Abstract
Oxygen is an important biomarker in cancer biology studies. Tumor hypoxia is one of the most important factors that regulate tumor growth, development, aggressiveness, metastasis and affects ...treatment outcome. Tumor hypoxia is spatially heterogeneous. Despite the clear importance of tumor oxygenation, most scientists studying tumor hypoxia or oxygen kinetics still rely on two-dimensional cell biology techniques. Most radiation resistance studies are performed in cell cultures or in vivo/in vitro systems where tumors are radiated in situ and tumor cells subsequently explanted, cultured, and studied for survival. Absence of reliable oxygen imaging instrument capable, with sufficient spatial and temporal resolution, of imaging hypoxia in tumor's volume is a challenge for the research field.
We report the construction of the first commercial preclinical oxygen imager, JIVA-25, based on electron paramagnetic resonance oxygen imaging (EPROI). EPROI is a non-invasive oxygen mapping method with high precision and absolute accuracy (1). EPR detects unpaired electron spins subjected to the constant uniform magnetic field by manipulating them using radio-frequency electromagnetic radiation. EPROI uses an injectable non-toxic soluble contrast agent, trityl (OX063/OX063-D24) for obtaining oxygen maps in tumor models. EPROI was used recently for the first demonstration of oxygen guided radiation therapy in a mouse model of tumor (2).
JIVA-25 is a compact 25 mT EPROI instrument suitable for in vitro and small animal in vivo oxygen mapping in tumor models of mice and rats. JIVA-25 provides pO2 maps with a high spatial resolution (up to 0.5 mm), high pO2 resolution (1-3 torr), and high temporal resolution (1-10 min). Currently, the instrument is being tested for its efficacy to provide tumor treatment in mouse model at two locations, Duke Cancer Institute and the University of Chicago. Further development to improve the spatial resolution using NCI developed single point imaging (SPI) is underway using NCI funded SBIR Phase II project. Overall, we expect that JIVA-25 will be a unique tool in helping scientists understand tumor oxygenation, perform efficient tumor treatment studies, and drug development.
Acknowledgement: We acknowledge support from NIH/NCI R43CA224840, NIH/NCI R44CA224840, NSF 1819583, and JDRF 3-SRA-2020-883-M-B.
References:
1. Epel B, Kotecha M, Halpern HJ. In vivo preclinical cancer and tissue engineering applications of absolute oxygen imaging using pulse EPR. J Magn Reson. 2017;280:149-57. doi: 10.1016/j.jmr.2017.04.017. PubMed PMID: 28552587.
2. Epel B, Maggio MC, Barth ED, Miller RC, Pelizzari CA, Krzykawska-Serda M, Sundramoorthy SV, Aydogan B, Weichselbaum RR, Tormyshev VM, Halpern HJ. Oxygen-guided radiation therapy. Int J Radiat Oncol Biol Phys. 2019;103(4):977-84. doi: 10.1016/j.ijrobp.2018.10.041. PubMed PMID: 30414912.
Citation Format: Boris Epel, Howard Halpern, Mrignaayni Kotecha. Preclinical oxygen imager for cancer oxygenation studies abstract. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1646.
Directional TV algorithm for fast EPR imaging Fang, Chenyun; Xi, Yarui; Epel, Boris ...
Journal of magnetic resonance (1997),
April 2024, 2024-Apr, 2024-04-00, 20240401, Letnik:
361
Journal Article
Recenzirano
Precise radiation guided by oxygen images has demonstrated superiority over the traditional radiation methods. Electron paramagnetic resonance (EPR) imaging has proven to be the most advanced oxygen ...imaging modality. However, the main drawback of EPR imaging is the long scan time. For each projection, we usually need to collect the projection many times and then average them to achieve high signal-to-noise ratio (SNR). One approach to fast scan is to reduce the repeating time for each projection. While the projections would be noisy and thus the traditional commonly-use filtered backprojection (FBP) algorithm would not be capable of accurately reconstructing images. Optimization-based iterative algorithms may accurately reconstruct images from noisy projections for they may incorporate prior information into optimization models. Based on the total variation (TV) algorithms for EPR imaging, in this work, we propose a directional TV (DTV) algorithm to further improve the reconstruction accuracy. We construct the DTV constrained, data divergence minimization (DTVcDM) model, derive its Chambolle–Pock (CP) solving algorithm, validate the correctness of the whole algorithm, and perform evaluations via simulated and real data. The experimental results show that the DTV algorithm outperforms the existing TV and FBP algorithms in fast EPR imaging. Compared to the standard FBP algorithm, the proposed algorithm may achieve 10 times of acceleration.
