Atlas registration for edema-corrected MRI lesion volume in mouse stroke models

Lesion volume measurements with magnetic resonance imaging are widely used to assess outcome in rodent models of stroke. In this study, we improved a mathematical framework to correct lesion size for edema which is based on manual delineation of the lesion and hemispheres. Furthermore, a novel MATLAB toolbox to register mouse brain MR images to the Allen brain atlas is presented. Its capability to calculate edema-corrected lesion size was compared to the manual approach. Automated image registration performed equally well in in a mouse middle cerebral artery occlusion model (Pearson r=0.976, p=2.265e-11). Information encapsulated in the registration was used to generate maps of edema induced tissue volume changes. These showed discrepancies to simplified tissue models underlying the manual approach. The presented techniques provide biologically more meaningful, voxel-wise biomarkers of vasogenic edema after stroke

Atlas registration for edema-corrected MRI lesion volume in mouse stroke models

Lesion volume measurements with magnetic resonance imaging are widely used to assess outcome in rodent models of stroke. In this study, we improved a mathematical framework to correct lesion size for edema which is based on manual delineation of the lesion and hemispheres. Furthermore, a novel MATLAB toolbox to register mouse brain MR images to the Allen brain atlas is presented. Its capability to calculate edema-corrected lesion size was compared to the manual approach. Automated image registration performed equally well in in a mouse middle cerebral artery occlusion model (Pearson r=0.976, p=2.265e-11). Information encapsulated in the registration was used to generate maps of edema induced tissue volume changes. These showed discrepancies to simplified tissue models underlying the manual approach. The presented techniques provide biologically more meaningful, voxel-wise biomarkers of vasogenic edema after stroke

Cellular heterogeneity contributes to subtype-specific expression of ZEB1 in human glioblastoma.

The transcription factor ZEB1 has gained attention in tumor biology of epithelial cancers because of its function in epithelial-mesenchymal transition, DNA repair, stem cell biology and tumor-induced immunosuppression, but its role in gliomas with respect to invasion and prognostic value is controversial. We characterized ZEB1 expression at single cell level in 266 primary brain tumors and present a comprehensive dataset of high grade gliomas with Ki67, p53, IDH1, and EGFR immunohistochemistry, as well as EGFR FISH. ZEB1 protein expression in glioma stem cell lines was compared to their parental tumors with respect to gene expression subtypes based on RNA-seq transcriptomic profiles. ZEB1 is widely expressed in glial tumors, but in a highly variable fraction of cells. In glioblastoma, ZEB1 labeling index is higher in tumors with EGFR amplification or IDH1 mutation. Co-labeling studies showed that tumor cells and reactive astroglia, but not immune cells contribute to the ZEB1 positive population. In contrast, glioma cell lines constitutively express ZEB1 irrespective of gene expression subtype. In conclusion, our data indicate that immune infiltration likely contributes to differential labelling of ZEB1 and confounds interpretation of bulk ZEB1 expression data

Publication Data from Koch et al 2017

<p>Contains the dataset and the MATLAB toolbox used for Koch et al. (2017) "Atlas registration for edema corrected MRI lesion volume in mouse stroke models"</p> <p><strong>data_koch_et_al_jcbfm_2017.zip</strong></p> <p>T2 weighted MRI data in NIFTI format from stroke mice 24 h post surgery. Contains raw data (images before registration, manually delineated hemisphere and lesion masks) and processed data (automatically generated brain mask and an additional version of raw images in registration to the Allen mouse brain atlas). Also contains a copy of some datasets for which slices in the image stack were removed. Includes an excel file describing the group assignment of each mouse (middle cerebral artery occlusion, photothrombosis or sham, full number of slices or partial number of slices) and describing files for each mouse. Histological data (TTC stainings) and corresponding regions of interest in ImageJ format are stored in a separate folder.</p> <p><strong>Toolbox available at GITHUB</strong></p> <p>https://github.com/philippboehmsturm/antx</p> <p>When downloading the toolbox at GITHUB please respect legal issues and carefully read the provided README file.</p

Expression of ZEB1 in human glial tumors and normal brain.

<p>(A) Biopsy samples of human glial tumors show abundant nuclear expression of ZEB1. Sections from non-neoplastic normal brain show weak cytoplasmic staining of neurons and nuclear expression in astrocytes. (B) Quantification of ZEB1 in full histological sections of gross total resections of human glial tumors. ZEB1 positive cells were quantified using automated image analysis. Dots represent the mean of multiple regions of interest (ROI) per tumor. Box plots show the distribution of the ZEB1 labelling in tumor with indicated integrated diagnosis according the 2016 WHO classification of CNS tumors [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0185376#pone.0185376.ref029" target="_blank">29</a>]. (C) <i>ZEB1</i> mRNA expression in public GBM cDNA microarray datasets. Boxplots show distribution in normal brain vs. GBM. Data were retrieved via the GlioVis portal [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0185376#pone.0185376.ref030" target="_blank">30</a>].</p

ZEB1 expression in the tumor microenvironment.

<p>(A) Cell type specific expression of ZEB1 in reactive brain tissue. Human brain biopsy samples from cases of seizure-induced reactive gliosis or subacute infarction were co-stained for ZEB1 and Iba1 for microglia, CD45 for leucocytes, CD68 for macrophages and GFAP for astrocytes, respectively. Scale bars 50 μm. (B) Co-labeling of ZEB1 and CD68 or HLA-DR, respectively in human GBM. (C,D) Correlation of microarray-based gene expression levels of <i>ZEB1</i> and myeloid cell markers <i>CD68</i> (C) and <i>AIF1</i> (D), respectively. Processed log₂-transformed intensities from 157 GBM cases studied by Gravendeel et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0185376#pone.0185376.ref034" target="_blank">34</a>] were obtained via the GlioVis portal [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0185376#pone.0185376.ref030" target="_blank">30</a>].</p

Intratumoral heterogeneity of ZEB1 expression.

<p>(A) Co-labeling of IDH1 R132H and ZEB1 in a case of IDH1 mutant glioblastoma. The image shown has been taken from one out of ten fields of view that were subjected to separate and blinded manual scoring of mutant IDH1 and ZEB1 expression. (B) ZEB1 gradient along the tumor edge of a mesenchymal GBM (BLN-7 parental tumor). ZEB1 IHC, overall cellularity (<i>blue</i>), the relative frequency of ZEB1+ cells (<i>red</i>) and the mean nuclear intensity of ZEB1+ cells (<i>green</i>) at the tumor edge are shown. (C,D) Expression of ZEB1 (<i>pink</i>) and CD68 (<i>brown</i>) in perinecrotic regions with (C) or without (D) pseudopalisades.</p

Intertumoral heterogeneity of ZEB1 expression.

<p>(A) Box plots of ZEB1 labelling index (percent) with respect to EGFR amplification and IDH1 mutation. (B,C) Correlation of ZEB1 expression and Ki67 labelling index or cellularity, respectively, in N = 193 glioblastoma TMA samples. Trend lines indicate linear regression estimates. Note log scale for Ki67 index. (D) Kaplan-Meier estimates of overall survival time (months) with respect to ZEB1 expression. The observed data range of ZEB1⁺ percentages was split into two equally sized bins at the threshold value of 49%.</p