Grabbe, Eckhardt

[["dc.bibliographiccitation.artnumber","e118"],["dc.bibliographiccitation.firstpage","1232"],["dc.bibliographiccitation.issue","7"],["dc.bibliographiccitation.journal","PLoS Genetics"],["dc.bibliographiccitation.lastpage","1243"],["dc.bibliographiccitation.volume","3"],["dc.contributor.author","Dullin, Christian"],["dc.contributor.author","Missbach-Guentner, Jeannine"],["dc.contributor.author","Vogel, Wolfgang F."],["dc.contributor.author","Grabbe, Eckhardt"],["dc.contributor.author","Alves, Frauke"],["dc.date.accessioned","2018-11-07T11:01:18Z"],["dc.date.available","2018-11-07T11:01:18Z"],["dc.date.issued","2007"],["dc.description.abstract","Rapid progress in exploring the human and mouse genome has resulted in the generation of a multitude of mouse models to study gene functions in their biological context. However, effective screening methods that allow rapid noninvasive phenotyping of transgenic and knockout mice are still lacking. To identify murine models with bone alterations in vivo, we used flat-panel volume computed tomography (fpVCT) for high-resolution 3-D imaging and developed an algorithm with a computational intelligence system. First, we tested the accuracy and reliability of this approach by imaging discoidin domain receptor 2-(DDR2-) deficient mice, which display distinct skull abnormalities as shown by comparative landmark-based analysis. High-contrast fpVCT data of the skull with 200 mu m isotropic resolution and 8-s scan time allowed segmentation and computation of significant shape features as well as visualization of morphological differences. The application of a trained artificial neuronal network to these datasets permitted a semiautomatic and highly accurate phenotype classification of DDR2-deficient compared to C57BL/6 wild-type mice. Even heterozygous DDR2 mice with only subtle phenotypic alterations were correctly determined by fpVCT imaging and identified as a new class. In addition, we successfully applied the algorithm to classify knockout mice lacking the DDR1 gene with no apparent skull deformities. Thus, this new method seems to be a potential tool to identify novel mouse phenotypes with skull changes from transgenic and knockout mice on the basis of random mutagenesis as well as from genetic models. However for this purpose, new neuronal networks have to be created and trained. In summary, the combination of fpVCT images with artificial neuronal networks provides a reliable, novel method for rapid, cost-effective, and noninvasive primary screening tool to detect skeletal phenotypes in mice."],["dc.identifier.doi","10.1371/journal.pgen.0030118"],["dc.identifier.isi","000248350000010"],["dc.identifier.pmid","17658952"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/8443"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/51120"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.publisher","Public Library Science"],["dc.relation.issn","1553-7390"],["dc.rights","CC BY 2.5"],["dc.rights.uri","https://creativecommons.org/licenses/by/2.5"],["dc.title","Semi-automatic classification of skeletal morphology in genetically altered mice using flat-panel volume computed tomography"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","663"],["dc.bibliographiccitation.issue","7"],["dc.bibliographiccitation.journal","Neoplasia"],["dc.bibliographiccitation.lastpage","673"],["dc.bibliographiccitation.volume","10"],["dc.contributor.author","Missbach-Guentner, Jeannine"],["dc.contributor.author","Dullin, Christian"],["dc.contributor.author","Kimmina, Sarah"],["dc.contributor.author","Zientkowska, Marta"],["dc.contributor.author","Domeyer-Missbach, Melanie"],["dc.contributor.author","Malz, Cordula"],["dc.contributor.author","Grabbe, Eckhardt"],["dc.contributor.author","Stühmer, Walter"],["dc.contributor.author","Alves, Frauke"],["dc.date.accessioned","2019-07-10T08:11:50Z"],["dc.date.available","2019-07-10T08:11:50Z"],["dc.date.issued","2008"],["dc.description.abstract","Noninvasive methods are strongly needed to detect and quantify not only tumor growth in murine tumor models but also the development of vascularization and necrosis within tumors. This study investigates the use of a new imaging technique, flat-panel detector volume computed tomography (fpVCT), to monitor in vivo tumor progression and structural changes within tumors of two murine carcinoma models. After tumor cell inoculation, single fpVCT scans of the entire mice were performed at different time points. The acquired isotropic, high-resolution volume data sets enable an accurate real-time assessment and precise measurements of tumor volumes. Spreading of contrast agent-containing blood vessels around and within the tumors was clearly visible over time. Furthermore, fpVCT