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Early prediction of tumor response to bevacizumab treatment in murine colon cancer models using three-dimensional dynamic contrast-enhanced ultrasound imaging
Early prediction of tumor response to bevacizumab treatment in murine colon cancer models using three-dimensional dynamic contrast-enhanced ultrasound imaging
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Early prediction of tumor response to bevacizumab treatment in murine colon cancer models using three-dimensional dynamic contrast-enhanced ultrasound imaging
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Early prediction of tumor response to bevacizumab treatment in murine colon cancer models using three-dimensional dynamic contrast-enhanced ultrasound imaging
Early prediction of tumor response to bevacizumab treatment in murine colon cancer models using three-dimensional dynamic contrast-enhanced ultrasound imaging

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Early prediction of tumor response to bevacizumab treatment in murine colon cancer models using three-dimensional dynamic contrast-enhanced ultrasound imaging
Early prediction of tumor response to bevacizumab treatment in murine colon cancer models using three-dimensional dynamic contrast-enhanced ultrasound imaging
Journal Article

Early prediction of tumor response to bevacizumab treatment in murine colon cancer models using three-dimensional dynamic contrast-enhanced ultrasound imaging

2017
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Overview
Due to spatial tumor heterogeneity and consecutive sampling errors, it is critically important to assess treatment response following antiangiogenic therapy in three dimensions as two-dimensional assessment has been shown to substantially over- and underestimate treatment response. In this study, we evaluated whether three-dimensional (3D) dynamic contrast-enhanced ultrasound (DCE-US) imaging allows assessing early changes in tumor perfusion following antiangiogenic treatment (bevacizumab administered at a dose of 10 mg/kg b.w.), and whether these changes could predict treatment response in colon cancer tumors that either are responsive (LS174T tumors) or none responsive (CT26) to the proposed treatment. Our results showed that the perfusion parameters of 3D DCE-US including peak enhancement (PE) and area under curve (AUC) significantly decreased by up to 69 and 77%, respectively, in LS174T tumors within 1 day after antiangiogenic treatment ( P  = 0.005), but not in CT26 tumors ( P  > 0.05). Similarly, the percentage area of neovasculature significantly decreased in treated versus control LS174T tumors ( P  < 0.001), but not in treated versus control CT26 tumors (P  = 0.796). Early decrease in both PE and AUC by 45–50% was predictive of treatment response in 100% (95% CI 69.2, 100%) of responding tumors, and in 100% (95% CI 88.4, 100%) and 86.7% (95% CI 69.3, 96.2%), respectively, of nonresponding tumors. In conclusion, 3D DCE-US provides clinically relevant information on the variability of tumor response to antiangiogenic therapy and may be further developed as biomarker for predicting treatment outcomes.