SwePub
Sök i SwePub databas

  Utökad sökning

Träfflista för sökning "WFRF:(Englund Elisabet) ;pers:(Bengzon Johan)"

Sökning: WFRF:(Englund Elisabet) > Bengzon Johan

  • Resultat 1-8 av 8
Sortera/gruppera träfflistan
   
NumreringReferensOmslagsbildHitta
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.
  •  
2.
  • Brabec, Jan, et al. (författare)
  • Histogram analysis of tensor-valued diffusion MRI in meningiomas : Relation to consistency, histological grade and type
  • 2022
  • Ingår i: NeuroImage: Clinical. - : Elsevier BV. - 2213-1582. ; 33
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Preoperative radiological assessment of meningioma characteristics is of value for pre- and post-operative patient management, counselling, and surgical approach.PURPOSE: To investigate whether tensor-valued diffusion MRI can add to the preoperative prediction of meningioma consistency, grade and type.MATERIALS AND METHODS: 30 patients with intracranial meningiomas (22 WHO grade I, 8 WHO grade II) underwent MRI prior to surgery. Diffusion MRI was performed with linear and spherical b-tensors with b-values up to 2000 s/mm2. The data were used to estimate mean diffusivity (MD), fractional anisotropy (FA), mean kurtosis (MK) and its components-the anisotropic and isotropic kurtoses (MKA and MKI). Meningioma consistency was estimated for 16 patients during resection based on ultrasonic aspiration intensity, ease of resection with instrumentation or suction. Grade and type were determined by histopathological analysis. The relation between consistency, grade and type and dMRI parameters was analyzed inside the tumor ("whole-tumor") and within brain tissue in the immediate periphery outside the tumor ("rim") by histogram analysis.RESULTS: Lower 10th percentiles of MK and MKA in the whole-tumor were associated with firm consistency compared with pooled soft and variable consistency (n = 7 vs 9; U test, p = 0.02 for MKA 10 and p = 0.04 for MK10) and lower 10th percentile of MD with variable against soft and firm (n = 5 vs 11; U test, p = 0.02). Higher standard deviation of MKI in the rim was associated with lower grade (n = 22 vs 8; U test, p = 0.04) and in the MKI maps we observed elevated rim-like structure that could be associated with grade. Higher median MKA and lower median MKI distinguished psammomatous type from other pooled meningioma types (n = 5 vs 25; U test; p = 0.03 for MKA 50 and p = 0.03 and p = 0.04 for MKI 50).CONCLUSION: Parameters from tensor-valued dMRI can facilitate prediction of consistency, grade and type.
  •  
3.
  • 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.
  •  
4.
  • Durmo, Faris, et al. (författare)
  • Assessment of Amide proton transfer weighted (APTw) MRI for pre-surgical prediction of final diagnosis in gliomas
  • 2020
  • Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 15:12
  • Tidskriftsartikel (refereegranskat)abstract
    • PURPOSE: Radiological assessment of primary brain neoplasms, both high (HGG) and low grade tumors (LGG), based on contrast-enhancement alone can be inaccurate. We evaluated the radiological value of amide proton transfer weighted (APTw) MRI as an imaging complement for pre-surgical radiological diagnosis of brain tumors.METHODS: Twenty-six patients were evaluated prospectively; (22 males, 4 females, mean age 55 years, range 26-76 years) underwent MRI at 3T using T1-MPRAGE pre- and post-contrast administration, conventional T2w, FLAIR, and APTw imaging pre-surgically for suspected primary/secondary brain tumor. Assessment of the additional value of APTw imaging compared to conventional MRI for correct pre-surgical brain tumor diagnosis. The initial radiological pre-operative diagnosis was based on the conventional contrast-enhanced MR images. The range, minimum, maximum, and mean APTw signals were evaluated. Conventional normality testing was performed; with boxplots/outliers/skewness/kurtosis and a Shapiro-Wilk's test. Mann-Whitney U for analysis of significance for mean/max/min and range APTw signal. A logistic regression model was constructed for mean, max, range and Receiver Operating Characteristic (ROC) curves calculated