Improving quantitative accuracy and tissue visualization in CBCT guided radiation therapy

提高 CBCT 引导放射治疗的定量准确性和组织可视化

基本信息

批准号：
10623256
负责人：
Cem Altunbas
金额：
$ 12.39万
依托单位：
UNIVERSITY OF COLORADO DENVER
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-15 至 2026-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10623256
关键词：
Address Affect Algorithms Anatomy Architecture Area Belgium Cancer Patient Clinical Clinical Trials Collaborations Colorado Data Development Devices Disease Dose Evaluation Florida Geometry Health Image Image-Guided Surgery Intervention Interventional radiology Investigation Ions Limb structure Manufacturer Measures Methods Modality Modification Monitor Noise Normal tissue morphology Orthopedics Patients Performance Photons Play Prediction of Response to Therapy Radiation Dose Unit Radiation Scattering Radiation therapy Regimen Reporting Role Scanning Site Software Tools Spiral Computed Tomography Structure System Technology Testing Texture Tissues Toxic effect Treatment Protocols Treatment-related toxicity Tumor Tissue Universities Variant Visualization Work clinical decision-making computerized data processing cone-beam computed tomography design experimental study fabrication image guided image registration improved individualized medicine maxillofacial medical schools novel patient population prevent prospective proton therapy prototype radiation response radiomics soft tissue tool transmission process tumor two-dimensional

Address Affect Algorithms Anatomy Architecture Area Belgium Cancer Patient Clinical Clinical Trials Collaborations Colorado Data Development Devices Disease Dose Evaluation Florida Geometry Health Image Image-Guided Surgery Intervention Interventional radiology Investigation Ions Limb structure Manufacturer Measures Methods Modality Modification Monitor Noise Normal tissue morphology Orthopedics Patients Performance Photons Play Prediction of Response to Therapy Radiation Dose Unit Radiation Scattering Radiation therapy Regimen Reporting Role Scanning Site Software Tools Spiral Computed Tomography Structure System Technology Testing Texture Tissues Toxic effect Treatment Protocols Treatment-related toxicity Tumor Tissue Universities Variant Visualization Work clinical decision-making computerized data processing cone-beam computed tomography design experimental study fabrication image guided image registration improved individualized medicine maxillofacial medical schools novel patient population prevent prospective proton therapy prototype radiation response radiomics soft tissue tool transmission process tumor two-dimensional

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项目摘要

PROJECT SUMMARY Even though cone beam computed tomography (CBCT) is the most commonly used volumetric image guidance modality, its role has been severely limited in the context of treatment monitoring and patient-specific treatment modifications in radiation therapy. Due to CBCT’s poor image quality, clinicians cannot clearly visualize soft tissues to assess anatomical changes, thus affecting their clinical decision-making. Moreover, tools for treatment monitoring, such as deformable registration and dose calculation, do not function robustly with today’s CBCT images due to the lack of CT number accuracy. Scattered radiation remains to be the fundamental problem in improving CBCT image quality. Thus, in this project, we propose the two-dimensional antiscatter grid (2D Grid) as a novel device to address the scatter problem and achieve high-quality CBCT images that are suitable for treatment monitoring. Our device has fundamentally different architecture and fabrication than existing antiscatter grids for CBCT. Due to its optimized grid structure, our 2D Grid provides both higher primary transmission and better scatter rejection performance than today’s state-of-the-art antiscatter grids. Due to its favorable primary transmission and scatter rejection performance, our 2D Grid improves the contrast-to-noise ratio and CT number accuracy to levels not achievable with existing antiscatter grids. We hypothesize that our 2D Grid will provide significantly better soft tissue visualization and CT number accuracy, and deformable registration algorithms are expected to perform significantly better. To test our hypotheses, we will develop and optimize data processing methods for 2D Grid implementation in CBCT (Aim 1). Subsequently, we will fabricate 2D Grid prototypes and evaluate their performance in clinical CBCT systems for photon and proton therapy (Aim 2). Following phantom based evaluations, we will conduct a prospective clinical trial to evaluate the clinical utility of improved image quality (Aim 3). We will perform observer studies to quantify the improvement in soft tissue visualization with respect to existing clinical CBCT and gold-standard Helical CT, assess the improvement in accuracy of deformable image registration algorithms, and evaluate the improvement in consistency of image intensity and texture features. While our application is focused on radiation therapy, the 2D Grid can play a key role in other CBCT applications, such as interventional radiology, extremity imaging, and intraoperative imaging. Due to its improved low-contrast visualization performance, our 2D Grid may also allow reduction of the imaging dose in CBCT.

项目摘要即使锥束计算机断层扫描（CBCT）是最常用的体积图像指导方式，在治疗监测和特定于患者的情况下，其作用受到严重限制放射治疗中的治疗修饰。由于CBCT的图像质量差，临床医生无法清楚可视化软提示以评估解剖学变化，从而影响其临床决策。而且，用于治疗监测的工具，例如可变形的注册和剂量计算，无法牢固发挥由于缺乏CT数量的精度，因此今天的CBCT图像。散射的辐射仍然是改善CBCT图像质量的基本问题。那，在这个项目，我们提出了二维抗议者网格（2D网格）作为解决散布的新设备问题并实现适合治疗监测的高质量CBCT图像。我们的设备有与现有的CBCT的现有抗议室网格的结构和制造根本不同。由于它的优化的网格结构，我们的2D网格既可以提供更高的一级传输和更好的散射排斥性能比当今最先进的抗议者网格。由于其有利的主要传输和分散拒绝性能，我们的2D网格提高了对比度比率和CT数量的准确性现有的抗探望者网格无法达到的水平。我们假设我们的2D网格将提供更好的软组织可视化和CT数字预期的准确性和可变形的注册算法将表现出色。测试我们的假设，我们将开发并优化CBCT中2D网格实现的数据处理方法（AIM 1）。随后，我们将制造2D网格原型，并评估其在临床CBCT中的性能光子和质子疗法的系统（AIM 2）。遵循基于幻影的评估，我们将进行前瞻性临床试验，以评估改进图像质量的临床实用性（AIM 3）。我们将表演观察者的研究量化了相对于现有临床CBCT的软组织可视化的改善和金标准的螺旋CT，评估可变形图像注册准确性的提高算法，并评估图像强度和纹理特征的一致性的改善。尽管我们的应用集中在放射治疗上，但2D网格可以在其他CBCT中发挥关键作用应用，例如介入放射学，肢体成像和术中成像。由于它的改进的低对比度可视化性能，我们的2D网格还可以减少成像剂量 CBCT。