Search

Electron paramagnetic resonance imaging (EPRI) can yield information about the 3-dimensional (3D) spatial distribution of the unpaired-electron-spin density from which the spatial distribution of oxygen concentration within tumor tissue, referred to as the oxygen image or electron paramagnetic resonance (EPR) image in this work, can be derived. Existing algorithms for reconstruction of EPR images often require data collected at a large number of densely sampled projection views, resulting in a prolonged data-acquisition time and consequently numerous practical challenges especially to in vivo animal EPRI. Therefore, a strong interest exists in shortening data-acquisition time through reducing the number of data samples collected in EPRI, and one approach is to acquire data at a reduced number of sparsely distributed projection views from which existing algorithms may reconstruct images with prominent artifacts. In this work, we investigate and develop an optimization-based technique for image reconstruction from data collected at sparsely sampled projection views for reducing scanning time in EPRI. Specifically, we design a convex optimization program in which the EPR image of interest is formulated as a solution and then tailor the Chambolle-Pock (CP) primal-dual algorithm to reconstruct the image by solving the convex optimization program. Using computer-simulated EPRI data from numerical phantoms and real EPRI data collected from physical phantoms, we perform studies on the verification and characterization of the optimization-based technique for EPR image reconstruction. Results of the studies suggest that the technique may yield accurate EPR images from data collected at sparsely distributed projection views, thus potentially enabling fast EPRI with reduced acquisition time.

The resolution and signal to noise ratio of EPR imaging and T1-weighted MRI were compared using an identical phantom. Several solutions of nitroxyl contrast agents with different EPR spectral shapes were tested. The feasibility of T1-weighted MRI to detect nitroxyl contrast agents was described. T1-weighted MRI can detect nitroxyl contrast agents with a complicated EPR spectrum easier and quicker; however, T1-weighted MRI has less quantitative ability especially for lipophilic nitroxyl contrast agents, because T1-relaxivity, i.e. accessibility to water, is affected by the hydrophilic/hydrophobic micro-environment of a nitroxyl contrast agent. The less quantitative ability of T1-weighted MRI may not be a disadvantage of redox imaging, which obtains reduction rate of a nitroxyl contrast. Therefore, T1-weighted MRI has a great advantage to check the pharmacokinetics of newly modified and/or designed nitroxyl contrast agents. 2007 Elsevier Inc. All rights reserved.

Electron paramagnetic resonance imaging (EPRI) is a technique that has been used for in vivo oxygen imaging of small animals. In continuous wave (CW) EPRI, the measurement can be interpreted as a sampled 4D Radon transform of the image function. The conventional filtered-backprojection (FBP) algorithm has been used widely for reconstructing images from full knowledge of the Radon transform acquired in CW EPRI. In practical applications of CW EPRI, one often is interested in information only in a region of interest (ROI) within the imaged subject. It is desirable to accurately reconstruct an ROI image only from partial knowledge of the Radon transform because acquisition of the partial data set can lead to considerable reduction of imaging time. The conventional FBP algorithm cannot, however, reconstruct accurate ROI images from partial knowledge of the Radon transform of even dimension. In this work, we describe two new algorithms, which are referred to as the backprojection filtration (BPF) and minimum-data filtered-backprojection (MDFBP) algorithms, for accurate ROI-image reconstruction from a partial Radon transform (or, truncated Radon transform) in CW EPRI. We have also performed numerical studies in the context of ROI-image reconstruction of a synthetic 2D image with density similar to that found in a small animal EPRI. This demonstrates both the inadequacy of the conventional FBP algorithm and the success of BPF and MDFBP algorithms in ROI reconstruction. The proposed ROI imaging approach promises a means to substantially reduce image acquisition time in CW EPRI.

The qualitative equivalence between the Fourier reconstruction (FR) algorithm and the filtered back projection (FBP) algorithm is demonstrated when all the different phase errors that can occur in FR are eliminated. The causes of phase errors are underlined and methods to eliminate them are presented. The practical comparison between FR and FBP has been evaluated on a numerical test image and the results are reported, demonstrating the qualitative equivalence. FR has the advantage of being very computationally efficient. In fact, the time spent to obtain the FR image was 1/20 of that used to obtain the FBP image. Because of the computational efficiency of FR and the good quality of the results obtained, an iterative version of FR has been used to implement the spectral–spatial imaging (SSI) algorithm in the field of electron paramagnetic resonance imaging (EPRI). An experimental example, demonstrating its good performance, is reported.