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- Ahmad, Nouman, et al.
(författare)
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Automatic segmentation of large-scale CT image datasets for detailed body composition analysis
- 2023
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Ingår i: BMC BIOINFORMATICS. - : BioMed Central (BMC). - 1471-2105. ; 24:1
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Tidskriftsartikel (refereegranskat)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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- Morell, Arvid, et al.
(författare)
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Influence of blood/tissue differences in contrast agent relaxivity on tracer based MR perfusion measurements
- 2015
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Ingår i: Magnetic Resonance Materials in Physics, Biology and Medicine. - : Springer Science and Business Media LLC. - 0968-5243 .- 1352-8661. ; 28:2, s. 135-147
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE:Perfusion assessment by monitoring the transport of a tracer bolus depends critically on conversion of signal intensity into tracer concentration. Two main assumptions are generally applied for this conversion; (1) contrast agent relaxivity is identical in blood and tissue, (2) change in signal intensity depends only on the primary relaxation effect. The purpose of the study was to assess the validity and influence of these assumptions.MATERIALS AND METHODS:Blood and cerebral tissue relaxivities r1, r2, and r2* for gadodiamide were measured in four pigs at 1.5 T. Gadolinium concentration was determined by inductively coupled plasma atomic emission spectroscopy. Influence of the relaxivities, secondary relaxation effects and choice of singular value decomposition (SVD) regularization threshold was studied by simulations.RESULTS:In vivo relaxivities relative to blood concentration [in s-1 mM-1 for blood, gray matter (GM), white matter (WM)] were for r1 (2.614 ± 1.061, 0.010 ± 0.001, 0.004 ± 0.002), r2 (5.088 ± 0.952, 0.091 ± 0.008, 0.059 ± 0.014), and r2* (13.292 ± 3.928, 1.696 ± 0.157, 0.910 ± 0.139). Although substantial, by a nonparametric test for paired samples, the differences were not statistically significant. The GM to WM blood volume ratio was estimated to 2.6 ± 0.9 by r1, 1.6 ± 0.3 by r2, and 1.9 ± 0.2 by r2*. Secondary relaxation was found to reduce the tissue blood flow, as did the SVD regularization threshold.CONCLUSION:Contrast agent relaxivity is not identical in blood and tissue leading to substantial errors. Further errors are introduced by secondary relaxation effects and the SVD regularization.
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- Nilsson, Bo, et al.
(författare)
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C3 and C4 are strongly related to adipose tissue variables and cardiovascular risk factors
- 2014
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Ingår i: European Journal of Clinical Investigation. - : John Wiley & Sons. - 0014-2972 .- 1365-2362. ; 44:6, s. 587-596
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Tidskriftsartikel (refereegranskat)abstract
- Background In several reports, C3 and C4 have been linked to diabetes and cardiovascular disease (CVD). Here, we investigate this link and the degree of C3 activation in elderly individuals. Methods In this study, C3 and C4 and the activation fragment C3a-desArg were analysed in 1016 subjects aged 70, in which blood pressure, lipid variables and fasting blood glucose were assessed. Results C3 levels were related to all the investigated classical cardiovascular risk factors and the metabolic syndrome (BMI, waist circumference, fat distribution, blood pressure, blood glucose levels, TG) except total cholesterol and LDL cholesterol in a highly significant fashion (Spearman up to 0,5; P<0.0001). C4 and C3a-desArg were associated in the same fashion but less significantly, while the ratios C4/C3 or C3a-desArg/C3 were not, indicating thatthe association was not directly related to complement activation. The levels C3 and to a lesser degree C4 and C3a-desArg were associated particularly with CRP, but also with E-selectin and ICAM-1. In addition, C3 and C4 levels were shown to decline significantly in 15 female subjects enrolled in a weight-reduction programme over 4 months. Conclusion A strong relation between C3, C4 and C3a-desArg levels, adipose tissue and risk factors of CVD was established. The data support that theadipose tissue produces complement components and generates initiators of inflammation, such as C3a and C5a, able to trigger a cyto/chemokine response, in proportion to the amount of adipose tissue. This corroborates the concept that complement contributes to the low-grade inflammation associated with obesity.
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