permits the identification of differences in the uptake of contrast media within tumors, thus delineating necrosis, tumor tissues, and blood vessels. Classification of tumor tissues based on the decomposition of the underlying mixture distribution of tissue-related Hounsfield units allowed the quantitative acquisition of necrotic tissues at each time point. Morphologic alterations of the tumor depicted by fpVCT were confirmed by histopathologic examination. Concluding, our data show that fpVCT may be highly suitable for the noninvasive evaluation of tumor responses to anticancer therapies during the course of the disease."],["dc.identifier.doi","10.1593/neo.08270"],["dc.identifier.pii","S1476558608800048"],["dc.identifier.pmid","18592006"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/11245"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/60806"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/102991"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.issn","1476-5586"],["dc.relation.orgunit","Universitätsmedizin Göttingen"],["dc.rights","Goescholar"],["dc.title","Morphologic changes of mammary carcinomas in mice over time as monitored by flat-panel detector volume computed tomography."],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","755"],["dc.bibliographiccitation.issue","9"],["dc.bibliographiccitation.journal","Neoplasia (New York, N.Y.)"],["dc.bibliographiccitation.lastpage","765"],["dc.bibliographiccitation.volume","9"],["dc.contributor.author","Missbach-Guentner, Jeannine"],["dc.contributor.author","Dullin, Christian"],["dc.contributor.author","Zientkowska, Marta"],["dc.contributor.author","Domeyer-Missbach, Melanie"],["dc.contributor.author","Kimmina, Sarah"],["dc.contributor.author","Obenauer, Silvia"],["dc.contributor.author","Kauer, Fritz"],["dc.contributor.author","Stühmer, Walter"],["dc.contributor.author","Grabbe, Eckhardt"],["dc.contributor.author","Vogel, Wolfgang F."],["dc.contributor.author","Alves, Frauke"],["dc.date.accessioned","2019-07-10T08:11:50Z"],["dc.date.available","2019-07-10T08:11:50Z"],["dc.date.issued","2007-09-01"],["dc.description.abstract","Skeletal metastasis is an important cause of mortality in patients with breast cancer. Hence, animal models, in combination with various imaging techniques, are in high demand for preclinical assessment of novel therapies. We evaluated the applicability of flat-panel volume computed tomography (fpVCT) to noninvasive detection of osteolytic bone metastases that develop in severe immunodeficient mice after intracardial injection of MDA-MB-231 breast cancer cells. A single fpVCT scan at 200-microm isotropic resolution was employed to detect osteolysis within the entire skeleton. Osteolytic lesions identified by fpVCT correlated with Faxitron X-ray analysis and were subsequently confirmed by histopathological examination. Isotropic three-dimensional image data sets obtained by fpVCT were the basis for the precise visualization of the extent of the lesion within the cortical bone and for the measurement of bone loss. Furthermore, fpVCT imaging allows continuous monitoring of growth kinetics for each metastatic site and visualization of lesions in more complex regions of the skeleton, such as the skull. Our findings suggest that fpVCT is a powerful tool that can be used to monitor the occurrence and progression of osteolytic lesions in vivo and can be further developed to monitor responses to antimetastatic therapies over the course of the disease."],["dc.identifier.pmid","17898871"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/11246"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/60807"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.issn","1476-5586"],["dc.relation.orgunit","Deutsches Primatenzentrum"],["dc.relation.orgunit","Universitätsmedizin Göttingen"],["dc.rights","Goescholar"],["dc.subject.mesh","Adenocarcinoma"],["dc.subject.mesh","Animals"],["dc.subject.mesh","Bone Neoplasms"],["dc.subject.mesh","Breast Neoplasms"],["dc.subject.mesh","Disease Progression"],["dc.subject.mesh","Female"],["dc.subject.mesh","Femoral Neoplasms"],["dc.subject.mesh","Humerus"],["dc.subject.mesh","Imaging, Three-Dimensional"],["dc.subject.mesh","Mice"],["dc.subject.mesh","Mice, SCID"],["dc.subject.mesh","Models, Animal"],["dc.subject.mesh","Osteolysis"],["dc.subject.mesh","Skull Neoplasms"],["dc.subject.mesh","Specific Pathogen-Free Organisms"],["dc.subject.mesh","Tibia"],["dc.subject.mesh","Tomography, X-Ray Computed"],["dc.subject.mesh","Tumor Burden"],["dc.title","Flat-panel detector-based volume computed tomography: a novel 3D imaging technique to monitor osteolytic bone lesions in a mouse tumor metastasis model."],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]