Computational Tools for Next Generation Volumetric Cone Beam Computed Tomography

下一代体积锥形束计算机断层扫描的计算工具

• 批准号: 9096789
• 负责人: Lei Xing
• 金额: $ 51.74万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9096789
• 关键词: Accounting; Adverse effects; Algorithms; Anatomy; Brachytherapy Seeds; Breathing; Characteristics; Childhood; Clinical; Cohort Studies; Computing Methodologies; Cone; Coupled; Data; Dental; Diagnostic radiologic examination; Dose; Excision; Foundations; Future; Goals; Health; Hip region structure; Image; Imaging Techniques; Individual; Knowledge; Liver; Location; Lung; Malignant Neoplasms; Malignant neoplasm of brain; Mathematics; Measurement; Medical; Metals; Methods; Morphologic artifacts; Motion; Noise; Pancreas; Pathology; Patients; Phase; Physics; Procedures; Process; Prosthesis; Radiation; Radiation Oncology; Radiation therapy; Research; Research Design; Research Personnel; Respiration; Risk; Scanning; Scheme; Second Primary Cancers; Shapes; Shoulder; System; Techniques; Technology; Testing; Time; Tissue imaging; Uncertainty; United States National Institutes of Health; Weight; X-Ray Computed Tomography; base; cancer imaging; clinical application; clinical decision-making; clinical practice; computerized data processing; computerized tools; cone-beam computed tomography; design; experience; image guided; image guided intervention; image guided radiation therapy; image processing; image reconstruction; improved; innovation; interest; leukemia; lifetime risk; next generation; patient population; process optimization; reconstruction; research clinical testing; response; scientific computing; signal processing; spatiotemporal; tool; treatment planning; tumor; Accounting; Adverse effects; Algorithms; Anatomy; Brachytherapy Seeds; Breathing; Characteristics; Childhood; Clinical; Cohort Studies; Computing Methodologies; Cone; Coupled; Data; Dental; Diagnostic radiologic examination; Dose; Excision; Foundations; Future; Goals; Health; Hip region structure; Image; Imaging Techniques; Individual; Knowledge; Liver; Location; Lung; Malignant Neoplasms; Malignant neoplasm of brain; Mathematics; Measurement; Medical; Metals; Methods; Morphologic artifacts; Motion; Noise; Pancreas; Pathology; Patients; Phase; Physics; Procedures; Process; Prosthesis; Radiation; Radiation Oncology; Radiation therapy; Research; Research Design; Research Personnel; Respiration; Risk; Scanning; Scheme; Second Primary Cancers; Shapes; Shoulder; System; Techniques; Technology; Testing; Time; Tissue imaging; Uncertainty; United States National Institutes of Health; Weight; X-Ray Computed Tomography; base; cancer imaging; clinical application; clinical decision-making; clinical practice; computerized data processing; computerized tools; cone-beam computed tomography; design; experience; image guided; image guided intervention; image guided radiation therapy; image processing; image reconstruction; improved; innovation; interest; leukemia; lifetime risk; next generation; patient population; process optimization; reconstruction; research clinical testing; response; scientific computing; signal processing; spatiotemporal; tool; treatment planning; tumor

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.

描述（由申请人提供）：锥束CT（CBCT）成像已成为图像引导干预措施和许多其他临床应用中必不可少的工具。但是，当前CBCT成像中的数据处理方法在多个方面缺乏，这通常会导致严重的伪像，并导致患者的高成像剂量。图像质量差会导致临床决策的很大不确定性，并严重阻碍了技术的最大利用。该项目旨在将CBCT开发为一种临床准确且可靠的技术，用于描述肿瘤靶标，介入指导和放射治疗治疗计划。为了应对NIH PAR-09-218，我们组建了一个研究人员团队，该研究人员由辐射肿瘤学，医学物理学，图像和信号处理，优化和应用数学以及建立的研究主题和项目组成，并统一了这些研究者的共同利益和专业知识。我们借鉴了我们在CBCT成像和科学计算方面的丰富经验，以开发下一代无伪影和超低剂量CBCT。将建立许多创新的策略来处理CBCT成像中稀疏，嘈杂和缺少数据的策略。具体目的是：（1）通过利用患者特异性的先前数据和压缩感应来实现超低剂量CBCT； （2）为CBCT重建中的金属伪像去除金属伪像的方法； （3）通过有效使用投影的相关相关性来获得无运动伪影图像。该项目的成功完成将提供高质量的CBCT图像，而成像剂量的数量级。对于图像引导的放射疗法，改进的图像质量将使基于CBCT的剂量计算并进行重新融合，这将为下一代的适应性疗法奠定基础，以最佳补偿患者的设置误差和分数解剖学变化。随着成像剂量的降低，该提出的技术将显着降低辐射引起的二次癌症的风险，并在常规临床实践中安全有效地利用体积X射线成像技术。