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•We propose a DTV algorithm for fast EPR imaging to speed up the scan process 10 times.•This is the first extension and application of DTV algorithm in 3D pulsed EPRI.•We first give a simple but effective model-parameters selection method.•We accelerate the convergence rate by introducing two balanced parameters.
We propose a new iterative reconstruction algorithm without system matrix for EPR imaging. It is based on the idea of image rotation. Thus, the complicated calculation of system matrix may be ...avoided. For the plane-driven projection method illustrated by the left figure, one must calculate the intersecting area of a plane with a cube. But, for the rotation-driven projection method illustrated by the right figure, one just need rotate the 3D object and sum up the voxel-values of the voxels layer by layer.
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•An iterative reconstruction method without system matrix for EPR imaging is proposed.•The core idea is the design of new projection and backprojection methods based on image-rotation.•The new algorithm can achieve the comparable accuracy relative to the traditional algorithm with system matrix.•The new algorithm may avoid the complicated calculation of system matrix.
Electron paramagnetic resonance (EPR) imaging is an advanced oxygen imaging modality for oxygen-image guided radiation. The iterative reconstruction algorithm is the research hot-point in image reconstruction for EPR imaging (EPRI) for this type of algorithm may incorporate image-prior information to construct advanced optimization model to achieve accurate reconstruction from sparse-view projections and/or noisy projections. However, the system matrix in the iterative algorithm needs complicated calculation and needs huge memory-space if it is stored in memory. In this work, we propose an iterative reconstruction algorithm without system matrix for EPRI to simplify the whole iterative reconstruction process. The function of the system matrix is to calculate the projections, whereas the function of the transpose of the system matrix is to perform backprojection. The existing projection and backprojection methods are all based on the configuration that the imaged-object remains stationary and the scanning device rotates. Here, we implement the projection and backprojection operations by fixing the scanning device and rotating the object. Thus, the core algorithm is only the commonly-used image-rotation algorithm, while the calculation and store of the system matrix are avoided. Based on the idea of image rotation, we design a specific iterative reconstruction algorithm for EPRI, total variation constrained data divergence minimization (TVcDM) algorithm without system matrix, and named it as image-rotation based TVcDM (R-TVcDM). Through a series of comparisons with the original TVcDM via real projection data, we find that the proposed algorithm may achieve similar reconstruction accuracy with the original one. But it avoids the complicated calculation and store of the system matrix. The insights gained in this work may be also applied to other imaging modalities, for example computed tomography and positron emission tomography.
This work propose the balanced TV-CP algorithm for 3D EPR imaging. In the original TV-CP algorithm, the balance mechanism is not used and it corresponds to v = 1 of the new balanced TV-CP algorithm. ...In this figure, we may see that the original TV-CP algorithm is not convergent, whereas the balanced TV-CP algorithm with the appropriately selected balance parameter, i.e. v = 0.01, may reach convergence and achieve accurate reconstruction, which may be seen from the figure showing the data-divergence iteration-curves in this paper. By use of the balance mechanism, the balanced TV-CP algorithm may guarantee convergence and achieve accurate image reconstruction.
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•The balanced TV-CP algorithm is proposed for 3D EPR imaging.•The original TV-CP algorithm cannot guarantee convergence.•The balanced TV-CP algorithm requires user feedback to guide convergence.•We perform simulation and real-data studies to evaluate how the balance parameter impacts convergence.•We give qualitative analysis via the data tolerance ellipse theory and the gradient descent principle.
