A novel in vivo tumor oxygen profiling assay: Combining functional and molecular imaging with multivariate mathematical modeling
Purpose: The objective of this study is to develop and test a novel high spatio-temporal in vivo assay to quantify tumor oxygenation and hypoxia. The assay implements a biophysical model of oxygen transport to fuse parameters acquired from in vivo functional and molecular imaging modalities. Introduction: Tumor hypoxia plays an important role in carcinogenesis. It triggers pathological angiogenesis to supply more oxygen to the tumor cells and promotes cancer cell metastasis. Preclinical and clinical evidence show that anti-angiogenic treatment is capable of normalizing the tumor vasculature both structurally and functionally. The resulting normalized vasculature provides a more efficient and uniform microcirculation that enhances oxygen and drug delivery to the tumor cells and improves second-line treatments such as traditional radiation or chemotherapy. Early studies using the overall or average tumor hypoxia as a prognostic biomarker of anti-angiogenic therapy efficacy was ambivalent; however, recent studies have discovered that the etiology of hypoxia and its heterogeneity could be used as reliable prognostic biomarkers. The capability to longitudinally map tumor hypoxia with high spatial and temporal resolution has the potential to enhance fundamental cancer research and ultimately cancer patient care. Method: A novel methodology to identify and characterize tumor hypoxia by fusing the physiological hemodynamic parametric maps obtained from functional and molecular imaging modalities and technique using a modified Krogh model of oxygen transport (MPO2) was developed. First, simulations studies were performed to validate this technique. Microscopy data of tumor and brain tissue (control) provided both the vasculature and rheology data. A Green's function algorithm was used to solve the ordinary differential equation and calculate the oxygen profile at a microscopic scale (15 μm) (GPO2), which was used as a reference. From this data, simulated physiological maps (perfusion, fractional plasma volume, fractional interstitial volume) and hemoglobin status (oxygen saturation, hemoglobin concentration) was used as input to MPO2 and used to calculate pO2 levels as a function of scanner spatial resolution and noise. Second, MPO2 was compared to pO2 measurements in xenograft breast tumors using OxyLite oxygen sensor as a Gold Standard, where DCE-CT and PCT-S images were acquired to obtain hemodynamic images. Finally, the vascular physiology measurements obtained from an anti-angiogenic therapeutic study in pancreatic tumors was applied to MPO2 and compared to therapeutic response. Results: The simulation results using Green's function pO2 as standard showed that the MPO2 model performance was dependent on the spatial resolution (voxel size) of the images. Sensitivity and error analysis of this model were also investigated in this study. These oxygen transport simulations results suggest the oxygen saturation and hemoglobin concentration were two key factors in tissue oxygenation, and concomitant with blood perfusion and tumor metabolic rate. Comparisons of the pO2 profile obtained from MPO2 and OxyLite probe in MCF7 tumor model demonstrated a significant correlation and approached a slope of one (after accounting for a few outliers). Simulation studies implementing the physiological data obtained from the anti-angiogenic therapeutic study in pancreatic tumors using the MPO2 model agreed with the experimental findings that blood perfusion is a valuable prognostic biomarker in therapeutic efficacy. This model also predicted the oxygenation improvement difference from two vascular renormalization modes (topological normalization and geometrical normalization). Conclusion: The results from the simulation and in vivo studies demonstrated the feasibility of this novel hypoxia assay. Simulation results of the pancreatic tumors provide an example of the impact the MPO2 model in conjunction with imaging can provide when evaluating the therapeutic significance of various normalization modes in anti-angiogenic therapy, and suggests potential approaches to further improve anti-angiogenic therapy efficacy.
Stantz, Purdue University.
Biomedical engineering|Health sciences|Biophysics
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