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中文摘要
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描述(由申请人提供):本项目的总体目标是显著提高胎儿MRI对高危妊娠的诊断、分析和预后能力。通过胎儿MRI获得的准确分析对于评估胎儿中枢神经系统发育障碍的高度可变病因学和知之甚少的病理生理学至关重要,这种疾病影响了大约0.5%的怀孕。然而,胎儿MRI局限于通过小胎儿大脑提供的小信号进行二维采集,并且胎儿的间歇性运动破坏了先进的三维体积MRI所必需的空间编码。为了解决这一限制并揭示胎儿MRI的力量,我们提出了新的成像和图像处理技术,在本项目中追求四个具体目标;目的1是我们总体目标的关键,涉及胎儿大脑三维高空间分辨率体积T2w图像的超分辨率重建。目的2涉及胎儿脑时空图谱的构建。目的3涉及比较胎儿脑生物测量和评估使用二维MRI,二维超声和三维MRI。最后,在Aim 4中,考虑使用3D胎儿MRI改善脑室肿大的评估。脑室肿大是最常见的胎儿脑异常,影响约0.1- 0.2%的胎儿。目标1和2涉及临床使用新技术的开发,目标3和4涉及技术开发和假设检验,以了解与目前的做法相比,使用已开发的技术在评估、诊断和分析胎儿大脑异常方面取得了多大的改进。
英文摘要
DESCRIPTION (provided by applicant): The overall objective of this project is to dramatically improve the capability of fetal MRI for diagnosis, analysis, and prognosis of high-risk pregnancies. Accurate analysis obtained by fetal MRI is crucial in evaluating the highly variable aetiology and poorly understood pathophysiology of fetal central nervous system developmental disorders which affect about one-half percent of pregnancies. Nevertheless, fetal MRI is limited to two- dimensional acquisitions by the small signal available from the small fetal brain, and by intermittent fetal motion that disrupts spatial encoding necessary for advanced three-dimensional volumetric MRI. In order to address this limitation and reveal the power of fetal MRI, we propose novel imaging and image processing technology pursuing four specific aims in this project; Aim 1, which is pivotal to our overall objective, involves super- resolution reconstruction of three-dimensional high spatial resolution volumetric T2w images of the fetal brain. Aim 2 involves the construction of a spatiotemporal fetal brain atlas. Aim 3 involves the comparison of fetal brain biometry and evaluation using 2D MRI, 2D sonography and 3D MRI. Finally in Aim 4 improved assessment of ventriculomegaly is considered using 3D fetal MRI. Ventriculomegaly is the most frequently observed fetal brain abnormality affecting about 0.1-0.2 percent of fetuses. Aims 1 and 2 involve the development of new technology for clinical use and Aims 3 and 4 involve both technical developments and hypothesis tests to see how much improvement is achieved in the evaluation, diagnosis, and analysis of fetal brain abnormalities using the developed technology as compared to the current practice.
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Motion Compensated fMRI for Pre-Surgical Planning in Epilepsy
  • 批准号:
    10659634
  • 项目类别:
  • 资助金额:
    $67.11万
  • 财政年份:
    2023
  • 负责人:
    SIMON K WARFIELD
  • 依托单位:
Machine learning algorithms to analyze large medical image datasets
  • 批准号:
    10434022
  • 项目类别:
  • 资助金额:
    $37.61万
  • 财政年份:
    2021
  • 负责人:
    SIMON K WARFIELD
  • 依托单位:
Machine learning algorithms to analyze large medical image datasets
  • 批准号:
    10182522
  • 项目类别:
  • 资助金额:
    $36.96万
  • 财政年份:
    2021
  • 负责人:
    SIMON K WARFIELD
  • 依托单位:
Machine learning algorithms to analyze large medical image datasets
  • 批准号:
    10584569
  • 项目类别:
  • 资助金额:
    $37.61万
  • 财政年份:
    2021
  • 负责人:
    SIMON K WARFIELD
  • 依托单位:
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