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Hypoxic tumors are resistant to radiotherapy, motivating the development of tools to image local oxygen concentrations. It is generally believed that stable or chronic hypoxia is the source of resistance, but more recent work suggests a role for transient hypoxia. Conventional EPR imaging (EPRI) is capable of imaging tissue pO2in vivo, with high pO2 resolution and 1mm spatial resolution but low imaging speed (10min temporal resolution for T1-based pO2 mapping), which makes it difficult to investigate the oxygen changes, e.g., transient hypoxia. Here we describe a new imaging method which accelerates dynamic EPR oxygen imaging, allowing 3D imaging at 2 frames per minute, fast enough to image transient hypoxia at the "speed limit" of observed pO2 change. The method centers on a low-rank tensor model that decouples the tradeoff between imaging speed, spatial coverage/resolution, and number of inversion times (pO2 accuracy). We present a specialized sparse sampling strategy and image reconstruction algorithm for use with this model. The quality and utility of the method is demonstrated in simulations and in vivo experiments in tumor bearing mice.

The value of any measurement and a fortiori any measurement technology is defined by the reproducibility and the accuracy of the measurements. This implies a relative freedom of the measurement from factors confounding its accuracy. In the past, one of the reasons for the loss of focus on the importance of imaging oxygen in vivo was the difficulty in obtaining reproducible oxygen or pO 2 images free from confounding variation. This review will briefly consider principles of electron paramagnetic oxygen imaging and describe how it achieves absolute oxygen measurements. We will provide a summary review of the progress in biomedical EPR imaging, predominantly in cancer biology research, discuss EPR oxygen imaging for cancer treatment and tissue graft assessment for regenerative medicine applications. [ABSTRACT FROM AUTHOR]

Electron paramagnetic resonance (EPR) Imaging (EPRI) is a robust method for measuring in vivo oxygen concentration (pO2). For 3D pulse EPRI, a commonly used reconstruction algorithm is the filtered backprojection (FBP) algorithm, in which the backprojection process is computationally intensive and may be time consuming when implemented on a CPU. A multistage implementation of the backprojection can be used for acceleration, however it is not flexible (requires equal linear angle projection distribution) and may still be time consuming. In this work, single-stage backprojection is implemented on a GPU (Graphics Processing Units) having 1152 cores to accelerate the process. The GPU implementation results in acceleration by over a factor of 200 overall and by over a factor of 3500 if only the computing time is considered. Some important experiences regarding the implementation of GPU-accelerated backprojection for EPRI are summarized. The resulting accelerated image reconstruction is useful for real-time image reconstruction monitoring and other time sensitive applications. [ABSTRACT FROM AUTHOR]

Electron paramagnetic resonance (EPR) spin–lattice relaxation (SLR) oxygen imaging has proven to be an indispensable tool for assessing oxygen partial pressure in live animals. EPR oxygen images show remarkable oxygen accuracy when combined with high precision and spatial resolution. Developing more effective means for obtaining SLR rates is of great practical, biological and medical importance. In this work we compared different pulse EPR imaging protocols and pulse sequences to establish advantages and areas of applicability for each method. Tests were performed using phantoms containing spin probes with oxygen concentrations relevant to in vivo oxymetry. We have found that for small animal size objects the inversion recovery sequence combined with the filtered backprojection reconstruction method delivers the best accuracy and precision. For large animals, in which large radio frequency energy deposition might be critical, free induction decay and three pulse stimulated echo sequences might find better practical usage. [ABSTRACT FROM AUTHOR]

ABSTRACT Electron paramagnetic resonance imaging (EPRI) provides 3D images of absolute oxygen concentration (pO2) in vivo with excellent spatial and pO2 resolution. When investigating such physiologic parameters in living animals, the situation is inherently dynamic. Improvements in temporal resolution and experimental versatility are necessary to properly study such a system. Uniformly distributed projections result in efficient use of data for image reconstruction. This has dictated current methods such as equal-solid-angle (ESA) spacing of projections. However, acquisition sequencing must still be optimized to achieve uniformity throughout imaging. An object-independent method for uniform acquisition of projections, using the ESA uniform distribution for the final set of projections, is presented. Each successive projection maximizes the distance in the gradient space between itself and prior projections. This maximally spaced projection sequencing (MSPS) method improves image quality for intermediate images reconstructed from incomplete projection sets, enabling useful real-time reconstruction. This method also provides improved experimental versatility, reduced artifacts, and the ability to adjust temporal resolution post factum to best fit the data and its application. The MSPS method in EPRI provides the improvements necessary to more appropriately study a dynamic system. © 2015 Wiley Periodicals, Inc. Concepts Magn Reson Part B (Magn Reson Engineering) 45B: 33-45, 2015 [ABSTRACT FROM AUTHOR]

Highlights: [•] Locations of radical species in black pepper seeds were investigated by continuous wave (CW) EPR and 9GHz EPR imaging. [•] Lithium phthalocyanine (LiPC) phantom was used to examine 9GHz EPR imaging capabilities. [•] Radical species were mostly located at the seed surface. [•] CW EPR and EPR imaging were useful for determination of the spatial distribution of paramagnetic species in various seeds. [ABSTRACT FROM AUTHOR]

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. Magn Reson Med 72:362-368, 2014. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Highlights: [•] Novel design of a bimodal resonator for 250MHz in vivo imaging. [•] This design improves signal to noise ratio per unit of time of in vivo images. [•] Alderman–Grant resonator is an optimal choice for excitation coil in bimodal resonator design. [•] Alderman–Grant resonator generates very low E-field in a sample which is important for in vivo imaging. [ABSTRACT FROM AUTHOR]

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. Magn Reson Med 71:440-450, 2014. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Hypoxic tumors are resistant to radiotherapy, motivating the development of tools to image local oxygen concentrations. It is generally believed that stable or chronic hypoxia is the source of resistance, but more recent work suggests a role for transient hypoxia. Conventional EPR imaging (EPRI) is capable of imaging tissue pO 2 in vivo , with high pO 2 resolution and 1 mm spatial resolution but low imaging speed (10 min temporal resolution for T 1 -based pO 2 mapping), which makes it difficult to investigate the oxygen changes, e.g., transient hypoxia. Here we describe a new imaging method which accelerates dynamic EPR oxygen imaging, allowing 3D imaging at 2 frames per minute, fast enough to image transient hypoxia at the “speed limit” of observed pO 2 change. The method centers on a low-rank tensor model that decouples the tradeoff between imaging speed, spatial coverage/resolution, and number of inversion times (pO 2 accuracy). We present a specialized sparse sampling strategy and image reconstruction algorithm for use with this model. The quality and utility of the method is demonstrated in simulations and in vivo experiments in tumor bearing mice. [ABSTRACT FROM AUTHOR]