Fig. 9.

PCA filtering applied to a dynamic EPRI study of spontaneous pO₂ fluctuations in a murine tumor. (a) Comparison of image quality for unfiltered and PCA filtered pO₂ images. The tumor is outlined in magenta and the 27 voxel ROI is outlined by the white square. (b) Observed temporal pO₂ fluctuations averaged over the ROI shown on the periphery of the tumor. PCA filtering helps to elucidate apparent sinusoidal pO₂ fluctuations that are difficult to discern in the unfiltered data. These fluctuations may be biologically relevant cycling or acute hypoxia.