title: Pattern analysis accounts for heterogeneity observed in MRI studies of tumor angiogenesis.
abstract: MRI is a method of choice for assessing anatomical structures or angiogenesis-related parameters noninvasively during tumor progression. Typically, tumor tissue displays a high degree of heterogeneity that can be evaluated using pattern analysis (PA), which comprises shape and texture analysis. This work aims at implementing PA methods to study angiogenesis in a murine tumor model and testing its sensitivity with regard to detecting changes elicited by administration of a drug. Twelve balb/c-nude mice were injected subcutaneously with 10(6) C51 cells (colon carcinoma). A first group (N = 6) of animals was treated with dimethyloxalylglycine, a drug known to stabilize hypoxia-inducible-factor-α, which among other functions, is involved in angiogenesis. The second group (N = 6) was treated with saline. MRI experiments assessing tumor blood volume and permeability-maps (K(trans) ) were performed immediately before and 6 days after drug treatment. Data have been analyzed using standard histogram analysis and PA. Standard histogram analysis did not reveal any difference between the two groups, neither before nor after the treatment. In contrast, PA revealed significant differences between drug and placebo treated mice in the texture of the TBV and K(trans) maps after drug treatment, but not with regard to tumors shapes. The results indicated that in view of the heterogeneity of tumor tissue, standard histogram analysis appears insensitive in picking-up differences in response to treatment, while PA appears to be particularly sensitive to changes in texture.
authors.affiliation: Institute for Biomedical Engineering, University of Zurich and ETH, Zurich, Switzerland.
authors.forename: Marco
authors.initials: M
authors.lastname: Dominietto
authors.forename: Steffi
authors.initials: S
authors.lastname: Lehmann
authors.forename: Ruth
authors.initials: R
authors.lastname: Keist
authors.forename: Markus
authors.initials: M
authors.lastname: Rudin
mesh_terms: D000465:Algorithms; D000600:Amino Acids, Dicarboxylic / Q000627:therapeutic use*; D020533:Angiogenesis Inhibitors / Q000627:therapeutic use; D000818:Animals; D045744:Cell Line, Tumor; D003110:Colonic Neoplasms / Q000150:complications / Q000188:drug therapy* / Q000473:pathology*; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D051379:Mice; D008807:Mice, Inbred BALB C; D008819:Mice, Nude; D009389:Neovascularization, Pathologic / Q000150:complications / Q000188:drug therapy* / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016896:Treatment Outcome; D047368:Tumor Burden
chemical_list: D000600:Amino Acids, Dicarboxylic; D020533:Angiogenesis Inhibitors; C040947:oxalylglycine
keywords: MRI; fractal dimension; lacunarity; mice; pattern analysis; tumor angiogenesis