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.

项目概要 我们提出了一种技术解决方案，可实现近乎理想的 X 射线光子计数探测器 (PCD) 计算机断层扫描 (CT)，我们称之为 PCD-CT 的大部分临床梦想将成为现实。 多能量像素间符合计数器(MEICC)的解决方案及设计实现是可行的 我们计划提供一个使用当今电子技术的 MEICC 的概念验证。 通过研究 MEICC 的细节、优化设计并研究性能，“取得进展” 使用蒙特卡罗 (MC) 模拟的 MEICC 有望成为下一代 X 射线 CT。 巨大的潜力，例如改善当前的 CT 图像，而且还可以实现新的临床应用，例如 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 成像和生物标志物、准确的软组织材料表征、K 边缘 研究表明，最新的 PCD 已足够。 快速用于临床 X 射线 CT，多个小组开发了原型全身 PCD-CT 系统并安装 研究表明 PCD-CT 的巨大潜力。 原型 PCD-CT 没有达到很高的期望，事实上，性能有时与此相当。 由于 PCD 像素之间存在一种称为“电荷共享”的现象，双能 CT 会增加噪声。 方差增加了 4 倍，降低了空间分辨率，降低了能量响应，并削弱了 总的来说，它对 PCD-CT 的性能有显着的负面影响。 是检测物理所固有的，电荷共享的概率约为 70%，因此不可能。 避免这是一个非常关键的问题，需要解决 MEICC 将解决噪声和偏见。 MEICC使用能量相关的符合计数器，保存电荷共享簿。 数据采集​​期间发生的事件，并使用事件发生后的确切数量来纠正它们 采集完成后，MEICC 不会干扰主要计数过程； 将保持与没有 MEICC 的速度一样快，可以使用当今的电子技术来实现。 因为它的像素间重合计数器简单且数字化，我们认为 MEICC 可以消除。 电荷共享效应，将噪声降低到最低水平，增强信号，提高能量 总体而言，我们计划通过实现近乎理想的 X 射线 PCD-CT 来检验这一假设。 以下 3 个具体目标： (SA1) 开发 MEICC 设计和算法 (SA2) 开发 MC 仿真； (SA3) 使用以下方法评估 MEICC 和其他完成技术的特定任务性能 Cramér-Rao 下限作为主要品质因数。