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Sökning: WFRF:(van Westen Danielle) > Sundgren Pia

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1.
  • Brabec, Jan, et al. (författare)
  • Coregistered histology sections with diffusion tensor imaging data at 200 µm resolution in meningioma tumors
  • 2023
  • Ingår i: Data in Brief. - 2352-3409. ; 48
  • Tidskriftsartikel (refereegranskat)abstract
    • A significant problem in diffusion MRI (dMRI) is the lack of understanding regarding which microstructural features account for the variability in the diffusion tensor imaging (DTI) parameters observed in meningioma tumors. A common assumption is that mean diffusivity (MD) and fractional anisotropy (FA) from DTI are inversely proportional to cell density and proportional to tissue anisotropy, respectively. Although these associations have been established across a wide range of tumors, they have been challenged for interpreting within-tumor variations where several additional microstructural features have been suggested as contributing to MD and FA.To facilitate the investigation of the biological underpinnings of DTI parameters, we performed ex-vivo DTI at 200 µm isotropic resolution on 16 excised meningioma tumor samples. The samples exhibit a variety of microstructural features because the dataset includes meningiomas of six different meningioma types and two different grades. Diffusion-weighted signal (DWI) maps, DWI maps averaged over all directions for given b-value, signal intensities without diffusion encoding (S0) as well as DTI parameters: MD, FA, in-plane FA (FAIP), axial diffusivity (AD) and radial diffusivity (RD), were coregistered to Hematoxylin & Eosin- (H&E) and Elastica van Gieson-stained (EVG) histological sections by a non-linear landmark-based approach.Here, we provide DWI signal and DTI maps coregistered to histology sections and describe the pipeline for processing the raw DTI data and the coregistration. The raw, processed, and coregistered data are hosted by Analytic Imaging Diagnostics Arena (AIDA) data hub registry, and software tools for processing are provided via GitHub. We hope that data can be used in research and education concerning the link between the meningioma microstructure and parameters obtained by DTI.
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2.
  • Brabec, Jan, et al. (författare)
  • Meningioma microstructure assessed by diffusion MRI : An investigation of the source of mean diffusivity and fractional anisotropy by quantitative histology
  • 2023
  • Ingår i: NeuroImage: Clinical. - : Elsevier BV. - 2213-1582. ; 37
  • 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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3.
  • Falk Delgado, Anna, et al. (författare)
  • Diagnostic value of alternative techniques to gadolinium-based contrast agents in MR neuroimaging : a comprehensive overview
  • 2019
  • Ingår i: Insight into Imaging. - : Springer Science and Business Media LLC. - 1869-4101 .- 1869-4101. ; 10:1
  • 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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4.
  • Follin, Cecilia, et al. (författare)
  • Microstructural white matter alterations associated to neurocognitive deficits in childhood leukemia survivors treated with cranial radiotherapy–a diffusional kurtosis study
  • 2019
  • Ingår i: Acta Oncologica. - 0284-186X. ; 58:7, s. 1021-1028
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Cranial radiotherapy (CRT) is a known risk factor for neurocognitive impairment in survivors of childhood acute lymphoblastic leukemia (ALL). Diffusion tensor imaging (DTI) and diffusional kurtosis imaging (DKI) are MRI techniques that quantify microstructural changes in brain white matter (WM) and DKI is regarded as the more sensitive of them. Our aim was to more thoroughly understand the nature of cognitive deficits after cranial radiotherapy (CRT) in adulthood after childhood ALL. Material and methods: Thirty-eight (21 women) ALL survivors, median age 38 (27–46) years, were investigated at median 34 years after diagnosis. All had been treated with a CRT dose of 24 Gy and with 11 years of complete hormone supplementation. DTI and DKI parameters were determined and neurocognitive tests were performed in ALL survivors and 29 matched controls. Results: ALL survivors scored lower than controls in neurocognitive tests of vocabulary, memory, learning capacity, spatial ability, executive functions, and attention (p <.001). The survivors had altered DTI parameters in the fornix, uncinate fasciculus, and ventral cingulum (all p <.05) and altered DKI parameters in the fornix, uncinate fasciculus, and dorsal and ventral cingulum (p <.05). Altered DTI parameters in the fornix were associated with impaired episodic verbal memory (r = −0.40, p <.04). The left and right uncinate fasciculus (r = 0.6, p <.001), (r = −0.5, p <.02) as well as the right ventral cingulum (r = 0.5, p <.007) were associated with impaired episodic visual memory. Altered DKI parameters in the fornix, right uncinate fasciculus (r = 0.3, r = 0.05, p =.02), and ventral cingulum (r = 0.3, p =.02) were associated with impaired results of episodic visual memory. Conclusion: ALL survivors with cognitive deficits demonstrated microstructural damage in several WM tracts that were more extensive with DKI as compared to DTI; this might be a marker of radiation and chemotherapy neurotoxicity underlying cognitive dysfunction.
