Electron paramagnetic resonance oxygen imaging of a rabbit tumor using localized spin probe delivery

Halpern

2015

Methods in Enzymology

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For over a century it has been known that tumor hypoxia, regions of a tumor with low levels of oxygenation, are important contributors to tumor resistance to radiation therapy and failure of radiation treatment of cancer. Recently, using novel pulse electron paramagnetic resonance (EPR) oxygen imaging, near absolute images of the partial pressure of oxygen (pO2) in tumors of living animals have been obtained. We discuss here the means by which EPR signals can be obtained in living tissues and tumors. We review development of EPR methods to image the pO2 in tumors and the potential for the pO2 image acquisition in human subjects.

Section: Epr Imaging In Cancer Biologymentioning

confidence: 99%

In Vivo pO2 Imaging of Tumors

Halpern

2015

Methods in Enzymology

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“…Currently, there are two main types of EPRI: pulse EPRI and continuous wave (CW) EPRI. Due to the short magnetic relaxation times of commonly used imaging agents, CW EPRI is more commonly used [4]. The availability of oxygen sensitive agents with longer relaxation times makes pulse EPRI oximetry possible and, considering higher accuracy and resolution, desirable [1].…”

Section: Introductionmentioning

confidence: 99%

3D pulse EPR imaging from sparse-view projections via constrained, total variation minimization

Zhang

Redler

Journal of Magnetic Resonance

et al. 2015

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Tumors and tumor portions with low oxygen concentrations (pO2) have been shown to be resistant to radiation therapy. As such, radiation therapy efficacy may be enhanced if delivered radiation dose is tailored based on the spatial distribution of pO2 within the tumor. A technique for accurate imaging of tumor oxygenation is critically important to guide radiation treatment that accounts for the effects of local pO2. Electron paramagnetic resonance imaging (EPRI) has been considered one of the leading methods for quantitatively imaging pO2 within tumors in vivo. However, current EPRI techniques require relatively long imaging times. Reducing the number of projections can considerably reduce the imaging time. Conventional image reconstruction algorithms, such as filtered back projection (FBP), may produce severe artifacts in images reconstructed from sparse-view projections. This can lower the utility of these reconstructed images. In this work, an optimization based image reconstruction algorithm using constrained, total variation (TV) minimization, subject to data consistency, is developed and evaluated. The algorithm was evaluated using simulated phantom, physical phantom and pre-clinical EPRI data. The TV algorithm is compared with FBP using subjective and objective metrics. The results demonstrate the merits of the proposed reconstruction algorithm.

“…The magnetic resonance images of water soluble spin probes in vivo show high sensitivity to varied physiologic information [2]. Specialized spin probes are designed to report on specific physiology [3].…”

Section: Introductionmentioning

confidence: 99%

Implementation of GPU-accelerated back projection for EPR imaging

Zhang

Redler

Journal of X-Ray Science and Technology: Clinical Applications

et al. 2015

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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.