Low dose cone beam CT for image guided adaptive radiotherapy

用于图像引导适应性放射治疗的低剂量锥形束 CT

• 批准号: 8026135
• 负责人: Steve Bin Jiang
• 金额: $ 29.56万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-03-01 至 2016-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8026135
• 关键词: Algorithms; Chest; Childhood; Clinical; Clinical Protocols; Detection; Dose; Excision; Future; Goals; Hour; Image; Lead; Low Dose Radiation; Morphologic artifacts; Noise; Patients; Performance; Play; Process; Radiation therapy; Research; Resolution; Retinal Cone; Role; Scanning; Series; Speed; Structure; System; Techniques; Testing; Time; Treatment outcome; Update; Variant; Work; base; cancer radiation therapy; clinical application; cone-beam computed tomography; digital; improved; innovation; next generation; reconstruction

DESCRIPTION (provided by applicant): Cone-beam computed tomography (CBCT) has been broadly used in image guided radiation therapy (IGRT) and adaptive radiation therapy (ART), to acquire the updated patient's geometry for precise targeting and treatment adaptation. However, the repeated use of CBCT during a treatment course has raised a serious concern on excessive x-ray imaging doses delivered to patients, which has greatly limited the maximal exploitation of the potential of modern radiotherapy. Especially for pediatric patients, this concern has prohibited the use of IGRT and ART, leading to compromised treatment outcome. Advanced iterative reconstruction algorithms, based on compressed sensing techniques, have demonstrated tremendous power in reconstructing CBCT images from very few and/or noisy projections, resulting in dramatically reduced imaging dose. However, these algorithms are very computationally inefficient and thus cannot be used in most clinical applications. We have recently made a breakthrough in developing an innovative CBCT reconstruction algorithm with a mathematical structure perfect for parallelization on a graphics processing unit (GPU) platform. Our preliminary results have shown that we can improve the efficiency by a factor of 100 over existing iterative algorithms and reduce the imaging dose by factor of 40~100 compared to the current clinical standard. Our goal is to develop this promising algorithm into a clinically functioning CBCT reconstruction system which can produce high quality CBCT images at extremely low radiation dose (<1% of the current dose) and high speed (< 5 seconds), by pursuing the following two specific aims: SA1. We will develop a GPU-based system to reconstruct high quality CBCT images at ultra-low radiation dose and ultra-high speed. SA2. We will evaluate the system through a series of numerical, phantom, and patient studies, demonstrate the gain in imaging dose reduction, and establish clinical protocols under various clinical conditions. Upon the completion of the proposed project, a clinically ready-to-use CBCT reconstruction system with ultra-low dose and ultra-fast performance will have been systematically developed and evaluated. Clinical introduction of such a system will significantly benefit a large number of patients receiving modern radiotherapy. Especially, our work will for the first time make IGRT and ART clinically available for pediatric patients. PUBLIC HEALTH RELEVANCE: This project is to develop an ultra fast and extremely low dose cone beam CT (CBCT) reconstruction system for image guided adaptive radiotherapy. Specifically, we will develop innovative CBCT reconstruction algorithms that can reduce the imaging dose to less than one percent of the current state of the art. More importantly, the mathematical structure of the new algorithms is perfect for GPU parallelization which makes the fast reconstruction clinically feasible.

描述（由申请人提供）：锥束计算机断层扫描（CBCT）已广泛用于引导放射疗法（IGRT）和适应性放射疗法（ART），以获取更新的患者的几何形状，以进行精确的靶向和治疗适应。然而，在治疗过程中反复使用CBCT，这引起了人们对X射线成像剂量过多的剂量的严重关注，这极大地限制了对现代放射疗法潜力的最大开发。特别是对于儿科患者，这种担忧禁止使用IGRT和ART，从而导致治疗结果受损。基于压缩感测技术的先进迭代重建算法在重建非常少量和/或嘈杂的投影中重建CBCT图像方面具有巨大的功能，从而大大减少了成像剂量。但是，这些算法在计算上效率低下，因此无法在大多数临床应用中使用。最近，我们在开发具有数学结构的创新CBCT重建算法方面取得了突破，非常适合在图形处理单元（GPU）平台上并行化。我们的初步结果表明，与当前的临床标准相比，我们可以将效率提高100倍，比现有迭代算法提高100倍，并将成像剂量降低40〜100。我们的目标是将这种有希望的算法开发为临床运作的CBCT重建系统，该系统可以通过追求以下两个特定目标来生产出极低辐射剂量（<当前剂量的<1％）和高速（<5秒）的高质量CBCT图像：SA1。我们将开发一个基于GPU的系统，以超低辐射剂量和超高速度重建高质量的CBCT图像。 SA2。我们将通过一系列数值，幻影和患者研究来评估系统，证明减少剂量剂量的增长，并在各种临床条件下建立临床方案。拟议项目完成后，将系统地开发和评估具有超低剂量和超快速性能的临床现成的CBCT重建系统。这种系统的临床引入将显着受益于大量接受现代放疗的患者。特别是，我们的工作将首次使IGRT和ART在临床上为儿科患者提供。 公共卫生相关性：该项目是为图像引导的自适应放射疗法开发超快速且极低的剂量锥束CT（CBCT）重建系统。具体而言，我们将开发创新的CBCT重建算法，这些算法可以将成像剂量降低到当前最新状态的百分之一。更重要的是，新算法的数学结构非常适合GPU并行化，这使得快速重建在临床上可行。