Advanced Source Reconstruction Techniques for Fetal Magnetocardiography

胎儿心磁图的先进源重建技术

基本信息

  • 批准号:
    7588217
  • 负责人:
  • 金额:
    $ 22.5万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2008
  • 资助国家:
    美国
  • 起止时间:
    2008-09-30 至 2010-08-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): The early detection of congenital heart anomalies is critical for monitoring or prompt interventions, which can reduce the risks of congestive heart failure. This calls for sustained efforts to improve the existing tools and methodologies used for the non-invasive screening of the fetal heart structure and physiology. Recently, fetal magnetocardiography (fMCG) has emerged as an attractive technique for the in-utero assessment of the fetal cardiac electrophysiology, which can offer vastly superior capabilities to those, attainable by alternative methods. However, a significant concern consists in the large variability in position and orientation of the fetuses relative to the biomagnetic sensing system, which may introduce confounding effects on the morphology of the signals recorded over the maternal abdomen. The paucity of data on detailed fMCG signal morphology is a direct consequence of these confounds, since it is often difficult to explain the intersubject variations in signal distribution across the sensor array as being generated by fundamental differences in the cardiac electrophysiology, common inconsistencies in the fetal presentation or variable anatomy of the fetal- maternal unit. The current study will focus on the development of new strategies for augmenting the clinical utility the fMCG recordings, aiming at examining the cardiac activity in source space (rather than sensor space), where the above described physical factors become non-salient. The proposed approach relies on estimating the spatio temporal parameters of a multi-dipolar model of the fetal cardiac source using a recursive subspace scanning algorithm. To account for the geometry and conductivity properties of the feto-abdominal tissues, the study seeks establishing a versatile strategy for incorporating 3D anatomical information about the feto-abdominal volume conductor obtained from free-hand ultrasound images into the discrete formulation of the forward electromagnetic problem based on boundary element methods. The study will initiate the development of a longitudinal normative data-base for metrics derived from the reconstructed cardiac vectors in fMCG recordings of low-risk pregnancies. Fetal subjects with abnormal increase in the thickness of the free ventricular walls documented by ultrasound will also be studied to probe the sensitivity of the proposed approach for detecting hallmarks of abnormal heart electrophysiology. The investigation aims to represent a substantial contribution in promoting the role of fMCG for the non- invasive screening of fetal cardiac development and for the detection of electrophysiological abnormalities. The successful clinical validation of the methodology will highly recommend fMCG as an investigational tool for studying fetal cardiac electrophysiology in a broad range of conditions, particularly those associated with increased risk of ventricular hypertrophy, e.g. intra-uterine growth retardation, diabetes, pulmonary valve and aortic stenosis, closure of the ductus arteriosus, tetralogy of Fallot, or ventricular septal defect. PUBLIC HEALTH RELEVANCE: Congenital heart anomalies are more common than anomalies affecting any other organ; therefore, further advancement of the techniques used for fetal heart monitoring is likely to have a substantial impact upon public health. Fetal magnetocardiography (fMCG) offers unique capabilities for non-invasive screening of fetal cardiac electrophysiology; however, in order to attain clinical significance, fMCG must provide unequivocal and consistent measures of fetal cardiac activity. This investigation aims to represent a substantial contribution in promoting the role of fMCG for studying fetal cardiac development and electrophysiological abnormalities by means of advanced source reconstruction algorithms, which efficiently use the multichannel fMCG data and 3D ultrasound images of the feto-abdominal anatomy to provide reliable measures of fetal cardiac electrophysiology. The successful clinical validation of the methodology for fetuses with abnormal increase in ventricular wall thickness will highly recommend fMCG as an investigational tool for studying fetal cardiac electrophysiology in a broad range of conditions associated with increased risk of ventricular hypertrophy, e.g. intra-uterine growth retardation, diabetes, pulmonary valve and aortic stenosis, closure of the ductus arteriosus, tetralogy of Fallot, or ventricular septal defect.
描述(由申请人提供):早期检测先天性心脏异常对于监测或及时干预至关重要,这可以降低充血性心力衰竭的风险。这需要持续努力,以改善现有的工具和方法用于胎儿心脏结构和生理的非侵入性筛选。最近,胎儿心磁图(fMCG)已成为一种有吸引力的技术,胎儿心脏电生理的宫内评估,它可以提供大大优于那些,可通过替代方法获得的上级能力。然而,一个重要的问题在于胎儿相对于生物磁感测系统的位置和方向的大的可变性,这可能会对在母体腹部上记录的信号的形态产生混淆效应。关于详细fMCG信号形态的数据的缺乏是这些混淆的直接后果,因为通常难以解释跨传感器阵列的信号分布的受试者间变化是由心脏电生理学的基本差异、胎儿呈现的常见不一致性或胎儿-母体单元的可变解剖结构产生的。目前的研究将集中于开发用于增强fMCG记录的临床实用性的新策略,旨在检查源空间(而不是传感器空间)中的心脏活动,其中上述物理因素变得不突出。所提出的方法依赖于使用递归子空间扫描算法估计胎儿心脏源的多偶极模型的时空参数。考虑到胎儿腹部组织的几何形状和导电性能,该研究旨在建立一个通用的策略,将从徒手超声图像获得的胎儿腹部体积导体的3D解剖信息纳入基于边界元法的正向电磁问题的离散公式。该研究将启动一个纵向规范性数据库的开发,用于从低风险妊娠的fMCG记录中重建的心脏向量中获得的指标。还将研究通过超声记录的游离心室壁厚度异常增加的胎儿受试者,以探索所提出的方法检测异常心脏电生理学标志的灵敏度。该研究旨在为促进fMCG在胎儿心脏发育的无创筛查和电生理异常检测中的作用做出实质性贡献。该方法的成功临床验证将强烈推荐fMCG作为研究广泛条件下胎儿心脏电生理学的研究工具,特别是与心室肥大风险增加相关的条件,例如宫内生长迟缓,糖尿病,肺动脉瓣和主动脉瓣狭窄,动脉导管闭合,法洛四联症或室间隔缺损。公共卫生关系:先天性心脏异常比影响任何其他器官的异常更常见;因此,用于胎儿心脏监测的技术的进一步发展可能会对公共卫生产生重大影响。胎儿心磁图(fMCG)为胎儿心脏电生理学的非侵入性筛查提供了独特的功能;然而,为了获得临床意义,fMCG必须提供胎儿心脏活动的明确和一致的测量。本研究旨在通过先进的源重建算法,有效地利用多通道fMCG数据和胎儿腹部解剖结构的3D超声图像,提供可靠的胎儿心脏电生理学测量,为促进fMCG在研究胎儿心脏发育和电生理异常中的作用做出实质性贡献。心室壁厚度异常增加的胎儿的方法学的成功临床验证将强烈推荐fMCG作为研究与心室肥大风险增加相关的广泛条件下的胎儿心脏电生理学的研究工具,例如宫内生长迟缓,糖尿病,肺动脉瓣和主动脉瓣狭窄,动脉导管闭合,法洛四联症,或室间隔缺损。

项目成果

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MIHAI POPESCU其他文献

MIHAI POPESCU的其他文献

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{{ truncateString('MIHAI POPESCU', 18)}}的其他基金

Advanced Source Reconstruction Techniques for Fetal Magnetocardiography
胎儿心磁图的先进源重建技术
  • 批准号:
    7694284
  • 财政年份:
    2008
  • 资助金额:
    $ 22.5万
  • 项目类别:

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