Low dose cone beam CT for image guided adaptive radiotherapy

描述（由申请人提供）：锥形束计算机断层扫描（CBCT）已广泛用于图像引导放射治疗（IGRT）和自适应放射治疗（ART），以获取更新的患者几何形状，用于精确靶向和治疗适应。然而，在治疗过程中重复使用CBCT引起了对输送给患者的过量X射线成像剂量的严重关注，这极大地限制了现代放射治疗潜力的最大开发。特别是对于儿科患者，这一问题已经禁止使用IGRT和ART，导致治疗结果受损。先进的迭代重建算法，基于压缩传感技术，已经证明了巨大的权力，重建CBCT图像从非常少和/或嘈杂的投影，导致显着降低成像剂量。然而，这些算法在计算上非常低效，因此不能用于大多数临床应用。我们最近在开发一种创新的CBCT重建算法方面取得了突破，该算法具有完美的数学结构，可在图形处理单元（GPU）平台上并行化。我们的初步结果表明，我们可以提高效率的一个因素100比现有的迭代算法，并减少成像剂量的一个因素40~100相比，目前的临床标准。我们的目标是将这种有前途的算法开发成临床功能的CBCT重建系统，该系统可以在极低的辐射剂量（<当前剂量的1%）和高速（< 5秒）下产生高质量的CBCT图像，通过追求以下两个特定目标：SA 1。我们将开发一个基于GPU的系统，以超低辐射剂量和超高速重建高质量的CBCT图像。SA 2.我们将通过一系列数值、体模和患者研究评估该系统，证明成像剂量降低的增益，并在各种临床条件下建立临床方案。在拟议项目完成后，将系统地开发和评估具有超低剂量和超快速性能的临床即用型CBCT重建系统。这种系统的临床引入将使大量接受现代放射治疗的患者受益。特别是，我们的工作将首次使IGRT和ART临床上可用于儿科患者。 公共卫生相关性：本计画旨在研制一种超快速、极低剂量的锥形束CT（CBCT）重建系统，以应用于影像导引的适应性放射治疗。具体来说，我们将开发创新的CBCT重建算法，可以将成像剂量降低到当前最先进水平的1%以下。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。

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.