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Purpose: Tissue oxygen (O2) levels are among the most important and most quantifiable stimuli to which cells and tissues respond through inducible signaling pathways. Tumor O2 levels are major determinants of the response to cancer therapy. Developing more accurate measurements and images of tissue O2 partial pressure (pO2), assumes enormous practical, biological, and medical importance., Methods: We present a fundamentally new technique to image pO2 in tumors and tissues with pulse electron paramagnetic resonance (EPR) imaging enabled by an injected, nontoxic, triaryl methyl (trityl) spin probe whose unpaired electron's slow relaxation rates report the tissue pO2. Heretofore, virtually all in vivo EPR O2 imaging measures pO2 with the transverse electron spin relaxation rate, R2e, which is susceptible to the self-relaxation confounding O2 sensitivity., Results: We found that the trityl electron longitudinal relaxation rate, R1e, is an order of magnitude less sensitive to confounding self-relaxation. R1e imaging has greater accuracy and brings EPR O2 images to an absolute pO2 image, within uncertainties., Conclusion: R1e imaging more accurately determines oxygenation of cancer and normal tissue in animal models than has been available. It will enable enhanced, rapid, noninvasive O2 images for understanding oxygen biology and the relationship of oxygenation patterns to therapy outcome in living animal systems., (Copyright © 2013 Wiley Periodicals, Inc.)

Purpose: Low oxygen concentration (hypoxia) in tumors strongly affects their malignant state and resistance to therapy. These effects may be more deleterious in regions undergoing cycling hypoxia. Electron paramagnetic resonance imaging (EPRI) has provided a noninvasive, quantitative imaging modality to investigate static pO2 in vivo. However, to image changing hypoxia, EPRI images with better temporal resolution may be required. The tradeoff between temporal resolution and signal-to-noise ratio (SNR) results in lower SNR for EPRI images with imaging time short enough to resolve cycling hypoxia., Methods: Principal component analysis allows for accelerated image acquisition with acceptable SNR by filtering noise in projection data, from which pO2 images are reconstructed. Principal component analysis is used as a denoising technique by including only low-order components to approximate the EPRI projection data., Results: Simulated and experimental studies show that principal component analysis filtering increases SNR, particularly for small numbers of sub-volumes with changing pO2 , enabling an order of magnitude increase in temporal resolution with minimal deterioration in spatial resolution or image quality., Conclusion: The SNR necessary for dynamic EPRI studies with temporal resolution required to investigate cycling hypoxia and its physiological implications is enabled by principal component analysis filtering., (Copyright © 2013 Wiley Periodicals, Inc.)