Vector Flow Velocity Imaging of Human Placenta using Angle-resolved Ultrasound and Deep Learning

使用角度分辨超声和深度学习对人胎盘进行矢量血流速度成像

• 批准号: 10886180
• 负责人: You Li
• 金额: $ 24.88万
• 依托单位: UNIVERSITY OF TEXAS DALLAS
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10886180
• 关键词: Acoustics; Affect; Artificial Intelligence; Biology; Biomedical Engineering; Blood; Blood flow; Chorionic villi; Clinic; Clinical; Clinical Research; Clinical assessments; Complex; Data; Data Science; Development; Diameter; Discipline of obstetrics; Disease; Doppler Ultrasound; Faculty; Fetal Growth Retardation; Fetus; Future; Growth; Gynecology; Human; Human Development; Image; Imaging Device; Imaging Techniques; Imaging technology; Investigation; Knowledge; Late pregnancy; Lateral; Machine Learning; Manuals; Maternal Mortality; Measurement; Measures; Medical Imaging; Mentors; Methodology; Modeling; Monitor; Mothers; Network-based; Neural Network Simulation; Noise; Output; Pattern; Physiological; Placenta; Placenta Accreta; Placenta Diseases; Placental Insufficiency; Placentation; Play; Pre-Eclampsia; Pregnancy; Pregnant Women; Premature Labor; Program Development; Radiology Specialty; Research; Research Personnel; Resolution; Role; Spiral Artery of the Endometrium; Structure; System; Techniques; Technology; Testing; Time; Tissues; Training; Translating; Translational Research; Trees; Ultrasonic wave; Ultrasonography; Uncertainty; United States; Universities; Villous; Virginia; Visualization; career; career development; cohort; deep learning; deep learning model; deep neural network; design; early pregnancy; fetal; hemodynamics; human imaging; imaging modality; imaging system; in vivo; machine learning model; millimeter; multidisciplinary; neural network; neural network architecture; new technology; novel; parallelization; programs; quantitative imaging; research and development; simulation; skill acquisition; skills; technique development; tenure track; tool; transmission process; ultrasound; vector

This proposal describes a five-year research and career development program to prepare Dr. You Li for a career as an independent investigator. The program will build upon Dr. Li’s multidisciplinary background as a biomedical engineer, trained in medical ultrasound imaging, by providing expertise in obstetrics, the application of machine learning in medical imaging, and translational research. The PI will be mentored at Stanford University by Drs. Jeremy Dahl (primary mentor, medical ultrasound), Virginia Winn (co-mentor, obstetrics and gynecology), and Matthew Lungren (co-mentor, radiology and artificial intelligence). Human placenta plays a vital role in human development, and its abnormalities may cause significant consequences to both the mother and the fetus. Preeclampsia, in particular, is a common disorder that affects approximately 1 in 33 pregnancies in the United States and accounts for 18% of pregnancy-associated maternal death. Many placental abnormalities, including preeclampsia, are related to the hemodynamics and growth of vessels in placenta. Despite the severe consequences of placental abnormalities, our understanding in placenta and placental abnormalities is lacking. One primary reason for the gap of knowledge is the inability to observe the hemodynamics of placenta in vivo. Currently, B-mode and Doppler ultrasound are the primary imaging modalities in imaging the placenta and its vasculature. However, significant limitations exist in the ability of Doppler ultrasound to visualize and measure detailed flow velocities in placental vasculature. It has low sensitivity to small vessels in the placenta, including spiral arteries and chorionic villi, and can only measure flow velocity along the ultrasound beam direction, requiring tedious manual angle correction for flow along any of the visible vessels if quantitative information is desired. These limitations make conventional Doppler ultrasound poorly suited for imaging the hemodynamics of the complex vasculature of human placenta. To provide full and detailed characterization of placental hemodynamics, we propose to develop a vector flow velocity imaging technique using deep neural network models and multiple angle plane wave ultrasound transmits. This technique will be able to quantitatively image both the flow velocity magnitudes and flow directions of millimeter-diameter vessels in human placenta over a large field of view. Aim 1 and 2 will be focused on the technical development of the technique to provide a semi- real-time vector flow imaging system based on a research ultrasound scanner, paving way for Aim 3, which will be focused on validating the clinical value of the technique on a pilot clinical study to image the hemodynamics in spiral arteries and chorionic villi of pregnant women. Successful completion of the project will provide a novel technique for the scientific and early clinical assessment of placental hemodynamics, development, and abnormalities including the development of the villous tree structure, placenta accreta, preeclampsia, and placental insufficiency. During the project, the PI will receive training in machine learning, obstetrics, translational research, and career development skills, which will transition the PI into an independent faculty.

该建议描述了一项为期五年的研究和职业发展计划，以准备您的职业生涯 作为独立研究员。该计划将基于Li博士的多学科背景作为生物医学 通过提供机器的应用专业知识，通过提供医疗超声成像的工程师 在医学成像中学习和翻译研究。 Drs将在斯坦福大学考虑PI。 杰里米·达尔（Jeremy Dahl）（主要的心理，医学超声），弗吉尼亚·温恩（妇产科，妇产科）， 马修·伦格伦（Matthew Lungren）（放射学和人工智能的同事）。人斑点在人类中起着至关重要的作用 发育及其异常可能会对母亲和胎儿造成重大影响。 尤其是防护症是一种常见疾病，在联合 国家和占妊娠相关的遗产死亡的18％​​。许多胎盘异常，包括 先兆子痫与血液动力学和血管生长有关。尽管很严重 缺乏位置异常的后果，我们对胎盘和斑点异常的理解缺乏。 知识差距的主要原因之一是无法观察体内胎盘的血液动力学。 目前，B模式和多普勒超声是成像plapeta及其成像的主要成像方式 脉管系统。但是，多普勒超声可视化和测量的能力存在着显着的局限性 位置脉管系统中的详细流速。它对胎盘中的小血管的敏感性低，包括 螺旋动脉和绒毛膜绒毛，只能测量沿超声梁方向的流速， 如果定量信息是 需要。这些局限性使常规多普勒超声检查不适合想象血液动力学 人胎盘的复杂脉管系统。提供完整而详细的装修表征 血液动力学，我们建议使用深神经网络开发矢量流速度成像技术 模型和多角平面波超声传输。该技术将能够定量图像 在人plapeta中，流速幅度和毫米直径vissels的流速度方向 大视野。 AIM 1和2将集中在技术的技术发展上，以提供半 基于研究超声扫描仪的实时矢量流成像系统，AIM 3的铺路方式，这将 专注于在试验临床研究中验证技术的临床价值，以对血液动力学成像 在孕妇的螺旋动脉和绒毛膜绒毛中。成功完成项目将提供小说 科学和早期临床评估的技术对位置血液动力学，发育和 异常，包括绒毛结构的发展，Pleceta Accreta，先兆子痫和 胎盘不足。在项目期间，PI将接受机器学习，产科，翻译的培训 研究和职业发展技能将把PI转变为独立的教师。