Total variation (TV) minimization algorithm is an effective algorithm capable of accurately reconstructing images from sparse projection data in a variety of imaging modalities including computed tomography (CT) and electron paramagnetic resonance imaging (EPRI). The data divergence constrained, TV minimization (DDcTV) model and its Chambolle-Pock (CP) solving algorithm have been proposed for CT. However, when the DDcTV-CP algorithm is applied to 3D EPRI, it suffers from slow convergence rate or divergence. We hypothesize that this is due to the magnitude imbalance between the data fidelity term and the TV regularization term. In this work, we propose a balanced TV (bTV) model incorporating a balance parameter and demonstrate its capability to avoid convergence issues for the 3D EPRI application. Simulation and real experiments show that the DDcTV-CP algorithm cannot guarantee convergence but the bTV-CP algorithm may guarantee convergence and achieve fast convergence by use of an appropriate balance parameter. Experiments also show that underweighting the balance parameter leads to slow convergence, whereas overweighting the balance parameter leads to divergence. The iteration-behavior change-law with the variation of the balance parameter is explained by use of the data tolerance ellipse and gradient descent principle. The findings and insights gained in this work may be applied to other imaging modalities and other constrained optimization problems.
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 pO2 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.
Electron paramagnetic resonance (EPR) imaging is an advanced in vivo oxygen imaging modality. The main drawback of EPR imaging is the long scanning time. Sparse-view projections collection is an ...effective fast scanning pattern. However, the commonly-used filtered back projection (FBP) algorithm is not competent to accurately reconstruct images from sparse-view projections because of the severe streak artifacts. The aim of this work is to develop an advanced algorithm for sparse reconstruction of 3D EPR imaging.
The optimization based algorithms including the total variation (TV) algorithm have proven to be effective in sparse reconstruction in EPR imaging. To further improve the reconstruction accuracy, we propose the directional TV (DTV) model and derive its Chambolle-Pock solving algorithm.
After the algorithm correctness validation on simulation data, we explore the sparse reconstruction capability of the DTV algorithm via a simulated six-sphere phantom and two real bottle phantoms filled with OX063 trityl solution and scanned by an EPR imager with a magnetic field strength of 250 G.
Both the simulated and real data experiments show that the DTV algorithm is superior to the existing FBP and TV-type algorithms and a deep learning based method according to visual inspection and quantitative evaluations in sparse reconstruction of EPR imaging.
These insights gained in this work may be used in the development of fast EPR imaging workflow of practical significance.
W-band (95 GHz) pulsed EPR and electron−nuclear double resonance (ENDOR) spectroscopic techniques were used to determine the hyperfine couplings of different protons of Cu(II)−histidine complexes in ...frozen solutions. The results were then used to obtain the coordination mode of the tridentate histidine molecule and to serve as a reference for Cu(II)−histidine complexation in other, more complex systems. Cu(II) complexes with l-histidine and dl-histidine-α-d,β-d 2 were prepared in H2O and in D2O, and orientation-selective W-band 1H and 2H pulsed ENDOR spectra of these complexes were recorded at 4.5 K. These measurements lead to the unambiguous assignment of the signals of the Hα, Hβ, imidazole Hε, and the exchangeable amino, Ham, protons. The 14N superhyperfine splitting observed in the X-band EPR spectrum and the presence of only one type of Hα and Hβ protons in the W-band ENDOR spectra show that the complex is a symmetric bis complex. Its g ∥ is along the molecular symmetry axis, perpendicular to the equatorial plane that consists of four coordinated nitrogens in histamine-like coordinations (NNNN). Simulations of orientation-selective ENDOR spectra provided the principal components of the protons' hyperfine interaction and the orientation of their principal axes with respect to g ∥. From the anisotropic part of the hyperfine interaction of Hα and Hβ and applying the point-dipole approximation, a structural model was derived. An unexpectedly large isotropic hyperfine coupling, 10.9 MHz, was found for Hα. In contrast, Hα of the Cu(II)−1-methyl-histidine complex, where only the amino nitrogen is coordinated, showed a much smaller coupling. Thus, the hyperfine coupling of Hα can serve as a signature for a histamine coordination where both the amino and imino nitrogens of the same molecule bind to the Cu(II), forming a six-membered chelating ring. Unlike Hα the hyperfine coupling of Hε is not as sensitive to the presence of a coordinated amino nitrogen of the same histidine molecule.
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