for individual and combined APTw signals.RESULTS: Conventional radiological diagnosis prior to surgery/biopsy was HGG (8 patients), LGG (12 patients), and metastasis (6 patients). Using the mean and maximum: APTw signal would have changed the pre-operative evaluation the diagnosis in 8 of 22 patients (two LGGs excluded, two METs excluded). Using a cut off value of >2.0% for mean APTw signal integral, 4 of the 12 radiologically suspected LGG would have been diagnosed as high grade glioma, which was confirmed by histopathological diagnosis. APTw mean of >2.0% and max >2.48% outperformed four separate clinical radiological assessments of tumor type, P-values = .004 and = .002, respectively.CONCLUSIONS: Using APTw-images as part of the daily clinical pre-operative radiological evaluation may improve diagnostic precision in differentiating LGGs from HGGs, with potential improvement of patient management and treatment.
  •  
5.
  • Durmo, Faris, et al. (författare)
  • Brain Tumor Characterization Using Multibiometric Evaluation of MRI
  • 2018
  • Ingår i: Tomography : a journal for imaging research. - : MDPI AG. - 2379-1381. ; 4:1, s. 14-25
  • Tidskriftsartikel (refereegranskat)abstract
    • The aim was to evaluate volume, diffusion, and perfusion metrics for better presurgical differentiation between high-grade gliomas (HGG), low-grade gliomas (LGG), and metastases (MET). For this retrospective study, 43 patients with histologically verified intracranial HGG (n = 18), LGG (n = 10), and MET (n = 15) were chosen. Preoperative magnetic resonance data included pre- and post-gadolinium contrast-enhanced T1-weighted fluid-attenuated inversion recover, cerebral blood flow (CBF), cerebral blood volume (CBV), fractional anisotropy, and apparent diffusion coefficient maps used for quantification of magnetic resonance biometrics by manual delineation of regions of interest. A binary logistic regression model was applied for multiparametric analysis and receiver operating characteristic (ROC) analysis. Statistically significant differences were found for normalized-ADC-tumor (nADC-T), normalized-CBF-tumor (nCBF-T), normalized-CBV-tumor (nCBV-T), and normalized-CBF-edema (nCBF-E) between LGG and HGG, and when these metrics were combined, HGG could be distinguished from LGG with a sensitivity and specificity of 100%. The only metric to distinguish HGG from MET was the normalized-ADC-E with a sensitivity of 68.8% and a specificity of 80%. LGG can be distinguished from MET by combining edema volume (Vol-E), Vol-E/tumor volume (Vol-T), nADC-T, nCBF-T, nCBV-T, and nADC-E with a sensitivity of 93.3% and a specificity of 100%. The present study confirms the usability of a multibiometric approach including volume, perfusion, and diffusion metrics in differentially diagnosing brain tumors in preoperative patients and adds to the growing body of evidence in the clinical field in need of validation and standardization.
  •  
6.
  • Durmo, Faris, et al. (författare)
  • Multivoxel 1H-MR Spectroscopy Biometrics for Preoprerative Differentiation Between Brain Tumors
  • 2018
  • Ingår i: Tomography : a journal for imaging research. - : MDPI AG. - 2379-1381. ; 4:4, s. 172-181
  • Tidskriftsartikel (refereegranskat)abstract
    • We investigated multivoxel proton magnetic resonance spectroscopy (1H-MRS) biometrics for preoperative differentiation and prognosis of patients with brain metastases (MET), low-grade glioma (LGG) and high-grade glioma (HGG). In total, 33 patients (HGG, 14; LGG, 9; and 10 MET) were included. 