The feasibility of computer-assisted 3D navigation in multiple-level lateral lumbar interbody fusion in combination with posterior instrumentation for adult spinal deformity

Current Trends in Artificial Intelligence-Assisted Spine Surgery: A Systematic Review

This systematic review summarizes existing evidence and outlines the benefits of artificial intelligence-assisted spine surgery. The popularity of artificial intelligence has grown significantly, demonstrating its benefits in computer-assisted surgery and advancements in spinal treatment. This study adhered to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), a set of reporting guidelines specifically designed for systematic reviews and meta-analyses. The search strategy used Medical Subject Headings (MeSH) terms, including "MeSH (Artificial intelligence)," "Spine" AND "Spinal" filters, in the last 10 years, and English- from January 1, 2013, to October 31, 2023. In total, 442 articles fulfilled the first screening criteria. A detailed analysis of those articles identified 220 that matched the criteria, of which 11 were considered appropriate for this analysis after applying the complete inclusion and exclusion criteria. In total, 11 studies met the eligibility criteria. Analysis of these studies revealed the types of artificial intelligence-assisted spine surgery. No evidence suggests the superiority of assisted spine surgery with or without artificial intelligence in terms of outcomes. In terms of feasibility, accuracy, safety, and facilitating lower patient radiation exposure compared with standard fluoroscopic guidance, artificial intelligence-assisted spine surgery produced satisfactory and superior outcomes. The incorporation of artificial intelligence with augmented and virtual reality appears promising, with the potential to enhance surgeon proficiency and overall surgical safety.

Impact of Navigation on 30-Day Outcomes for Adult Spinal Deformity Surgery

STUDY DESIGN

Retrospective database study.

OBJECTIVE

Navigation has been increasingly used to treat degenerative disease, with positive radiographic and clinical outcomes and fewer adverse events and reoperations, despite increased operative time. However, short-term analysis on treating adult spinal deformity (ASD) surgery with navigation is limited, particularly using large nationally represented cohorts. This is the first large-scale database study to compare 30-day readmission, reoperation, morbidity, and value-per-operative time for navigated and conventional ASD surgery.

METHODS

Adults were identified in the National Surgical Quality Improvement Program (NSQIP) database. Multivariate regression was used to compare outcomes between navigated and conventional surgery and to control for predictors and baseline differences.

RESULTS

3190 ASD patients were included. Navigated and conventional patients were similar. Navigated cases had greater operative time (405 vs 320 min) and mean RVUs per case (81.3 vs 69.7), and had more supplementary pelvic fixations (26.1 vs 13.4%) and osteotomies (50.3 vs 27.7%) (P <.001).In univariate analysis, navigation had greater reoperation (9.9 vs 5.2%, P = .011), morbidity (57.8 vs 46.8%, P = .007), and transfusion (52.2 vs 41.8%, P = .010) rates. Readmission was similar (11.9 vs 8.4%). In multivariate analysis, navigation predicted reoperation (OR = 1.792, P = .048), but no longer predicted morbidity or transfusion. Most reoperations were infectious and hardware-related.

CONCLUSIONS

Despite controlling for patient-related and procedural factors, navigation independently predicted a 79% increased odds of reoperation but did not predict morbidity or transfusion. Readmission was similar between groups. This is explained, in part, by greater operative time and transfusion, which are risk factors for infection. Reoperation most frequently occurred for wound- and hardware-related reasons, suggesting navigation carries an increased risk of infectious-related events beyond increased operative time.

X23D-Intraoperative 3D Lumbar Spine Shape Reconstruction Based on Sparse Multi-View X-ray Data

