Spectral CT metal artifact correction

能谱CT金属伪影校正

• 批准号: 9924529
• 负责人: Taly Gilat Schmidt
• 金额: $ 34.7万
• 依托单位: MARQUETTE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-05-01 至 2023-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9924529
• 关键词: Algorithms; Anatomy; Calibration; Clinical; Data; Data Set; Dental; Development; Diagnostic; Diagnostic Imaging; Dose; Gold; Hip Prosthesis; Image; Image Analysis; Implant; Knowledge; Malignant neoplasm of prostate; Maps; Measurement; Metals; Methods; Morphologic artifacts; Noise; Normal tissue morphology; Organ; Orthopedic Procedures; Orthopedics; Overdose; Pathology; Pelvis; Performance; Photons; Prevalence; Prostate Cancer therapy; Radiation Dose Unit; Radiation therapy; Risk; Roentgen Rays; Source; Starvation; System; Techniques; Technology; Tissues; Uncertainty; Variant; Work; X-Ray Computed Tomography; base; data modeling; design; experimental study; image reconstruction; imaging modality; implant material; improved; in vivo; irradiation; novel; photon-counting detector; physical model; preservation; prototype; public health relevance; reconstruction; research clinical testing; simulation; soft tissue; treatment planning; tumor

PROJECT SUMMARY Radiation therapy treatment planning can be severely impacted by the presence of metal objects such as implants and orthopaedic hardware. Metal objects cause artifacts in computed tomography (CT) images that obscure anatomical structures and alter the CT numbers, both of which are critical to estimate accurately for the purpose of planning radiation therapy. These uncertainties can cause underdosing of tumors and overdosing of healthy tissue. Existing metal artifact reduction techniques do not fully mitigate all artifacts created by the metal objects and are known to introduce new artifacts. This project will develop a spectral CT imaging method to reduce metal artifacts while maintaining CT number accuracy and soft tissue contrast. We propose to reduce metal artifacts in CT imaging by using state-of-the-art acquisition techniques, combined with an optimization- based reconstruction framework. We developed a constrained `one-step' spectral CT image reconstruction (cOSSCIR) algorithm in previous work and preliminary studies demonstrate feasibility of the proposed algorithm to reduce metal artifacts to <8 HU error. The incorporation of physical effects into the data model is one method by which the algorithm reduces metal artifacts. The optimization framework developed by our group uniquely incorporates constraints that mitigate undersampling due to unreliable measurements that pass through metal and also enable acquisition approaches that will reduce the number of unreliable measurements. The methods are designed to correct metal artifacts broadly and automatically without requiring knowledge of the implant material. The project objective to reduce metal artifacts while maintaining soft tissue contrast and CT number accuracy will be achieved by further developing the cOSSCIR algorithm and investigating its application to both dual-kV and photon-counting spectral acquisition methods using simulations, phantom experiments, and clinical photon-counting CT datasets. The algorithm will also be evaluated relative to task of radiation therapy planning for prostate cancer in the presence of hip prostheses using simulations and phantom experiments. The developed spectral CT metal artifact correction method will be compared to gold-standard images and an established metal artifact reduction technique. Successful completion of the project aims will result in a method to reduce metal artifacts in CT images while maintaining soft tissue contrast and CT number accuracy that has been validated on simulated and experimental phantom data.

项目摘要 放射治疗计划可能会受到金属物体的严重影响， 植入物和矫形硬件。金属物体在计算机断层摄影（CT）图像中引起伪影， 模糊解剖结构并改变CT值，这两者对于准确估计 计划放射治疗的目的。这些不确定性可能导致肿瘤剂量不足和药物过量。 健康组织现有的金属伪影减少技术不能完全减轻由金属产生的所有伪影 对象，并且已知会引入新的工件。该项目将开发一种光谱CT成像方法， 减少金属伪影，同时保持CT数值准确性和软组织对比度。我们建议减少 CT成像中的金属伪影，采用最先进的采集技术，结合优化- 重建框架。我们开发了一种受约束的"一步"光谱CT图像重建 （cOSSCIR）算法在前期工作和初步研究中的应用证明了该算法的可行性 以将金属伪影减少到<8 HU误差。将物理效应纳入数据模型是一种方法 通过该算法减少了金属伪影。我们团队开发的优化框架 结合了限制条件，可缓解由于通过金属的不可靠测量而导致的采样不足 并且还实现了将减少不可靠测量的数量的获取方法。的方法 被设计为广泛地自动校正金属伪影 材料该项目旨在减少金属伪影，同时保持软组织对比度和CT数量 通过进一步开发cOSSCIR算法并研究其在两个方面的应用， 使用模拟、体模实验和临床的双kV和光子计数光谱采集方法 光子计数CT数据集。该算法还将相对于放射治疗计划的任务进行评价 在髋关节假体的存在下，使用模拟和幻影实验的前列腺癌。的 开发的光谱CT金属伪影校正方法将与金标准图像进行比较， 建立了金属伪影减少技术。成功完成项目目标将产生一种方法 减少CT图像中的金属伪影，同时保持软组织对比度和CT数量准确性， 在模拟和实验体模数据上进行了验证。