1H-MRS imaging (MRSI) data were assessed and neurochemical profiles for metabolites N-acetyl aspartate (NAA) + NAAG(NAA), Cr + PCr(total creatine, tCr), Glu + Gln(Glx), lactate (Lac), myo-inositol(Ins), GPC + PCho(total choline, tCho), and total lipids, and macromolecule (tMM) signals were estimated. Metabolites were reported as absolute concentrations or ratios to tCho or tCr levels. Voxels of interest in an MRSI matrix were labeled according to tissue. Logistic regression, receiver operating characteristic, and Kaplan-Meier survival analysis was performed. Across HGG, LGG, and MET, average Ins/tCho was shown to be prognostic for overall survival (OS): low values (≤1.29) in affected hemisphere predicting worse OS than high values (>1.29), (log rank < 0.007). Lip/tCho and Ins/tCho combined showed 100% sensitivity and specificity for both HGG/LGG (P < .001) and LGG/MET (P < .001) measured in nonenhancing/contrast-enhancing lesional tissue. Combining tCr/tCho in perilesional edema with tCho/tCr and NAA/tCho from ipsilateral normal- appearing tissue yielded 100% sensitivity and 81.8% specificity (P < .002) for HGG/MET. Best single biomarker: Ins/tCho for HGG/LGG and total lipid/tCho for LGG/MET showed 100% sensitivity and 75% and 100% specificity, respectively. HGG/MET; NAA/tCho showed 75% sensitivity and 84.6% specificity. Multivoxel 1H-MRSI provides prognostic information for OS for HGG/LGG/MET and a multibiometric approach for differentiation may equal or outperform single biometrics.
  •  
7.
  • Pfenninger, Cosima, et al. (författare)
  • CD133 is not present on neurogenic astrocytes in the adult subventricular zone, but on embryonic neural stem cells, ependymal cells, and glioblastoma cells
  • 2007
  • Ingår i: Cancer Research. - 1538-7445. ; 67:12, s. 5727-5736
  • Tidskriftsartikel (refereegranskat)abstract
    • Human brain tumor stem cells have been enriched using antibodies against the surface protein CD133. An antibody recognizing CD133 also served to isolate normal neural stem cells from fetal human brain, suggesting a possible lineage relationship between normal neural and brain tumor stem cells. Whether CD133-positive brain tumor stem cells can be derived from CD133-positive neural stem or progenitor cells still requires direct experimental evidence, and an important step toward such investigations is the identification and characterization of normal CD133-presenting cells in neurogenic regions of the embryonic and adult brain. Here, we present evidence that CD133 is a marker for embryonic neural stem cells, an intermediate radial glial/ependymal cell type in the early postnatal stage, and for ependymal cells in the adult brain, but not for neurogenic astrocytes in the adult subventricular zone. Our findings suggest two principal possibilities for the origin of brain tumor stem cells: a derivation from CD133-expressing cells, which are normally not present in the adult brain (embryonic neural stem cells and an early postnatal intermediate radial glial/ependymal cell type), or from CD133-positive ependymal cells in the adult brain, which are, however, generally regarded as postmitotic. Alternatively, brain tumor stem cells could be derived from proliferative but CD133-negative neurogenic astrocytes in the adult brain. In the latter case, brain tumor development would involve the production of CD133.
  •  
8.
  • Wickham, Jenny, et al. (författare)
  • Inhibition of epileptiform activity by neuropeptide Y in brain tissue from drug-resistant temporal lobe epilepsy patients
  • 2019
  • Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1
  • Tidskriftsartikel (refereegranskat)abstract
    • In epilepsy patients, drug-resistant seizures often originate in one of the temporal lobes. In selected cases, when certain requirements are met, this area is surgically resected for therapeutic reasons. We kept the resected tissue slices alive in vitro for 48 h to create a platform for testing a novel treatment strategy based on neuropeptide Y (NPY) against drug-resistant epilepsy. We demonstrate that NPY exerts a significant inhibitory effect on epileptiform activity, recorded with whole-cell patch-clamp, in human hippocampal dentate gyrus. Application of NPY reduced overall number of paroxysmal depolarising shifts and action potentials. This effect was mediated by Y2 receptors, since application of selective Y2-receptor antagonist blocked the effect of NPY. This proof-of-concept finding is an important translational milestone for validating NPY-based gene therapy for targeting focal drug-resistant epilepsies, and increasing the prospects for positive outcome in potential clinical trials.
  •  
Skapa referenser, mejla, bekava och länka
  • Resultat 1-8 av 8

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy