3D pulse EPR imaging from sparse-view projections via constrained, total variation minimization
3D pulse EPR imaging from sparse-view projections via constrained, total variation minimization
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DOI：
10.1016/j.jmr.2015.06.009
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发表时间：
2015-09-01
影响因子：
2.2
通讯作者：
Halpern, Howard
中科院分区：
文献类型：
--
作者：
Qiao, Zhiwei;Redler, Gage;Halpern, Howard
肿瘤和低氧浓度（pO（2））的肿瘤部分已被证明对放射治疗有抵抗力。因此，如果基于肿瘤内pO（2）的空间分布来定制递送的辐射剂量，则可以增强辐射治疗功效。肿瘤氧合的准确成像技术对于指导放射治疗至关重要，因为局部pO（2）的影响。电子顺磁共振成像（EPRI）被认为是定量成像体内肿瘤内pO（2）的主要方法之一。然而，目前的EPRI技术需要相对较长的成像时间。减少投影扫描的数量可以大大减少成像时间。传统的图像重建算法，如滤波反投影（FBP），可能会在从稀疏视图投影重建的图像中产生严重的伪影。这会降低这些重建图像的效用。在这项工作中，基于优化的图像重建算法，使用约束，总变差（TV）最小化，受数据的一致性，开发和评估。使用模拟体模、物理体模和临床前EPRI数据对算法进行了评价。TV算法进行了比较，FBP使用主观和客观的指标。实验结果验证了该算法的有效性。(C)2015爱思唯尔公司All rights reserved.
Tumors and tumor portions with low oxygen concentrations (pO(2)) 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 pO(2) 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 pO(2). Electron paramagnetic resonance imaging (EPRI) has been considered one of the leading methods for quantitatively imaging pO(2) within tumors in vivo. However, current EPRI techniques require relatively long imaging times. Reducing the number of projection scan 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. (C) 2015 Elsevier Inc. All rights reserved.