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

脊髓针注射被广泛应用于麻醉目的：外科手术，减轻背部疼痛，以及产科的硬膜外。每年有200多万北美人接受这种手术。然而，每年约有6万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、焦虑和住院时间的增加；(2)少数患者将遭受暂时或永久的神经功能缺损；(3)感知到的风险抑制了脊髓针注射的更广泛使用。为了改善患者的治疗效果，已经提出了几种超声引导技术来更准确地放置针头。然而，麻醉医师对解剖特征的描述质量较差，并且难以解释图像，这阻碍了超声成为标准的治疗方法。我的建议引入了增强超声（i-Guide-U）技术对干预和诊断的直观指导，该技术增强了来自其他成像模式的计算机模型，以提高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，以基础解剖知识为基础，显著提高超声图像形成质量。这些方法将在脊髓针注射的背景下进行整合和评估，以提高关键解剖结构和靶向的可见性。该项目将培养两名博士、五名硕士和五名本科生从事前沿生物医学工程研究。

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.