Analyse von Tumormausmodellen mittels dynamischer MRT und einer dedizierten Softwareplattform
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Philipps-Universität Marburg
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Abstract
Purpose: To implement a software platform (DynaVision) dedicate to analyze data from functional imaging of tumors with different mathematical approaches, and to test the software platform in pancreatic carcinoma xenografts in mice with severe combined immunodeficiency disease (SCID). Materials and
Methods: A software program was developed for extraction and visualization of tissue perfusion parameters from dynamic contrast-enhanced images. This includes regional parameter calculationfrom enhancement curves, parametric images (e. g., blood flow), animation, 3Dvisualization, two-compartment modeling, a mode for comparing different datasets (e. g., therapy monitoring),and motion correction. We analyzed xenograft tumors from two pancreatic carcinoma cell lines (BxPC3 and ASPC1) implanted in 14 SCIDmice after injection of Gd-DTPA into the tail
vein. These data were correlated with histopathological findings.
Results: Image analysis was completed in approximately 15 minutes per data set. The possibility of drawing and editing ROIs within the whole data set makes it easy to obtain quantitative data from the intensity-time curves. In one animal, motion artifacts reduced the image quality to a greater extent but data
analysis was still possible after motion correction. Dynamic MRI of mice tumor models revealed a highly heterogeneous distribution of the contrast-enhancement curves and derived parameters, which correlated with differences in histopathology. ASPC1 tumors showed a more hypervascular type of curves
with faster and higher signal enhancement rate (wash-in) and a faster signal decrease (wash-out). BXPC3 tumors showed a more hypovascular type with slower wash-in and wash-out. This correlated with the biological properties of the tumors.
Conclusion: With the described software, it was possible to analyze tissue
perfusion parameters in small xenograft tumor models in mice. Our data correlated with histopathological data, and the qualitative and quantitative perfusion parameters could distinguish two tumor entities with different growth characteristics.
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Created: 2008Issued: 2008-05-20Updated: 2011-08-10
Faculty
Medizin
Publisher
Philipps-Universität Marburg
Language
ger
Data types
DoctoralThesis
Keywords
Tierexperimentelle StudienPancreasPankreasNeoplasmsDatenanalyseMagnetic resonance (MR)Data analysisNeoplasmenExperimental studies
DFG-subjects
NMR-Tomographie
DDC-Numbers
610
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Maurer, Elisabeth (134282264): Analyse von Tumormausmodellen mittels dynamischer MRT und einer dedizierten Softwareplattform. : Philipps-Universität Marburg 2008-05-20. DOI: https://doi.org/10.17192/z2008.0322.
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This item has been published with the following license: In Copyright