| 1. |
- Knutsson, Linda, et al.
(författare)
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Dynamic susceptibility contrast MRI with a prebolus contrast agent administration design for improved absolute quantification of perfusion.
- 2014
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Ingår i: Magnetic Resonance in Medicine. - : Wiley. - 1522-2594 .- 0740-3194. ; 72:4, s. 996-1006
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Tidskriftsartikel (refereegranskat)abstract
- Arterial partial-volume effects (PVEs) often hamper reproducible absolute quantification of cerebral blood flow (CBF) and cerebral blood volume (CBV) obtained by dynamic susceptibility contrast MRI (DSC-MRI). The aim of this study was to examine whether arterial PVEs in DSC-MRI data can be minimized by rescaling the arterial input function (AIF) using a sagittal-sinus venous output function obtained following a prebolus administration of a low dose of contrast agent.
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| 4. |
- Ahmadi, Khazar, et al.
(författare)
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Gray matter hypoperfusion is a late pathological event in the course of Alzheimer's disease
- 2023
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Ingår i: Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism. - 1559-7016. ; 43:4, s. 565-580
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Tidskriftsartikel (refereegranskat)abstract
- Several studies have shown decreased cerebral blood flow (CBF) in Alzheimer's disease (AD). However, the role of hypoperfusion in the disease pathogenesis remains unclear. Combining arterial spin labeling MRI, PET, and CSF biomarkers, we investigated the associations between gray matter (GM)-CBF and the key mechanisms in AD including amyloid-β (Aβ) and tau pathology, synaptic and axonal degeneration. Further, we applied a disease progression modeling to characterize the temporal sequence of different AD biomarkers. Lower perfusion was observed in temporo-occipito-parietal cortex in the Aβ-positive cognitively impaired compared to both Aβ-negative and Aβ-positive cognitively unimpaired individuals. In participants along the AD spectrum, GM-CBF was associated with tau, synaptic and axonal dysfunction, but not Aβ in similar cortical regions. Axonal degeneration was further associated with hypoperfusion in cognitively unimpaired individuals. Disease progression modeling revealed that GM-CBF disruption Followed the abnormality of biomarkers of Aβ, tau and brain atrophy. These findings indicate that tau tangles and neurodegeneration are more closely connected with GM-CBF changes than Aβ pathology. Although subjected to the sensitivity of the employed neuroimaging techniques and the modeling approach, these findings suggest that hypoperfusion might not be an early event associated with the build-up of Aβ in preclinical phase of AD.
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| 5. |
- Brabec, Jan, et al.
(författare)
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Meningioma microstructure assessed by diffusion MRI : An investigation of the source of mean diffusivity and fractional anisotropy by quantitative histology
- 2023
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Ingår i: NeuroImage: Clinical. - : Elsevier BV. - 2213-1582. ; 37
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Mean diffusivity (MD) and fractional anisotropy (FA) from diffusion MRI (dMRI) have been associated with cell density and tissue anisotropy across tumors, but it is unknown whether these associations persist at the microscopic level.PURPOSE: To quantify the degree to which cell density and anisotropy, as determined from histology, account for the intra-tumor variability of MD and FA in meningioma tumors. Furthermore, to clarify whether other histological features account for additional intra-tumor variability of dMRI parameters.MATERIALS AND METHODS: We performed ex-vivo dMRI at 200 μm isotropic resolution and histological imaging of 16 excised meningioma tumor samples. Diffusion tensor imaging (DTI) was used to map MD and FA, as well as the in-plane FA (FA IP). Histology images were analyzed in terms of cell nuclei density (CD) and structure anisotropy (SA; obtained from structure tensor analysis) and were used separately in a regression analysis to predict MD and FA IP, respectively. A convolutional neural network (CNN) was also trained to predict the dMRI parameters from histology patches. The association between MRI and histology was analyzed in terms of out-of-sample (R 2 OS) on the intra-tumor level and within-sample R 2 across tumors. Regions where the dMRI parameters were poorly predicted from histology were analyzed to identify features apart from CD and SA that could influence MD and FA IP, respectively. RESULTS: Cell density assessed by histology poorly explained intra-tumor variability of MD at the mesoscopic level (200 μm), as median R 2 OS = 0.04 (interquartile range 0.01-0.26). Structure anisotropy explained more of the variation in FA IP (median R 2 OS = 0.31, 0.20-0.42). Samples with low R 2 OS for FA IP exhibited low variations throughout the samples and thus low explainable variability, however, this was not the case for MD. Across tumors, CD and SA were clearly associated with MD (R 2 = 0.60) and FA IP (R 2 = 0.81), respectively. In 37% of the samples (6 out of 16), cell density did not explain intra-tumor variability of MD when compared to the degree explained by the CNN. Tumor vascularization, psammoma bodies, microcysts, and tissue cohesivity were associated with bias in MD prediction based solely on CD. Our results support that FA IP is high in the presence of elongated and aligned cell structures, but low otherwise. CONCLUSION: Cell density and structure anisotropy account for variability in MD and FA IP across tumors but cell density does not explain MD variations within the tumor, which means that low or high values of MD locally may not always reflect high or low tumor cell density. Features beyond cell density need to be considered when interpreting MD.
