Quasi-ideal photon counting x-ray CT with multi-energy inter-pixel coincidence counter (MEICC)

具有多能量像素间符合计数器 (MEICC) 的准理想光子计数 X 射线 CT

• 批准号: 10117252
• 负责人: Katsuyuki Taguchi
• 金额: $ 19.73万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2024-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10117252
• 关键词: Address; Algorithms; Anodes; Books; Charge; Clinical; Communication; Computer software; Contrast Media; Data; Detection; Diagnostic; Dreams; Electronics; Event; Financial compensation; Funding; Hospitals; Image; Industry; Measures; Modeling; Monte Carlo Method; Needles; Noise; PF4 Gene; Performance; Phase; Photons; Physics; Probability; Process; Radiation Dose Unit; Resolution; Roentgen Rays; Scheme; Signal Transduction; Small Business Innovation Research Grant; Sum; System; Technology; Testing; Time; Work; X-Ray Computed Tomography; analog; base; clinical application; data acquisition; design; detector; digital; expectation; imaging agent; imaging biomarker; imaging modality; improved; next generation; photon-counting detector; programs; prototype; response; soft tissue; tool

Project Summary We propose a technical solution that enables nearly ideal photon counting detectors (PCDs) for x-ray computed tomography (CT), which will bring most of clinical dreams surrounding PCD-CT into reality. We call the solution multi-energy inter-pixel coincidence counter (MEICC) and it is feasible to implement the design and algorithm of MEICC using today’s electronics technology. We plan to provide a proof of concept that will “move the needle” by working on the detail of MEICC, optimizing the design and studying the performance of MEICC using Monte Carlo (MC) simulations. PCD-CT is expected to be the next generation of x-ray CT. It has great potentials such as improve the current CT images but also to enable new clinical applications, such as higher spatial resolution, better soft tissue contrast, stronger contrast agent enhancement, radiation dose reduction, quantitative CT imaging and biomarkers, accurate soft tissue material characterization, K-edge imaging, and simultaneous multi-contrast agent imaging. Studies showed that latest PCDs were sufficiently fast for clinical x-ray CT and several groups developed prototype whole-body PCD-CT systems and installed them for a beta test in 2014–2018. Studies have shown great potential of PCD-CT. But, the performance of the prototype PCD-CT did not meet high expectations. In fact, the performance was sometimes comparable to that of dual-energy CT because of a phenomenon called “charge sharing” between PCD pixels. It increases noise variance by a factor of 4, degrades the spatial resolution, degrades the energy response, and weakens the spectral signals. Overall, it has a significantly negative impact on the performance of PCD-CT. Charge sharing is inherent to the detection physics and the probability of charge sharing is ~70%. Thus, it is impossible to avoid and is a very critical issue that needs to be addressed. MEICC will address both noise and bias added by charge sharing. MEICC uses energy-dependent coincidence counters, keeps the book of charge sharing events during the data acquisition, and corrects them using the exact number of the occurrences after the acquisition is completed. MEICC does not interfere with the primary counting process; thus, PCDs with MEICC will remain as fast as those without MEICC. MEICC can be implemented using today’s electronics technology because its inter-pixel coincidence counters are simple and digital. We hypothesize that MEICC can eliminate the effect of charge sharing, decrease noise to the minimal level, enhance signals, improve the energy response, and over all, enable nearly ideal x-ray PCD-CT. We plan to test the hypothesis by accomplishing the following 3 specific aims: (SA1) Develop MEICC designs and algorithms; (SA2) develop MC simulation programs; (SA3) assess the task-specific performance of MEICC and other completing technologies using Cramér–Rao lower bound as the primary figure of merit.

项目摘要 我们提出了一种技术解决方案，使x射线的光子计数探测器(Pcd)近乎理想。 计算机断层扫描(CT)，它将把围绕PCD-CT的大多数临床梦想变成现实。我们打电话给 提出了一种多能量像素间符合计数器(MEICC)的解决方案，并实现了该设计 以及使用当今电子技术的MEICC的算法。我们计划提供一个概念证明，将 通过对MEICC的细节进行研究，对MEICC的设计进行优化，并研究了MEICC的性能 使用蒙特卡罗(MC)模拟的MEICC。PCD-CT有望成为下一代X射线CT。它有 巨大的潜力，如改善目前的CT图像，也使新的临床应用，如 更高的空间分辨率，更好的软组织对比度，更强的造影剂增强，辐射剂量 还原、定量CT成像和生物标记物、准确的软组织材料表征、K-Edge 成像和同步多造影剂成像。研究表明，最新的PCD足以 FAST for临床X光CT和几个小组开发了全身PCD-CT原型系统并安装 他们将在2014-2018年进行Beta测试。研究表明，PCD-CT具有很大的潜力。但是，这场比赛的表现 样机PCD-CT没有达到很高的期望。事实上，它的表现有时可以与之媲美 这是因为PCD像素之间存在一种称为“电荷共享”的现象。它增加了噪音 方差为4的因子，会降低空间分辨率，降低能量响应，并削弱 光谱信号。总体而言，它对PCD-CT的性能有显著的负面影响。电荷共享 是探测物理所固有的，电荷共享的概率约为70%。因此，不可能 避免和是一个需要解决的非常关键的问题。MEICC将解决噪声和偏差问题，由 电荷共享。MEICC使用能量依赖的符合计数器，保持电荷共享 事件，并使用数据采集后的准确发生次数进行更正。 收购已完成。MEICC不会干扰主要的计数过程；因此，使用MEICC的PCD 将保持和那些没有MEICC的人一样快。可以使用当今的电子技术来实现MEICC 因为它的像素间符合计数器简单而数字化。我们假设MEICC可以消除 电荷共享的效果，将噪声降到最低，增强信号，提高能量 响应，总的来说，实现了近乎理想的x射线PCD-CT。我们计划通过完成 以下三个具体目标：(SA1)开发MEICC设计和算法；(SA2)开发MC仿真 计划；(SA3)使用以下工具评估MEICC和其他完成技术的特定任务性能 Cramér-Rao下限作为主要的优点系数。