Rd were reduced in T2D compared to contr ol subjects. The prediabetes group had intermediate findings. Total MRglu in heart, visceral AT, gluteus and calf muscle was similar across groups. Whole-body insulin sensitivity asses sed as glucose infusion rate correlated with liver MR glu but inversely with brain MRglu. Liver fat content correlated with MRglu in brain but inversely with MRglu in other tissues. Calf muscle fat was inversely associated with MR glu only in the same muscle group. Conclusions: This integrated imaging approach provides detailed quantification of tissue-specific glucose metabolism. During T2D development, insulin-stimulated glucose disposal is impaired and increasingly shifted away from muscle, liver and fat toward the brain. Altered glucose handling in the brain and liver fat accumulation may aggravate insulin resistance in several organs. © 2021 BioScientifica Ltd.. All rights reserved.
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