Quantitative dual-energy CT imaging for radiation therapy treatment planning

用于放射治疗计划的定量双能 CT 成像

基本信息

批准号：
8628785
负责人：
JEFFREY F WILLIAMSON
金额：
$ 30.26万
依托单位：
VIRGINIA COMMONWEALTH UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-04-01 至 2016-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8628785
关键词：
Address Algorithms Architecture Base Composition Benchmarking Biological Brachytherapy Breast Cancer Patient Charge Chest Clinical Clinical Research Clinical Treatment Clinical assessments Code Data Data Set Dependence Development Devices Disease Dose Electron Beam Electron Beam Therapy Environment Equilibrium Female breast Funding Goals Head and Neck Cancer Head and neck structure Housing Image Imaging technology Implant Intensity-Modulated Radiotherapy Knowledge Light Lung Malignant neoplasm of lung Malignant neoplasm of prostate Maps Measurement Medical Methods Modality Modeling Noise Normal tissue morphology Organ Outcome Patients Pelvis Performance Photons Process Property Prostate Protons Radiation therapy Relative (related person)Research Resolution Sampling Scanning Seeds Shapes Simulate Slice Structure System Techniques Technology Testing Therapeutic Tissues Tomography, Computed, Scanners Toxic effect Uncertainty Variant Work X-Ray Computed Tomography abstracting analytical tool base cancer site clinical practice clinically significant cost effective density digital electron density experience high risk human tissue image reconstruction improved in vivo innovation irradiation male malignant breast neoplasm novel parallel computer particle patient population proton beam proton therapy prototype public health relevance reconstruction therapy outcome tool treatment planning tumor

项目摘要

DESCRIPTION (provided by applicant): Quantitative dual-energy CT imaging for radiation therapy treatment planning 6. Project Summary/Abstract Proton-beam therapy (PT) and low-energy (20-60 keV) photon-emitting brachytherapy (LEPBT) are rapidly evolving modalities with high potential for improving radiation therapy clinical outcomes because of their ability to deliver high doses to the target tissue while sparing surrounding normal tissues. Dose delivery from both modalities is sensitive to the atomic composition as well as election density of the irradiated tissues. For LEPBT, current dose-calculation practice ignores tissue inhomogeneity, introducing dose-prediction errors as large as a factor of 2. For PT, current quantitative single-energy computed tomography imaging (QSECT) leads to 3-6 mm range uncertainties that significantly increases exposure of adjacent organs to high doses. Recommended bulk tissue compositions are based upon inadequate data with large and essentially unknown patient-to-patient and intrapatient variability and cannot provide an adequate basis either for clinical treatment planning or assessing dose delivery uncertainty in PT or LEPBT. Conventional QSECT is inadequate for quantitative study of PT and LEPBT radiological tissue properties because tissue composition and electron density vary independently. The goal of this project is to develop and validate a novel quantitative dual-energy CT (QDECT) imaging technology able to accurately image the radiological properties and to demonstrate QDECT utility by assessing the magnitude and clinical significance of tissue inhomogeneities in a small patient sample. To achieve these goals, three specific aims are proposed. In Specific Aim 1, a novel statistical image reconstruction algorithm will be developed for reconstructing 3D cross-section maps derived from dual energy spiral sinograms exported from a clinical multi-slice CT imaging system. Specifically, an alternating minimization regularized, 3D reconstruction engine will be adapted and optimized to the problems of accurate tissue-map imaging for brachytherapy and proton-beam dose planning and a clinical prototype implemented. In Specific Aim 2, QDECT cross-section images reconstructed from experimentally-acquired dual-energy sinograms will be validated against experimental phantom, patient data, and computational benchmarks. Analysis of estimation errors will be used to focus AM reconstruction algorithm optimization efforts above. The developed QDECT process will be used to study the magnitude and variability of proton stopping-power and photon-cross section maps in our small patient population. Specific Aim 3 will study the dosimetric and clinical impact of more accurate patient-specific QDECT cross-section distributions on simulated brachytherapy, electron-beam and proton-beam treatment plans in head and neck, prostate, breast, and lung cancer sites using available treatment-planning systems and Monte Carlo dose-estimation codes.

描述（由申请人提供）：用于放射治疗治疗计划的定量双能 CT 成像 6. 项目摘要/摘要质子束治疗 (PT) 和低能量 (20-60 keV) 光子发射近距离放射治疗 (LEPBT) 正在迅速发展不断发展的模式具有改善放射治疗临床结果的巨大潜力，因为它们能够向目标组织提供高剂量，同时不伤害周围的正常组织。两种方式的剂量输送对受照射组织的原子组成和选举密度都很敏感。对于 LEPBT，当前的剂量计算实践忽略了组织不均匀性，引入了高达 2 倍的剂量预测误差。对于 PT，当前的定量单能量计算机断层扫描成像 (QSECT) 导致 3-6 毫米范围的不确定性，从而显着增加邻近器官暴露于高剂量。推荐的大块组织成分基于不充分的数据，具有大量且基本上未知的患者与患者之间以及患者内部的变异性，并且不能为临床治疗计划或评估 PT 或 LEPBT 中的剂量输送不确定性提供充分的基础。传统的 QSECT 不足以定量研究 PT 和 LEPBT 放射学组织特性，因为组织成分和电子密度独立变化。该项目的目标是开发和验证一种新型定量双能 CT (QDECT) 成像技术，该技术能够准确地对放射学特性进行成像，并通过评估小患者样本中组织不均匀性的程度和临床意义来证明 QDECT 的实用性。为了实现这些目标，提出了三个具体目标。在具体目标 1 中，将开发一种新颖的统计图像重建算法，用于重建从临床多层 CT 成像系统导出的双能量螺旋正弦图导出的 3D 横截面图。具体来说，交替最小化正则化 3D 重建引擎将针对近距离放射治疗和质子束剂量规划的精确组织图成像问题进行调整和优化，并实施临床原型。在具体目标 2 中，根据实验获得的双能正弦图重建的 QDECT 横截面图像将根据实验体模、患者数据和计算基准进行验证。估计误差的分析将用于集中上面的AM重建算法优化工作。开发的 QDECT 过程将用于研究我们的小患者群体中质子阻止本领和光子横截面图的大小和变异性。具体目标 3 将研究更准确的患者特异性 QDECT 横截面分布对使用现有治疗的头颈癌、前列腺癌、乳腺癌和肺癌部位的模拟近距离放射治疗、电子束和质子束治疗计划的剂量测定和临床影响-规划系统和蒙特卡罗剂量估计代码。