课题基金 / 基金详情

项目摘要

项目成果

Adam M Alessio的其他基金

相似基金

相关文献

中文摘要
翻译
本提案的目的是开发临床可行的策略,通过动态计算机断层扫描(CT)成像,在与普通核心肌灌注研究相当的低辐射剂量下定量估计心肌血流量(MBF)。尽管量化MBF(以ml/g/min为单位)的临床价值已得到证实,但目前还没有广泛的临床方法可以轻松地以绝对单位测量MBF。动态CT提供了量化流量的潜力,但这些研究所传递的辐射剂量不能被广泛接受。该建议的具体目标是开发1)最佳心肌血流量估计方法,2)用于MBF估计的低剂量动态CT采集策略,3)无偏数据恢复算法和4)基于权衡空间分辨率的图像重建方法,以降噪和用先验知识约束噪声。这些目标将通过模拟动态对比增强CT成像来发展,并通过患者检查来评估。我们假设,通过选择采集策略和明智地应用降噪策略,可以通过低剂量动态CT确定准确的心内和心下MBF估计。这项工作提出了新的低剂量采集和数据/图像增强策略,能够以ml/g/min的绝对单位准确定量估计血流量。这些方法将大大降低辐射剂量,这对患者安全、动态CT用于MBF测量的临床应用以及其他已证实的动态CT应用至关重要。这项工作将使心脏动态CT成为一种安全、简单、广泛可用的定量MBF评估工具,为定量血流受限疾病提供有价值的临床信息,减少不必要的导管手术,为治疗选择提供信息,并开发新的治疗方法。
英文摘要
DESCRIPTION (provided by applicant) The objective of this proposal is to develop clinically viable strategies for the quantitative estimation of myocardial blood flow (MBF) from dynamic computed tomography (CT) imaging with low radiation doses comparable to those received in common nuclear myocardial perfusion studies. Despite the proven clinical value of quantifying MBF (in ml/g/min), there are no widespread clinical methods to easily measure MBF in absolute units. Dynamic CT offers the potential to quantify flow, but the radiation dose imparted from these studies prohibits widespread acceptance. The specific aims of the proposal are to develop 1) optimal myocardial blood flow estimation methods, 2) low-dose dynamic CT acquisition strategies for MBF estimation, 3) unbiased data restoration algorithms and 4) image reconstruction methods based on trading off spatial resolution for noise reduction and constraining noise with a priori knowledge. These aims will be developed with simulations of dynamic contrast enhanced CT imaging and evaluated with patient exams. We hypothesize that accurate subendo- and subepi-cardial MBF estimates can be determined with low- dose dynamic CT through selection of acquisition strategies and judicious application of noise reduction strategies. This work proposes novel low-dose acquisition and data/image enhancement strategies to enable accurate quantitative estimates of blood flow in absolute units of ml/g/min. These methods will allow for substantial reductions in radiation dose, which is essential for patient safety, clinical application of dynamic CT for MBF measurement, and for other proven applications of dynamic CT. This work will position cardiac dynamic CT as a safe, easy, and widely available tool for quantitative MBF estimation, providing valuable clinical information for quantification of flow limiting disease, minimizing unnecessary catheterization procedures, informing therapy choices, and developing new therapies.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Development of Artificial Intelligence (AI) based algorithms to classify the Pneumoconioses
  • 批准号:
    10428946
  • 项目类别:
  • 资助金额:
    $21.7万
  • 财政年份:
    2022
  • 负责人:
    Adam M Alessio
  • 依托单位:
Development of Artificial Intelligence (AI) based algorithms to classify the Pneumoconioses
  • 批准号:
    10709621
  • 项目类别:
  • 资助金额:
    $20.16万
  • 财政年份:
    2022
  • 负责人:
    Adam M Alessio
  • 依托单位:
Automatic Rib Fracture Detection in Pediatric Radiography to Identify Non-Accidental Trauma
  • 批准号:
    9976563
  • 项目类别:
  • 资助金额:
    $17.81万
  • 财政年份:
    2019
  • 负责人:
    Adam M Alessio
  • 依托单位:
IEEE Medical Imaging Conference
  • 批准号:
    8910150
  • 项目类别:
  • 资助金额:
    $1.0万
  • 财政年份:
    2015
  • 负责人:
    Adam M Alessio
  • 依托单位:
海外基金