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| 6. |
- Falk Delgado, Anna, et al.
(författare)
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Diagnostic value of alternative techniques to gadolinium-based contrast agents in MR neuroimaging : a comprehensive overview
- 2019
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Ingår i: Insights into Imaging. - : Springer Science and Business Media LLC. - 1869-4101. ; 10:1
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Forskningsöversikt (refereegranskat)abstract
- Gadolinium-based contrast agents (GBCAs) increase lesion detection and improve disease characterization for many cerebral pathologies investigated with MRI. These agents, introduced in the late 1980s, are in wide use today. However, some non-ionic linear GBCAs have been associated with the development of nephrogenic systemic fibrosis in patients with kidney failure. Gadolinium deposition has also been found in deep brain structures, although it is of unclear clinical relevance. Hence, new guidelines from the International Society for Magnetic Resonance in Medicine advocate cautious use of GBCA in clinical and research practice. Some linear GBCAs were restricted from use by the European Medicines Agency (EMA) in 2017.This review focuses on non-contrast-enhanced MRI techniques that can serve as alternatives for the use of GBCAs. Clinical studies on the diagnostic performance of non-contrast-enhanced as well as contrast-enhanced MRI methods, both well established and newly proposed, were included. Advantages and disadvantages together with the diagnostic performance of each method are detailed. Non-contrast-enhanced MRIs discussed in this review are arterial spin labeling (ASL), time of flight (TOF), phase contrast (PC), diffusion-weighted imaging (DWI), magnetic resonance spectroscopy (MRS), susceptibility weighted imaging (SWI), and amide proton transfer (APT) imaging.Ten common diseases were identified for which studies reported comparisons of non-contrast-enhanced and contrast-enhanced MRI. These specific diseases include primary brain tumors, metastases, abscess, multiple sclerosis, and vascular conditions such as aneurysm, arteriovenous malformation, arteriovenous fistula, intracranial carotid artery occlusive disease, hemorrhagic, and ischemic stroke.In general, non-contrast-enhanced techniques showed comparable diagnostic performance to contrast-enhanced MRI for specific diagnostic questions. However, some diagnoses still require contrast-enhanced imaging for a complete examination.
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| 7. |
- Kämpe, Robin, et al.
(författare)
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Quantification of normal cerebral oxygen extraction and oxygen metabolism by phase-based MRI susceptometry: evaluation of repeatability using two different imaging protocols.
- 2017
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Ingår i: Clinical Physiology and Functional Imaging. - : Wiley. - 1475-0961. ; 37:2, s. 220-2011
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Tidskriftsartikel (refereegranskat)abstract
- Global oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO2 ) were quantified in a test-retest study. Cerebral blood flow (CBF) data, required for CMRO2 estimation, were obtained using dynamic susceptibility contrast MRI (DSC-MRI). OEF and CMRO2 were quantified using two separate data sets, that is, conventional high-resolution (HR) gradient echo (GRE) phase maps as well as echo planar imaging (EPI) phase maps taken from the baseline (precontrast) part of the DSC-MRI time series. The EPI phase data were included to elucidate whether an extra HR-GRE scan is needed to obtain information about OEF and CMRO2 , or if this information can be extracted from the DSC-MRI experiment only.
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| 8. |
- Lampinen, Björn, et al.
(författare)
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Probing brain tissue microstructure with MRI: principles, challenges, and the role of multidimensional diffusion-relaxation encoding.
