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Integration of Prior CT into CBCT Reconstruction for Improved Image Quality via Reconstruction of Difference: First Patient Studies

机译:通过重建差异改造改善图像质量的CBCT重建的先前CT对CBCT重建的集成:第一患者研究

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Purpose: There are many clinical situations where diagnostic CT is used for an initial diagnosis or treatment planning, followed by one or more CBCT scans that are part of an image-guided intervention. Because the high-quality diagnostic CT scan is a rich source of patient-specific anatomical knowledge, this provides an opportunity to incorporate the prior CT image into subsequent CBCT reconstruction for improved image quality. We propose a penalized-likelihood method called reconstruction of difference (RoD), to directly reconstruct differences between the CBCT scan and the CT prior. In this work, we demonstrate the efficacy of RoD with clinical patient datasets. Methods: We introduce a data processing workflow using the RoD framework to reconstruct anatomical changes between the prior CT and current CBCT. This workflow includes processing steps to account for non-anatomical differences between the two scans including 1) scatter correction for CBCT datasets due to increased scatter fractions in CBCT data; 2) histogram matching for attenuation variations between CT and CBCT; and 3) registration for different patient positioning. CBCT projection data and CT planning volumes for two radiotherapy patients - one abdominal study and one head-and-neck study - were investigated. Results: In comparisons between the proposed RoD framework and more traditional FDK and penalized-likelihood reconstructions, we find a significant improvement in image quality when prior CT information is incorporated into the reconstruction. RoD is able to provide additional low-contrast details while correctly incorporating actual physical changes in patient anatomy. Conclusions: The proposed framework provides an opportunity to either improve image quality or relax data fidelity constraints for CBCT imaging when prior CT studies of the same patient are available. Possible clinical targets include CBCT image-guided radiotherapy and CBCT image-guided surgeries.
机译:目的:有许多临床情况,其中诊断CT用于初始诊断或治疗规划,其次是一个或多个是图像引导干预的一部分的CBCT扫描。由于高质量的诊断CT扫描是具有丰富的患者特定解剖知识的来源,因此这提供了将先前CT图像结合到后续CBCT重建的机会,以改善图像质量。我们提出了一种称为差异差异(棒)重建的惩罚似然方法,直接在CBCT扫描和CT之前重建差异。在这项工作中,我们展示了杆与临床患者数据集的疗效。方法:我们使用杆框架介绍数据处理工作流程,以重建先前CT和当前CBCT之间的解剖改变。该工作流包括处理步骤,以考虑两个扫描之间的非解剖差异,包括CBCT数据增加的CBCT数据集的散点校正; 2)针对CT和CBCT之间的衰减变化的直方图匹配; 3)注册不同的患者定位。 CBCT投影数据和两种放射疗法患者的CT规划体积 - 调查了一个腹部研究和一项头颈研究。结果:在提出的杆框架和更传统的FDK与惩罚 - 似然重建之间的比较中,当先前的CT信息结合到重建时,我们发现图像质量的显着改善。棒能够在正确地结合患者解剖学中的实际物理变化的同时提供额外的低对比度细节。结论:当前同一患者的现有CT研究时,所提出的框架提供了改善图像质量或放松数据保真限制的机会,为CBCT成像进行CBCT成像。可能的临床目标包括CBCT图像引导放射疗法和CBCT图像引导的手术。

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