Cluster analysis of quantitative parametric maps from DCE-MRI: application in evaluating heterogeneity of tumor response to antiangiogenic treatment

• Published in: Magnetic resonance imaging 2015-07, Vol.33 (6), p.725-736
• Main Authors: Longo, Dario Livio, Dastrù, Walter, Consolino, Lorena, Espak, Miklos, Arigoni, Maddalena, Cavallo, Federica, Aime, Silvio
• Format: Article
• Language: English
• Subjects: Angiogenesis Inhibitors - therapeutic use; Animals; Antiangiogenic; Breast Neoplasms - drug therapy; Cluster Analysis; Clustering; Contrast Media - pharmacokinetics; DCE-MRI; Disease Models, Animal; Gadolinium - pharmacokinetics; Gd-complexes; Image Enhancement - methods; Magnetic Resonance Imaging; Mice; Mice, Inbred BALB C; Pharmacokinetic modeling; Radiology; Tumor heterogeneity
• ISSN: 0730-725X; 1873-5894
• DOI: 10.1016/j.mri.2015.03.005

Abstract Purpose The objective of this study was to compare a clustering approach to conventional analysis methods for assessing changes in pharmacokinetic parameters obtained from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) during antiangiogenic treatment in a breast cancer model. Materials and methods BALB/c mice bearing established transplantable her2+ tumors were treated with a DNA-based antiangiogenic vaccine or with an empty plasmid (untreated group). DCE-MRI was carried out by administering a dose of 0.05 mmol/kg of Gadocoletic acid trisodium salt, a Gd-based blood pool contrast agent (CA) at 1 T. Changes in pharmacokinetic estimates (Ktrans and vp ) in a nine-day interval were compared between treated and untreated groups on a voxel-by-voxel analysis. The tumor response to therapy was assessed by a clustering approach and compared with conventional summary statistics, with sub-regions analysis and with histogram analysis. Results Both the Ktrans and vp estimates, following blood-pool CA injection, showed marked and spatial heterogeneous changes with antiangiogenic treatment. Averaged values for the whole tumor region, as well as from the rim/core sub-regions analysis were unable to assess the antiangiogenic response. Histogram analysis resulted in significant changes only in the vp estimates (p < 0.05). The proposed clustering approach depicted marked changes in both the Ktrans and vp estimates, with significant spatial heterogeneity in vp maps in response to treatment (p < 0.05), provided that DCE-MRI data are properly clustered in three or four sub-regions. Conclusions This study demonstrated the value of cluster analysis applied to pharmacokinetic DCE-MRI parametric maps for assessing tumor response to antiangiogenic therapy.