Intraoperative ultrasound visualization of paravertebral anatomy in the retroperitoneal space during lateral lumbar spine surgery

Systematic Review: Applications of Intraoperative Ultrasound in Spinal Surgery

BACKGROUND

Due to increased practicality and decreased costs and radiation, interest has risen for intraoperative ultrasound (iUS) in spinal surgery applications; however, few studies have provided a robust overview of its use in spinal surgery. We synthesize findings of existing literature on usage of iUS in navigation, pedicle screw placement, and identification of anatomy during spinal interventions.

METHODS

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were utilized in this systematic review. Studies were identified through PubMed, Scopus, and Google Scholar databases using the search string. Abstracts mentioning iUS in spine applications were included. Upon full-text review, exclusion criteria were implemented, including outdated studies or those with weak topic relevance or statistical power. Upon elimination of duplicates, multi-reviewer screening for eligibility, and citation search, 44 manuscripts were analyzed.

RESULTS

Navigation using iUS is safe, effective, and economical. iUS registration accuracy and success is within clinically acceptable limits for image-guided navigation (Table 2). Pedicle screw instrumentation with iUS is precise with a favorable safety profile (Table 2). Anatomical landmarks are reliably identified with iUS, and surgeons are overwhelmingly successful in neural or vascular tissue identification with iUS modalities including standard B mode, doppler, and contrast-enhanced ultrasound (CE-US) (Table 3). iUS use in traumatic reduction of fractures properly identifies anatomical structures, intervertebral disc space, and vasculature (Table 3).

CONCLUSION

iUS eliminates radiation, decreases costs, and provides sufficient accuracy and reliability in identification of anatomical and neurovascular structures in various spinal surgery settings.

Enhanced Safety of Pedicle Subtraction Osteotomy Using Intraoperative Ultrasound

BACKGROUND

Pedicle subtraction osteotomy (PSO) can improve sagittal alignment but carries risks, including iatrogenic spinal cord and nerve root injury. Critically, during the reduction phase of the technique, medullary kinking or neural element compression can lead to neurologic deficits.

METHODS

We describe 3 cases of thoracic PSO and evaluate the feasibility, findings, and utility of intraoperative ultrasound in this setting.

RESULTS

Intraoperative ultrasound can provide a visual assessment of spinal cord morphology before and after PSO reduction and influences surgical decision making with regard to the final amount of sagittal plane correction. This modality is particularly useful for confirming ventral decompression of disc-osteophyte complex before reduction and also after reduction maneuvers when there is kinking of the thecal sac but uncertainty about the underlying status of the spinal cord. Intraoperative ultrasound is a reliable modality that fits well into the technical sequence of PSO, adds a minimal amount of operative time, and has few limitations.

CONCLUSIONS

We propose that intraoperative ultrasound is a useful supplement to standard neuromonitoring modalities for ensuring safe PSO reduction and decompression of neural elements.

Artificial Intelligence-enabled, Real-time Intraoperative Ultrasound Imaging of Neural Structures Within the Psoas: Validation in a Porcine Spine Model

STUDY DESIGN

Experimental in-vivo animal study.

OBJECTIVE

The aim of this study was to evaluate an Artificial Intelligence (AI)-enabled ultrasound imaging system's ability to detect, segment, classify, and display neural and other structures during trans-psoas spine surgery.

SUMMARY OF BACKGROUND DATA

Current methodologies for intraoperatively localizing and visualizing neural structures within the psoas are limited and can impact the safety of lateral lumbar interbody fusion (LLIF). Ultrasound technology, enhanced with AI-derived neural detection algorithms, could prove useful for this task.

METHODS

The study was conducted using an in vivo porcine model (50 subjects). Image processing and machine learning algorithms were developed to detect neural and other anatomic structures within and adjacent to the psoas muscle while using an ultrasound imaging system during lateral lumbar spine surgery (SonoVision,™ Tissue Differentiation Intelligence, USA). The imaging system's ability to detect and classify the anatomic structures was assessed with subsequent tissue dissection. Dice coefficients were calculated to quantify the performance of the image segmentation.

RESULTS

The AI-trained ultrasound system detected, segmented, classified, and displayed nerve, psoas muscle, and vertebral body surface with high sensitivity and specificity. The mean Dice coefficient score for each tissue type was >80%, indicating that the detected region and ground truth were >80% similar to each other. The mean specificity of nerve detection was 92%; for bone and muscle, it was >95%. The accuracy of nerve detection was >95%.

CONCLUSION

This study demonstrates that a combination of AI-derived image processing and machine learning algorithms can be developed to enable real-time ultrasonic detection, segmentation, classification, and display of critical anatomic structures, including neural tissue, during spine surgery. AI-enhanced ultrasound imaging can provide a visual map of important anatomy in and adjacent to the psoas, thereby providing the surgeon with critical information intended to increase the safety of LLIF surgery.Level of Evidence: N/A.