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5.
  • Lampinen, Björn, et al. (författare)
  • Neurite density imaging versus imaging of microscopic anisotropy in diffusion MRI : A model comparison using spherical tensor encoding
  • 2017
  • Ingår i: NeuroImage. - : Elsevier BV. - 1095-9572 .- 1053-8119. ; 147, s. 517-531
  • Tidskriftsartikel (refereegranskat)abstract
    • In diffusion MRI (dMRI), microscopic diffusion anisotropy can be obscured by orientation dispersion. Separation of these properties is of high importance, since it could allow dMRI to non-invasively probe elongated structures such as neurites (axons and dendrites). However, conventional dMRI, based on single diffusion encoding (SDE), entangles microscopic anisotropy and orientation dispersion with intra-voxel variance in isotropic diffusivity. SDE-based methods for estimating microscopic anisotropy, such as the neurite orientation dispersion and density imaging (NODDI) method, must thus rely on model assumptions to disentangle these features. An alternative approach is to directly quantify microscopic anisotropy by the use of variable shape of the b-tensor. Along those lines, we here present the 'constrained diffusional variance decomposition' (CODIVIDE) method, which jointly analyzes data acquired with diffusion encoding applied in a single direction at a time (linear tensor encoding, LTE) and in all directions (spherical tensor encoding, STE). We then contrast the two approaches by comparing neurite density estimated using NODDI with microscopic anisotropy estimated using CODIVIDE. Data were acquired in healthy volunteers and in glioma patients. NODDI and CODIVIDE differed the most in gray matter and in gliomas, where NODDI detected a neurite fraction higher than expected from the level of microscopic diffusion anisotropy found with CODIVIDE. The discrepancies could be explained by the NODDI tortuosity assumption, which enforces a connection between the neurite density and the mean diffusivity of tissue. Our results suggest that this assumption invalid, which leads to a NODDI neurite density that is inconsistent between LTE and STE data. Using simulations, we demonstrate that the NODDI assumptions result in parameter bias that precludes the use of NODDI to map neurite density. With CODIVIDE, we found high levels of microscopic anisotropy in white matter, intermediate levels in structures such as the thalamus and the putamen, and low levels in the cortex and in gliomas. We conclude that accurate mapping of microscopic anisotropy requires data acquired with variable shape of the b-tensor.
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6.
  • Lampinen, Björn, et al. (författare)
  • Optimal experimental design for filter exchange imaging: Apparent exchange rate measurements in the healthy brain and in intracranial tumors.
  • 2017
  • Ingår i: Magnetic Resonance in Medicine. - : Wiley. - 1522-2594 .- 0740-3194. ; 77:3, s. 1104-1114
  • Tidskriftsartikel (refereegranskat)abstract
    • PURPOSE: Filter exchange imaging (FEXI) is sensitive to the rate of diffusional water exchange, which depends, eg, on the cell membrane permeability. The aim was to optimize and analyze the ability of FEXI to infer differences in the apparent exchange rate (AXR) in the brain between two populations.METHODS: A FEXI protocol was optimized for minimal measurement variance in the AXR. The AXR variance was investigated by test-retest acquisitions in six brain regions in 18 healthy volunteers. Preoperative FEXI data and postoperative microphotos were obtained in six meningiomas and five astrocytomas.RESULTS: Protocol optimization reduced the coefficient of variation of AXR by approximately 40%. Test-retest AXR values were heterogeneous across normal brain regions, from 0.3 ± 0.2 s-1 in the corpus callosum to 1.8 ± 0.3 s-1 in the frontal white matter. According to analysis of statistical power, in all brain regions except one, group differences of 0.3-0.5 s-1 in the AXR can be inferred using 5 to 10 subjects per group. An AXR difference of this magnitude was observed between meningiomas (0.6 ± 0.1 s-1 ) and astrocytomas (1.0 ± 0.3 s-1 ).CONCLUSIONS: With the optimized protocol, FEXI has the ability to infer relevant differences in the AXR between two populations for small group sizes. Magn Reson Med 77:1104-1114, 2017.