Visual assessment based on intraoperative 2D X-rays remains the predominant aid for intraoperative decision-making, surgical guidance, and error prevention. However, correctly assessing the 3D shape of complex anatomies, such as the spine, based on planar fluoroscopic images remains a challenge even for experienced surgeons. This work proposes a novel deep learning-based method to intraoperatively estimate the 3D shape of patients' lumbar vertebrae directly from sparse, multi-view X-ray data. High-quality and accurate 3D reconstructions were achieved with a learned multi-view stereo machine approach capable of incorporating the X-ray calibration parameters in the neural network. This strategy allowed a priori knowledge of the spinal shape to be acquired while preserving patient specificity and achieving a higher accuracy compared to the state of the art. Our method was trained and evaluated on 17,420 fluoroscopy images that were digitally reconstructed from the public CTSpine1K dataset. As evaluated by unseen data, we achieved an 88% average F1 score and a 71% surface score. Furthermore, by utilizing the calibration parameters of the input X-rays, our method outperformed a counterpart method in the state of the art by 22% in terms of surface score. This increase in accuracy opens new possibilities for surgical navigation and intraoperative decision-making solely based on intraoperative data, especially in surgical applications where the acquisition of 3D image data is not part of the standard clinical workflow.

A Retrospective Comparative Analysis of Perioperative Complications in Navigated versus Conventional Thoracolumbar Fusion in the Setting of Adult Spinal Deformity

OBJECTIVE

Stereotactic intraoperative computer-assisted navigation has been shown to improve pedicle screw accuracy in spinal fusion surgery, but evidence of impact of navigation on clinical outcomes is lacking. The aim of this study is to compare rates of perioperative complications between navigated and nonnavigated procedures for deformity correction.

METHODS

An administrative database was queried for adult patients undergoing thoracolumbar fusion procedures for deformity. Nonelective cases and those involving malignancy, infection, or trauma were excluded. Individuals were divided into 2 cohorts based on the use of stereotactic intraoperative navigation and paired 1:1 for comparison based on a propensity score matching algorithm. Rates of unplanned reoperation and other perioperative complications were compared between matched groups. A multivariable Cox regression model was constructed to identify the impact of navigation on specific subgroups.

RESULTS

A total of 6150 patients met eligibility criteria for the study; after propensity score matching, 456 patients who underwent conventional fusion were matched to 456 patients receiving intraoperative navigation. Navigated cases took an average of 30 minutes longer than nonnavigated cases. There were no significant differences in rates of complications between cohorts. A subgroup analysis revealed that use of navigation was associated with decreased hazard for reoperation in individuals undergoing interbody fusion.

CONCLUSIONS

Despite increased surgical duration, the use of navigation does not seem to significantly impact rates of perioperative complications outside of procedures involving interbody fusion. Surgeons should elect to use navigation in cases expected to be of high operative complexity at their own discretion.

Navigation and Robotic-Assisted Single-Position Prone Lateral Lumbar Interbody Fusion: Technique, Feasibility, Safety, and Case Series

BACKGROUND

Single-position prone lateral interbody fusion is a recently introduced technical modification of the minimally invasive retroperitoneal transpsoas approach for lateral lumbar interbody fusion (LLIF). Several technical descriptions of single-position prone LLIF have been published with traditional fluoroscopy for guidance. However, there has been no investigation of either three-dimensional computed tomography-based navigation for prone LLIF or integration with robotic assistance platforms with the prone lateral technique. This study evaluated the feasibility and safety of spinal navigation and robotic assistance for single-position prone LLIF.

METHODS

Retrospective review of medical records and a prospectively acquired database for a single center was performed to examine immediate and 30-day clinical and radiographic outcomes for consecutive patients undergoing single-position prone LLIF with spinal navigation and/or robotic assistance.

RESULTS

Nine patients were treated, 4 women and 5 men. Mean age was 65.4 years (range, 46-75 years), and body mass index was 30.2 kg/m² (range, 24-38 kg/m²). The most common surgical indication was adjacent segment disease (44.4%), followed by pseudarthrosis (22.2%), spondylolisthesis (11.1%), degenerative disc disease (11.1%), and recurrent stenosis (11.1%). Postoperative approach-related complications included pain-limited bilateral hip flexor weakness (4/5) and pain-limited left knee extension weakness (4/5) in 1 patient (11.1%) and right lateral thigh numbness and dysesthesia in 1 patient (11.1%). All cages were placed within quarters 2-3, signifying the middle portion of the disc space. There were no instances of misguidance by navigation.

CONCLUSIONS

Integration of spinal navigation and robotic assistance appears feasible, accurate, and safe as an alternative to fluoroscopic guidance for single-position LLIF.