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OBJECTIVE: Computed tomography is considered the gold-standard imaging tool to evaluate spinal implant accuracy. However, there are no studies that evaluate the accuracy of robotic sacroiliac joint (SIJ) implant placement using CT to date. The aim of this study was to compare the accuracy of implant placement on CT between robotic and fluoroscopic navigation for SIJ fusion and the subsequent complications and clinical outcomes of suboptimally placed screws. METHODS: A retrospective analysis of SIJ fusions utilizing either robotic or fluoroscopic guidance at a single institution was conducted from 2014 to 2023. Implant placement accuracy was evaluated on intra- or postoperative CT. Primary endpoints were SIJ screw placement accuracy and complications. Secondary endpoints were pain status at the first and second follow-ups and rates of 2-year revision surgery. Statistical analysis was performed using chi-square tests. RESULTS: Sixty-nine patients who underwent 78 SIJ fusions were included, of which 63 were robotic and 15 were fluoroscopic. The mean age of the cohort at the time of surgery was 55.9 ± 14.2 years, and 35 patients (50.7%) were female. There were 135 robotically placed and 34 fluoroscopically placed implants. A significant difference was found in implant placement accuracy between robotic and fluoroscopic fusion (97.8% vs 76.5%, p < 0.001). When comparing optimal versus suboptimal implant placement, no difference was found in the presence of 30-day complications (p = 0.98). No intraoperative complications were present in this cohort. No difference was found in subjective pain status at the first (p = 0.69) and second (p = 0.45) follow-ups between optimal and suboptimal implant placement. No patients underwent 2-year revision surgery. CONCLUSIONS: Use of robotic navigation was significantly more accurate than the use of fluoroscopic navigation for SIJ implant placement. Complications overall were low and not different between optimally and suboptimally placed implants. Suboptimally placed implants did not differ in degree of subjective pain improvement or rates of revision surgery postoperatively.
RESUMO
OBJECTIVE: Achieving appropriate spinopelvic alignment has been shown to be associated with improved clinical symptoms. However, measurement of spinopelvic radiographic parameters is time-intensive and interobserver reliability is a concern. Automated measurement tools have the promise of rapid and consistent measurements, but existing tools are still limited to some degree by manual user-entry requirements. This study presents a novel artificial intelligence (AI) tool called SpinePose that automatically predicts spinopelvic parameters with high accuracy without the need for manual entry. METHODS: SpinePose was trained and validated on 761 sagittal whole-spine radiographs to predict the sagittal vertical axis (SVA), pelvic tilt (PT), pelvic incidence (PI), sacral slope (SS), lumbar lordosis (LL), T1 pelvic angle (T1PA), and L1 pelvic angle (L1PA). A separate test set of 40 radiographs was labeled by four reviewers, including fellowship-trained spine surgeons and a fellowship-trained radiologist with neuroradiology subspecialty certification. Median errors relative to the most senior reviewer were calculated to determine model accuracy on test images. Intraclass correlation coefficients (ICCs) were used to assess interrater reliability. RESULTS: SpinePose exhibited the following median (interquartile range) parameter errors: SVA 2.2 mm (2.3 mm) (p = 0.93), PT 1.3° (1.2°) (p = 0.48), SS 1.7° (2.2°) (p = 0.64), PI 2.2° (2.1°) (p = 0.24), LL 2.6° (4.0°) (p = 0.89), T1PA 1.1° (0.9°) (p = 0.42), and L1PA 1.4° (1.6°) (p = 0.49). Model predictions also exhibited excellent reliability at all parameters (ICC 0.91-1.0). CONCLUSIONS: SpinePose accurately predicted spinopelvic parameters with excellent reliability comparable to that of fellowship-trained spine surgeons and neuroradiologists. Utilization of predictive AI tools in spinal imaging can substantially aid in patient selection and surgical planning.
Assuntos
Inteligência Artificial , Humanos , Reprodutibilidade dos Testes , Pelve/diagnóstico por imagem , Feminino , Masculino , Adulto , Coluna Vertebral/diagnóstico por imagem , Pessoa de Meia-Idade , Radiografia/métodos , Lordose/diagnóstico por imagem , Vértebras Lombares/diagnóstico por imagemRESUMO
OBJECTIVE: Emergency department visits 90 days after elective spinal surgery are relatively common, with rates ranging from 9% to 29%. Emergency visits are very costly, so their reduction is of importance. This study's objective was to evaluate the reasons for emergency department visits and determine potentially modifiable risk factors. METHODS: This study retrospectively reviewed data queried from the Michigan Spine Surgery Improvement Collaborative (MSSIC) registry from July 2020 to November 2021. MSSIC is a multicenter (28-hospital) registry of patients undergoing cervical and lumbar degenerative spinal surgery. Adult patients treated for elective cervical and/or lumbar spine surgery for degenerative pathology (spondylosis, intervertebral disc disease, low-grade spondylolisthesis) were included. Emergency department visits within 90 days of surgery (outcome measure) were analyzed utilizing univariate and multivariate regression analyses. RESULTS: Of 16,224 patients, 2024 (12.5%) presented to the emergency department during the study period, most commonly for pain related to spinal surgery (31.5%), abdominal problems (15.8%), and pain unrelated to the spinal surgery (12.8%). On multivariate analysis, age (per 5-year increase) (relative risk [RR] 0.94, 95% CI 0.92-0.95), college education (RR 0.82, 95% CI 0.69-0.96), private insurance (RR 0.79, 95% CI 0.70-0.89), and preoperative ambulation status (RR 0.88, 95% CI 0.79-0.97) were associated with decreased emergency visits. Conversely, Black race (RR 1.30, 95% CI 1.13-1.51), current diabetes (RR 1.13, 95% CI 1.01-1.26), history of deep venous thromboembolism (RR 1.28, 95% CI 1.16-1.43), history of depression (RR 1.13, 95% CI 1.03-1.25), history of anxiety (RR 1.32, 95% CI 1.19-1.46), history of osteoporosis (RR 1.21, 95% CI 1.09-1.34), history of chronic obstructive pulmonary disease (RR 1.19, 95% CI 1.06-1.34), American Society of Anesthesiologists class > II (RR 1.18, 95% CI 1.08-1.29), and length of stay > 3 days (RR 1.29, 95% CI 1.16-1.44) were associated with increased emergency visits. CONCLUSIONS: The most common reasons for emergency department visits were surgical pain, abdominal dysfunction, and pain unrelated to index spinal surgery. Increased focus on postoperative pain management and bowel regimen can potentially reduce emergency visits. The risks of diabetes, history of osteoporosis, depression, and anxiety are areas for additional preoperative screening.