Intuitive Guidance for Intervention and Diagnosis with Enhanced Ultrasound (i-Guide-U)

脊椎注射被广泛应用于麻醉目的：手术、缓解背痛以及产科的硬膜外麻醉。每年有200多万北美人接受这种手术。然而，每年约有60,000名患者经历与针头放置不准确相关的并发症。这些并发症有三个后果：(1)疼痛、焦虑和住院时间增加，(2)少数患者将出现暂时性或永久性的神经功能障碍，(3)感知的风险阻碍了更广泛地使用脊椎针头注射。为了改善患者的预后，已经提出了几种超声引导技术来更准确地放置针头。然而，麻醉师面临着解剖特征描述质量差和图像解释困难的问题，阻碍了超声成为护理的标准。我的建议引入了使用增强超声(I-Guide-U)技术的介入和诊断的直观指导，该技术增强了来自其他成像方式的计算机模型，以改善超声图像的质量并增强解释。它首次将医学图像配准和超声组织分型相结合，基于潜在的解剖学知识显著提高了超声图像的形成质量。这些方法将在脊柱注射的背景下进行整合和评估，以改善关键解剖结构和靶向的可见性。该项目将培养尖端生物医学工程研究领域的两名博士、五名硕士和五名本科生。

Spinal needle injections are widely applied for anesthetic purposes: for surgery, for the relief of back pain, and for epidurals in obstetrics. More than two million North Americans undergo these procedures each year. However, about 60,000 patients per year experience complications associated with inaccurate placement of the needle. These complications have three consequences: (1) an increase in pain, anxiety and the length of hospital stay, (2) a small number of patients will suffer temporary or permanent neurologic deficit, and (3) the perceived risk inhibits more widespread use of spinal needle injections. To improve patient outcomes, several ultrasound-guided techniques have been proposed for more accurate placement of the needle. However, anesthesiologists experience poor quality depiction of anatomical features and difficulty in interpreting images, preventing ultrasound from becoming the standard-of-care.My proposal introduces intuitive guidance for intervention and diagnosis with enhanced ultrasound (i-Guide-U) technologies that augment computer models derived from other imaging modalities to improve the quality of ultrasound images and enhance interpretations. For the first time, it combines medical image registration and ultrasound tissue typing to dramatically improve ultrasound image formation quality based on the knowledge of the underlying anatomy. These methods will be integrated and evaluated in the context of spinal needle injection for improved visibility of critical anatomical structures and targeting. This program will train two PhD, five MSc and five undergraduate students in leading edge biomedical engineering research.