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7.
  • Lampinen, Björn, et al. (författare)
  • Probing brain tissue microstructure with MRI: principles, challenges, and the role of multidimensional diffusion-relaxation encoding.
  • 2023
  • Ingår i: NeuroImage. - 1095-9572. ; 282
  • 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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8.
  • Lätt, Jimmy, et al. (författare)
  • Regional values of diffusional kurtosis estimates in the healthy brain.
  • 2013
  • Ingår i: Journal of Magnetic Resonance Imaging. - : Wiley. - 1522-2586 .- 1053-1807. ; 37:3, s. 610-618
  • Tidskriftsartikel (refereegranskat)abstract
    • PURPOSE: To provide estimates of the diffusional kurtosis in the healthy brain in anatomically defined areas and list these along previously reported values in pathologies. MATERIALS AND METHODS: Thirty-six volunteers (mean age = 33.1 years; range, 19-64 years) underwent diffusional kurtosis imaging. Mean kurtosis (MK), radial kurtosis (RK), mean diffusivity (MD), radial diffusivity (RD), and fractional anisotropy (FA) were determined in 26 anatomical structures. Parameter estimates were assessed regarding age dependence. RESULTS: MK varied from 1.38 in the splenium of the corpus callosum to 0.66 in the caudate head, MD varied from 0.68 to 0.62 μm(2) /ms and FA from 0.87 to 0.29. MK, and FA showed a strong positive correlation, RK and RD a strong negative correlation. Parameter estimates showed age correlation in some regions; also the average MK and RK for all WM and all GM areas, respectively, were negatively correlated with age. CONCLUSION: DKI parameter estimates MK and RK varied depending on the anatomical region and varied with age in pooled WM and GM data. MK estimates in the internal capsule, corpus callosum, and thalamus were consistent with previous studies. The range of values of MK and RK in healthy brain overlapped with that in pathologies. J. Magn. Reson. Imaging 2012. © 2012 Wiley Periodicals, Inc.
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9.
  • Mårtensson, Johanna, et al. (författare)
  • Spatial analysis of diffusion tensor tractography statistics along the inferior fronto-occipital fasciculus with application in progressive supranuclear palsy
  • 2013
  • Ingår i: Magnetic Resonance Materials in Physics, Biology and Medicine. - : Springer Science and Business Media LLC. - 0968-5243 .- 1352-8661. ; 26:6, s. 527-537
  • Tidskriftsartikel (refereegranskat)abstract
    • The purpose of the study was to develop a method for analysis of diffusion parameters along white matter (WM) tracts, using spatial normalization based on anatomical landmarks, and to introduce the apparent area coefficient (AAC). The method's applicability was tested in the inferior fronto-occipital fasciculus (IFO) in patients with progressive supranuclear palsy (PSP) and healthy controls (HCs). A framework for analysis of diffusion parameters was developed. Spatial normalization of the tracts was performed using anatomical landmarks, to avoid deformations caused by cerebral atrophy. Initially, 38 HCs were used to optimize a threshold for the minimal size of regions that differ between groups. The fractional anisotropy, mean diffusivity, AAC, and the hemispheric asymmetry index (AI), were compared between 11 PSP patients and 15 HCs. The method was feasible for analysis of PSP patients and HCs. The AI showed that the observed hemispheric asymmetry of AAC was significantly larger in PSP patients compared with HCs in small regions of the IFO. The method was successfully employed for analysis of diffusion parameters along the IFO in a patient group. This method can be potentially useful in studies of WM diseases, with or without cerebral atrophy.
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10.
  • Nilsson, Markus, et al. (författare)
  • Imaging brain tumour microstructure
  • 2018
  • Ingår i: NeuroImage. - : Elsevier BV. - 1053-8119. ; 182, s. 232-250
  • 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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