Computational Tools for Next Generation Volumetric Cone Beam Computed Tomography

描述(申请人提供)：锥束CT(CBCT)成像正在成为图像引导介入治疗和许多其他临床应用中不可或缺的工具。然而，目前CBCT成像的数据处理方法存在多方面的不足，往往会产生严重的伪影，给患者带来较大的成像剂量。较差的图像质量给临床决策带来了很大的不确定性，严重阻碍了该技术的最大限度利用。该项目旨在将CBCT发展成为一种临床上准确可靠的技术，用于勾画肿瘤靶点、介入指导和放射治疗计划。为了响应NIH PAR-09-218，我们组建了一支由放射肿瘤学、医学物理学、图像和信号处理、优化和应用数学领域的领导者组成的调查团队，并建立了研究主题和项目，统一了这些调查人员的共同兴趣和专业知识。我们利用我们在CBCT成像和科学计算方面的丰富经验，开发出下一代无伪影和超低剂量的CBCT。将建立一些创新的策略来处理CBCT成像中的稀疏、噪声和丢失数据。具体目标是：(1)通过利用患者特定的先验数据和压缩感知来实现超低剂量的CBCT；(2)开发一种分而治之的CBCT重建中的金属伪影去除方法；(3)通过有效地利用投影的相间相关性来获得无运动伪影的图像。该项目的成功完成将提供高质量的CBCT图像，成像剂量少一个数量级。对于图像引导放射治疗，图像质量的提高将使基于CBCT的精确剂量计算和重新规划成为可能，这将为下一代适应性治疗奠定基础，以最佳地补偿患者设置误差和部分解剖变化。随着成像剂量的减少，建议的技术将显著降低辐射诱发继发性癌症的风险，并有助于在常规临床实践中安全有效地使用体积X射线成像技术。

DESCRIPTION (provided by applicant): Cone beam CT (CBCT) imaging is becoming an indispensable tool in image guided interventions and many other clinical applications. The data processing method in current CBCT imaging is, however, deficient in multiple aspects, which often leads to severe artifacts and results in high imaging dose to the patients. The poor image quality causes much uncertainty in clinical decision-making and seriously impedes the maximal utilization of the technology. This project is directed at developing CBCT into a clinically accurate and reliable technique for delineation of tumor target, interventional guidance and radiation therapy treatment planning. In response to NIH PAR-09-218, we have assembled a team of investigators comprised of leaders in the fields of radiation oncology, medical physics, image and signal processing, optimization and applied mathematics and established research themes and projects that unify the common interests and expertise of these investigators. We draw on our extensive experience in CBCT imaging and scientific computing to develop the next generation of artifact-free and ultra-low dose CBCT. A number of innovative strategies to dealing with sparse, noisy, and missing data in CBCT imaging will be established. Specific aims are: (1) To achieve ultra-low dose CBCT by utilization of patient-specific prior data and compressed sensing; (2) to develop a divide-and-conquer approach for metal artifact removal in CBCT reconstruction; and (3) to obtain motion artifact-free images by effective use of inter-phase correlation of the projections. Successful completion of this project will provide high quality CBCT images with orders of magnitude less imaging dose. For image guided radiation therapy, the improved image quality will make accurate CBCT-based dose calculation and replanning possible, which will lay the foundation for next generation of adaptive therapy to optimally compensate for the patient setup error and inter- fractional anatomy change. With the reduction in imaging dose, the proposed technique will significantly reduce the risk of radiation-induced secondary cancers and contribute to the safe and efficient use of volumetric X-ray imaging techniques in routine clinical practice.