Abstract

Introduction Minimally invasive spinal surgeries rely heavily on imaging for localization of key anatomical structures. Current established modalities either do not provide adequate visualization of soft-tissue structures or do so in an indirect manner. Real-time integrated soft-tissue imaging will allow surgeons to accurately differentiate nerves, muscle, vasculature, and bone while simultaneously preventing excessive dissection of tissue and risk to patients. Areas Covered SonoVision™ is a novel imaging device able to meet the needs of intraoperative anatomical visualization. This review explains the mechanism of the device and summarizes the empirical support for its use. Multiple animal, cadaver, and human studies have been used to compile machine-learning training data and validate the system’s accuracy and usability through actual and simulated surgical scenarios. Expert Opinion SonoVision™ represents a significant improvement over current intraoperative imaging technology in terms of accuracy, efficiency, and ease of use. This system provides vital anatomical information that would otherwise be unavailable in an intuitive, real-time format. SonoVision™ may play an important role in improving outcomes in lateral approach spine surgery as well as making minimally invasive techniques more accessible to a wider range of surgeons. Article Highlights The direct lateral transpsoas approach for lumbar fusion has distinct advantages, but is associated with various complications, many of which are related to inadequate intraoperative imaging. There is a significant unmet need for real-time intraoperative soft-tissue imaging in spine surgery. The SonoVision™ ultrasound system utilizes machine-learning algorithms to provide real-time soft tissue imaging and differentiation for use during spine procedures. Early trials are promising with regard to SonoVision’s™ ability to meet needs for intraoperative soft-tissue imaging in lateral approach spine surgery.

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