- 2023
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Ingår i: NeuroImage. - 1095-9572. ; 282
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Tidskriftsartikel (refereegranskat)abstract
- Diffusion MRI uses the random displacement of water molecules to sensitize the signal to brain microstructure and to properties such as the density and shape of cells. Microstructure modeling techniques aim to estimate these properties from acquired data by separating the signal between virtual tissue 'compartments' such as the intra-neurite and the extra-cellular space. A key challenge is that the diffusion MRI signal is relatively featureless compared with the complexity of brain tissue. Another challenge is that the tissue microstructure is wildly different within the gray and white matter of the brain. In this review, we use results from multidimensional diffusion encoding techniques to discuss these challenges and their tentative solutions. Multidimensional encoding increases the information content of the data by varying not only the b-value and the encoding direction but also additional experimental parameters such as the shape of the b-tensor and the echo time. Three main insights have emerged from such encoding. First, multidimensional data contradict common model assumptions on diffusion and T2 relaxation, and illustrates how the use of these assumptions cause erroneous interpretations in both healthy brain and pathology. Second, many model assumptions can be dispensed with if data are acquired with multidimensional encoding. The necessary data can be easily acquired in vivo using protocols optimized to minimize Cramér-Rao lower bounds. Third, microscopic diffusion anisotropy reflects the presence of axons but not dendrites. This insight stands in contrast to current 'neurite models' of brain tissue, which assume that axons in white matter and dendrites in gray matter feature highly similar diffusion. Nevertheless, as an axon-based contrast, microscopic anisotropy can differentiate gray and white matter when myelin alterations confound conventional MRI contrasts.
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| 9. |
- Lampinen, Björn, et al.
(författare)
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Towards unconstrained compartment modeling in white matter using diffusion-relaxation MRI with tensor-valued diffusion encoding
- 2020
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Ingår i: Magnetic Resonance in Medicine. - : Wiley. - 0740-3194 .- 1522-2594. ; 84:3, s. 1605-1623
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To optimize diffusion-relaxation MRI with tensor-valued diffusion encoding for precise estimation of compartment-specific fractions, diffusivities, and T2 values within a two-compartment model of white matter, and to explore the approach in vivo. Methods: Sampling protocols featuring different b-values (b), b-tensor shapes (bΔ), and echo times (TE) were optimized using Cramér-Rao lower bounds (CRLB). Whole-brain data were acquired in children, adults, and elderly with white matter lesions. Compartment fractions, diffusivities, and T2 values were estimated in a model featuring two microstructural compartments represented by a “stick” and a “zeppelin.”. Results: Precise parameter estimates were enabled by sampling protocols featuring seven or more “shells” with unique b/bΔ/TE-combinations. Acquisition times were approximately 15 minutes. In white matter of adults, the “stick” compartment had a fraction of approximately 0.5 and, compared with the “zeppelin” compartment, featured lower isotropic diffusivities (0.6 vs. 1.3 μm2/ms) but higher T2 values (85 vs. 65 ms). Children featured lower “stick” fractions (0.4). White matter lesions exhibited high “zeppelin” isotropic diffusivities (1.7 μm2/ms) and T2 values (150 ms). Conclusions: Diffusion-relaxation MRI with tensor-valued diffusion encoding expands the set of microstructure parameters that can be precisely estimated and therefore increases their specificity to biological quantities.
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| 10. |
- Nilsson, Markus, et al.
(författare)
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Imaging brain tumour microstructure
- 2018
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Ingår i: NeuroImage. - : Elsevier BV. - 1053-8119. ; 182, s. 232-250
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Forskningsöversikt (refereegranskat)abstract
- Imaging is an indispensable tool for brain tumour diagnosis, surgical planning, and follow-up. Definite diagnosis, however, often demands histopathological analysis of microscopic features of tissue samples, which have to be obtained by invasive means. A non-invasive alternative may be to probe corresponding microscopic tissue characteristics by MRI, or so called ‘microstructure imaging’. The promise of microstructure imaging is one of ‘virtual biopsy’ with the goal to offset the need for invasive procedures in favour of imaging that can guide pre-surgical planning and can be repeated longitudinally to monitor and predict treatment response. The exploration of such methods is motivated by the striking link between parameters from MRI and tumour histology, for example the correlation between the apparent diffusion coefficient and cellularity. Recent microstructure imaging techniques probe even more subtle and specific features, providing parameters associated to cell shape, size, permeability, and volume distributions. However, the range of scenarios in which these techniques provide reliable imaging biomarkers that can be used to test medical hypotheses or support clinical decisions is yet unknown. Accurate microstructure imaging may moreover require acquisitions that go beyond conventional data acquisition strategies. This review covers a wide range of candidate microstructure imaging methods based on diffusion MRI and relaxometry, and explores advantages, challenges, and potential pitfalls in brain tumour microstructure imaging.
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