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中文摘要
翻译
描述(申请人提供):计算机断层扫描(CT)对现代医学的重要贡献显而易见。近年来,与身体CT相关的辐射剂量问题受到了广泛的关注,部分原因是它的成功和较高的临床使用率。由于不存在与当前CT辐射暴露水平相关的非零风险,因此迫切需要在身体CT中采取更有力的剂量减少策略。然而,这一点必须在诊断准确性方面不能有明显的妥协。该提案的首要目标是开发、优化和评估一种迭代图像重建算法,该算法承诺在不影响诊断准确性的情况下,将辐射剂量从当前水平降低70%-90%。通过使用所提出的DR-PICCS重建,亚mSv腹部CT扫描可以在许多临床应用中保持诊断的准确性,例如评估尿路结石和结直肠息肉。对于其他诊断成像应用,也可以在保持诊断性能的情况下,将剂量减少约70%-90%。我们的回溯性和前瞻性试点研究的初步结果表明,我们的合作翻译研究小组拟议的研究是可行的。为了实现我们提出的总体目标,我们将实现以下具体目标:(1)优化DR-PICCS用于超低剂量腹部CT成像的实施方案;(2)对使用DR-PICCS重建算法重建的超低剂量诊断性腹部CT图像进行前瞻性验证。其目的包括:(1)展示超低剂量DR-PICCs重建图像与当前标准剂量FBP图像在图像噪声和诊断准确性方面的等价性;(2)超低剂量CT与DR-PICCs重建技术与其他商用重建技术的性能比较;(3)用于仿真结肠镜(CT)检查的亚mSv CT成像的前瞻性验证。该项目的成功完成将提供有关超低剂量腹部CT成像的临床可行性和实用性的宝贵信息,包括实用技术的优化(目标1)、诊断准确性的验证(目标2)以及在结直肠癌筛查中的应用(目标3)。该项目的成功完成还将提供临床评估其他超低剂量CT成像重建方法所需的方法学范例和独特的CT数据集。
英文摘要
DESCRIPTION (provided by applicant): The important contribution of computed tomography (CT) to modern medicine is readily apparent. Recently, the issue of the radiation dose related to body CT has received considerable attention, in part because of its success and high rate of clinical utilization. Because the absence of a non-zero risk related to the current levels of radiation exposures from CT cannot be conclusively proven, there is a dire need for more robust dose reduction strategies at body CT. This, however, must be implemented without a significant compromise in diagnostic accuracy. The overarching objective of the proposal is to develop, optimize, and evaluate an iterative image reconstruction algorithm that holds a promise to reduce radiation dose by 70%-90% from current levels, without compromising diagnostic accuracy. By employing the proposed DR-PICCS reconstruction, sub-mSv abdominal CT scanning with preserved diagnostic accuracy may be achievable for a number of clinical applications, such as evaluation for urolithiasis and colorectal polyps. For other diagnostic imaging applications, dose reductions on the order of 70%-90% may be possible, again with preserved diagnostic performance. Preliminary results from our retrospective and prospective pilot studies have demonstrated the feasibility of the proposed study by our collaborative translational research group. The following specific aims will be carried out to accomplish our proposed overall objective: (1) Optimization of the DR-PICCS implementation for ultra-low-dose abdominal CT imaging; (2) Prospective validation of ultra-low- dose diagnostic abdominal CT images reconstructed with DR-PICCS reconstruction algorithm. This aim includes demonstration of equivalence in image noise and diagnostic accuracy between ultra-low-dose DR- PICCS reconstructions and current standard-of-care dose FBP images; and performance comparison of ultra- low-dose CT with DR-PICCS against other commercially-available reconstruction techniques; and (3) Prospective validation of sub-mSv CT imaging for virtual colonoscopy (CT colonography) screening. Successful completion of this project will provide valuable information about the clinical feasibility and utility of ultra-low-dose abdominal CT imaging, including optimization of a practical technique (Aim 1), validation of diagnostic accuracy (Aim 2), and application to colorectal cancer screening (Aim 3). The successful completion of the project will also provide a methodological paradigm and unique CT data sets needed to clinically evaluate other ultra-low-dose CT imaging reconstruction methods.
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Next Generation Cone Beam CT with Improved Contrast Resolution and Added Spectral Imaging Functionality
  • 批准号:
    10660754
  • 项目类别:
  • 资助金额:
    $60.82万
  • 财政年份:
    2023
  • 负责人:
    Guang-Hong Chen
  • 依托单位:
Clinical Translation of a One-Stop-Shop Imaging Method for Abdominal CT
  • 批准号:
    10522078
  • 项目类别:
  • 资助金额:
    $62.23万
  • 财政年份:
    2022
  • 负责人:
    Guang-Hong Chen
  • 依托单位:
Clinical Translation of a One-Stop-Shop Imaging Method for Abdominal CT
  • 批准号:
    10686103
  • 项目类别:
  • 资助金额:
    $60.18万
  • 财政年份:
    2022
  • 负责人:
    Guang-Hong Chen
  • 依托单位:
Functional Lung Imaging Using a Single kV CT Acquisition
  • 批准号:
    10436306
  • 项目类别:
  • 资助金额:
    $75.96万
  • 财政年份:
    2021
  • 负责人:
    Guang-Hong Chen
  • 依托单位:
海外基金