Tailored Algorithms for Non-Contrast Computed Tomography Using Sinogram Restorati

描述(申请人提供)：CT扫描在静脉(IV)和/或肠道造影剂、用于改善对血管结构的辨别、改善组织特征、搜索肠穿孔或瘘管以及许多相关应用的药物的情况下和在没有静脉(IV)和/或肠道造影剂的情况下进行。静脉造影剂对肾脏有毒性作用，尤其是对肾功能受损的患者。因此，许多患者不能或不应该进行静脉增强扫描，因此经常进行非对比CT(NC-CT)扫描，尽管其固有的局限性包括较差的对比度和噪声特性。迫切需要改进这种非增强扫描的诊断性能。该项目的长期目标是使用针对特定应用优化的统计原理图像重建来克服NC-CT的局限性。通过降低噪声，同时使用投影域平滑和使用显式测量统计模型的恢复来保持分辨率，将增加固有的对比度与噪声。这项工作的成功完成可能会为慢性肾脏疾病、对比剂过敏、肥胖患者以及辐射剂量有限的筛查应用提供卓越的CT成像性能。它有4个具体目标：(1)利用特定临床CT扫描仪的统计和物理特性来合成特定于仪器的数学模型。(2)在NC-CT考试中实施惩罚式正弦图恢复方法。(3)NC-CT图像重建策略将在专用硬件上实现，以获得临床有用的重建时间。(4)将优化惩罚似然正弦图恢复策略，以提供针对特定NC-CT应用的定制算法，并在临床病例数据库中进行测试。该项目完成后，将提供一种经过验证的方法，以显著改善信噪比和对比度噪声，重建非对比CT扫描，从而提高紧急检查的诊断性能。该系统将是灵活的，在临床上可行的多中心测试在选定的应用。重建方法将针对最有前景的应用进行优化，并将提供诊断性能的初步测量。公共卫生相关性该项目的长期目标是开发和应用统计学原理的图像重建方法，用于非对比计算机断层扫描(CT)。通过降低噪声，同时使用投影域平滑和使用显式测量统计模型的恢复来保持分辨率，将增加固有的对比度与噪声。

DESCRIPTION (provided by applicant): Computed tomography (CT) scans are performed both with and without intravenous (IV) and/or enteric contrast, drugs used to improve the discrimination of vascular structures, improve tissue characterization, search for bowel perforation or fistulae, and many related applications. IV contrast is nephrotoxic, especially in patients with impaired renal function. Consequently, many patients cannot or should not have IV contrast, so non-contrast CT (NC-CT) scans are often performed, despite their intrinsic limitations, which include poor contrast-to-noise properties. There is a critical and immediate need to improve the diagnostic performance of such unenhanced scans. The long-term goal of this project is to overcome the limitations of NC-CT using statistically principled image reconstruction optimized for specific applications. The intrinsic contrast-to-noise will be increased by reducing noise while preserving resolution using projection-domain smoothing and restoration with explicit models of measurement statistics. Successful completion of this work may provide superior CT imaging performance for patients with chronic kidney disease, contrast allergy, obesity, and for screening applications where radiation dose is limited. There are 4 specific aims: (1) An instrument-specific mathematical model will be synthesized using the statistical and physical properties of a particular clinical CT scanner. (2) Penalized-likehood sinogram restoration methods will be implemented on NC-CT exams. (3) The NC-CT image reconstruction strategy will be implemented on dedicated hardware to achieve clinically useful reconstruction times. (4) The penalized-likelihood sinogram restoration strategy will be optimized to deliver tailored algorithms for specific NC-CT applications and tested on a database of clinical cases. On completion, this project will provide a validated means to reconstruct non-contrast CT scans with significantly improved signal-to-noise and contrast-to-noise, thereby improving the diagnostic performance for emergency examinations. The system will be flexible and clinically feasible for multicenter testing in selected applications. The reconstruction methods will be optimized for the most promising applications, and preliminary measurements of diagnostic performance will be available. PUBLIC HEALTH RELEVANCE The long term goal of this project is to develop and apply statistically principled image reconstruction approaches for non-contrast computed tomography (CT). The intrinsic contrast-to-noise will be increased by reducing noise while preserving resolution using projection-domain smoothing and restoration with explicit models of measurement statistics.