Algorithm-Enabled Auto-Calibrating Quantitative Dual-Energy CT

支持算法的自动校准定量双能 CT

• 批准号: 10448987
• 负责人: XIAOCHUAN PAN
• 金额: $ 22.83万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-10 至 2024-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10448987
• 关键词: Algorithmic Analysis; Algorithms; Cations; Clinical; Contrast Media; Data; Development; Diagnostic; Disease Management; Dose; Ensure; Evaluation; Evaluation Studies; Home; Image; Intensive Care Units; Interventional radiology; Measurement; Measures; Metals; Modification; Morphologic artifacts; Operative Surgical Procedures; Orthopedics; Outcome; Radiation therapy; Research; Rewards; Scanning; System; Techniques; Time; X-Ray Computed Tomography; algorithm development; arm; clinical application; cone-beam computed tomography; design; disease diagnosis; experimental study; foot; image reconstruction; imager; imaging capabilities; improved; innovation; prototype; reconstruction; success; tool

Project Summary/Abstract The objective of the project is to develop auto-calibrating quantitative dual-energy CT (AC-QDECT) through algorithm development for accurate, simultaneous reconstruction of images and spectra on cone-beam CT (CBCT). Quantitative DECT (QDECT) is a recognized technique of significant clinical potential for improving disease diagnosis and management, and is performed currently only on advanced diagnostic (Dx) CT in which spectra must be estimated as a prior from separate measurements. There is little effort yet in developing non- Dx QDECT systems such as CBCT for use in, e.g., surgery and radiation therapy (RT); a leading reason for this is that accurate spectra cannot be measured/estimated readily in experiments in current CBCT imaging. In CBCT with AC-QDECT capability proposed, both images and spectra are treated as unknowns on an equal footing, and we develop a non-convex primal-dual (NCPD) algorithm simultaneously to yield images and spectra only from data. We will also use the NCPD algorithm to enable AC-QDECT capability on CBCT with innovative partial scanning configurations of clinical application significance. Finally, we will evaluate AC- QDECT capability enabled on CBCT in extensive simulated- and real-data studies. The project hypothesis is that CBCT with AC-QDECT capability can be enabled by use of the NCPD algorithm for yielding quantitatively accurate images without spectra as a priori estimated from separate measurements. The specific aims of the project are (1) to develop the NCPD algorithm for enabling AC-QDECT capability on CBCT and (2) to prototype and evaluate the AC-QDECT capability proposed on CBCT. The project is built upon our success research on the development of QDECT and CBCT tailored to applications growing rapidly in surgery, RT, and orthopedics. The project outcome is the establishment of the feasibility of algorithm-enabled AC-QDECT capability on CBCT, substantially expanding the application domain and utility of CBCT.

项目摘要/摘要 该项目的目的是通过通过 用于准确，同时重建图像和光谱上的算法开发锥束CT （CBCT）。定量DECT（QDECT）是一种公认​​的技术，具有改善的临床潜力的重要临床潜力 疾病诊断和管理，目前仅在高级诊断（DX）CT上进​​行 光谱必须估计为单独测量的先验。开发非 - DX QDECT系统，例如CBCT，例如手术和放射疗法（RT）；主要原因 这是在当前CBCT成像中的实验中，无法轻易测量/估计准确的光谱。在 提出具有AC-QDECT能力的CBCT，图像和光谱都被视为未知数。 立足，我们同时开发了一个非凸原始偶（NCPD）算法，以产生图像和 仅来自数据的光谱。我们还将使用NCPD算法在CBCT上启用AC-QDECT功能 临床应用显着性的创新部分扫描配置。最后，我们将评估 在广泛的模拟和真实数据研究中，CBCT启用了QDECT能力。项目假设是 可以通过使用NCPD算法来定量地启用具有AC-QDECT功能的CBCT 从单独的测量值中估算出的精确图像是没有光谱的先验图像。特定目标 项目是（1）开发用于在CBCT上启用AC-QDECT功能的NCPD算法和（2） 原型并评估CBCT提出的AC-QDECT能力。该项目建立在我们的成功之上 针对手术，RT和 骨科。项目结果是建立启用算法的AC-QDECT的可行性 CBCT上的能力，大大扩展了CBCT的应用领域和效用。