Intraoperative vascular detection and three-dimensional reconstruction using statistical variance and infrared optical tracking methods in high frequency ultrasound imaging

Intraoperative characterization of blood flow and visualization of microvasculature can have a huge impact on surgical outcomes. Knowledge about vasculature can provide diagnostic leverage, reducing operating times and improving patient recovery. Currently used Doppler-based techniques suffer from various shortcomings such as poor spatial resolution, high susceptibility to motion artifacts, and the inability to detect longitudinal flows. Our aim is to develop a fast, non-invasive approach to intraoperative microvascular imaging of slow-moving blood. In this work, we present a spatio-temporal approach to detect blood flow in vessels on the order of 0.1 mm. Specifically, a speckle-variance flow processing algorithm is used to detect small changes in B-mode pixel intensity on a micro-ultrasound (μUS) system operating in the range of 22-70 MHz. Data used in this study was acquired intraoperatively for patients undergoing neurosurgical procedures. Microcirculation was clearly visible in various anatomical structures and the spatial resolution in flow detection was much superior in comparison to Doppler-based flow detection. Moreover, using infrared optical tracking (Northern Digital Inc., Waterloo, Canada), a three-dimensional reconstruction of the microvasculature was constructed. This 3D vessel map allows for better visualization of the vasculature in the surgical cavity – allowing surgeons to plan their incisions, minimizing blood loss and potentially improving patient outcomes. To our knowledge, this is the first implementation of a three-dimensional, intraoperative microcirculation imaging technique using statistical and optical methods, alongside a non-Doppler high frequency ultrasound.