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OBJECTIVE Treatment of primary spinal infection includes medical management with or without surgical intervention. The objective of this study was to identify risk factors for the eventual need for surgery in patients with primary spinal infection on initial presentation. METHODS From January 2010 to July 2019, 275 patients presented with primary spinal infection. Demographic, infectious, imaging, laboratory, treatment, and outcome data were retrospectively reviewed and collected. Thirty-three patients were excluded due to insufficient follow-up (≤ 90 days) or death prior to surgery. RESULTS The mean age of the 242 patients was 58.8 ± 13.6 years. The majority of the patients were male (n = 130, 53.7%), White (n = 150, 62.0%), and never smokers (n = 132, 54.5%). Fifty-four patients (22.3%) were intravenous drug users. One hundred fifty-four patients (63.6%) ultimately required surgery while 88 (36.4%) never needed surgery during the duration of follow-up. There was no significant difference in age, gender, race, BMI, or comorbidities between the surgery and no-surgery groups. On univariate analysis, the presence of an epidural abscess (55.7% in the no-surgery group vs 82.5% in the surgery group, p < 0.0001), the median spinal levels involved (2 [interquartile range (IQR) 2–3] in the no-surgery group vs 3 [IQR 2–5] in the surgery group, p < 0.0001), and active bacteremia (20.5% in the no-surgery vs 35.1% in the surgery group, p = 0.02) were significantly different. The cultured organism and initial laboratory values (erythrocyte sedimentation rate, C-reactive protein, white blood cell count, creatinine, and albumin) were not significantly different between the groups. On multivariable analysis, the final model included epidural abscess, cervical or thoracic spine involvement, and number of involved levels. After adjusting for other variables, epidural abscess (odds ratio [OR] 3.04, 95% confidence interval [CI] 1.64–5.63), cervical or thoracic spine involvement (OR 2.03, 95% CI 1.15–3.61), and increasing number of involved levels (OR 1.16, 95% CI 1.01–1.35) were associated with greater odds of surgery. Fifty-two surgical patients (33.8%) underwent decompression alone while 102 (66.2%) underwent decompression with fusion. Of those who underwent decompression alone, 2 (3.8%) of 52 required subsequent fusion due to kyphosis. No patient required hardware removal due to persistent infection. CONCLUSIONS At time of initial presentation of primary spinal infection, the presence of epidural abscess, cervical or thoracic spine involvement, as well as an increasing number of involved spinal levels were potential risk factors for the eventual need for surgery in this study. Additional studies are needed to assess for risk factors for surgery and antibiotic treatment failure.

OBJECTIVE Augmented reality (AR) is a novel technology which, when applied to spine surgery, offers the potential for efficient, safe, and accurate placement of spinal instrumentation. The authors report the accuracy of the first 205 pedicle screws consecutively placed at their institution by using AR assistance with a unique head-mounted display (HMD) navigation system. METHODS A retrospective review was performed of the first 28 consecutive patients who underwent AR-assisted pedicle screw placement in the thoracic, lumbar, and/or sacral spine at the authors’ institution. Clinical accuracy for each pedicle screw was graded using the Gertzbein-Robbins scale by an independent neuroradiologist working in a blinded fashion. RESULTS Twenty-eight consecutive patients underwent thoracic, lumbar, or sacral pedicle screw placement with AR assistance. The median age at the time of surgery was 62.5 (IQR 13.8) years and the median body mass index was 31 (IQR 8.6) kg/m2. Indications for surgery included degenerative disease (n = 12, 43%); deformity correction (n = 12, 43%); tumor (n = 3, 11%); and trauma (n = 1, 4%). The majority of patients (n = 26, 93%) presented with low-back pain, 19 (68%) patients presented with radicular leg pain, and 10 (36%) patients had documented lower extremity weakness. A total of 205 screws were consecutively placed, with 112 (55%) placed in the lumbar spine, 67 (33%) in the thoracic spine, and 26 (13%) at S1. Screw placement accuracy was 98.5% for thoracic screws, 97.8% for lumbar/S1 screws, and 98.0% overall. CONCLUSIONS AR depicted through a unique HMD is a novel and clinically accurate technology for the navigated insertion of pedicle screws. The authors describe the first 205 AR-assisted thoracic, lumbar, and sacral pedicle screws consecutively placed at their institution with an accuracy of 98.0% as determined by a Gertzbein-Robbins grade of A or B.

OBJECTIVE In the treatment of spinal metastases with stereotactic body radiation therapy (SBRT), vertebral compression fracture (VCF) is a common and potentially morbid complication. Better methods to identify patients at high risk of radiation-induced VCF are needed to evaluate prophylactic measures. Radiomic features from pretreatment imaging may be employed to more accurately predict VCF. The objective of this study was to develop and evaluate a machine learning model based on clinical characteristics and radiomic features from pretreatment imaging to predict the risk of VCF after SBRT for spinal metastases. METHODS Vertebral levels C2 through L5 containing metastases treated with SBRT were included if they were naive to prior surgery or radiation therapy, target delineation was based on consensus guidelines, and 1-year follow-up data were available. Clinical features, including characteristics of the patient, disease, and treatment, were obtained from chart review. Radiomic features were extracted from the planning target volume (PTV) on pretreatment CT and T1-weighted MRI. Clinical and radiomic features selected by least absolute shrinkage and selection operator (LASSO) regression were included in random forest classification models, which were trained to predict VCF within 1 year after SBRT. Model performance was assessed with leave-one-out cross-validation. RESULTS Within 1 year after SBRT, 15 of 95 vertebral levels included in the analysis demonstrated new or progressive VCF. Selected clinical features included BMI, performance status, total prescription dose, dose to 99% of the PTV, lumbar location, and 2 components of the Spine Instability Neoplastic Score (SINS): lytic tumor character and spinal misalignment. Selected radiomic features included 5 features from CT and 3 features from MRI. The best-performing classification model, derived from a combination of selected clinical and radiomic features, demonstrated a sensitivity of 0.844, specificity of 0.800, and area under the receiver operating characteristic (ROC) curve (AUC) of 0.878. This model was significantly more accurate than alternative models derived from only selected clinical features (AUC = 0.795, p = 0.048) or only components of the SINS (AUC = 0.579, p < 0.0001). CONCLUSIONS In the treatment of spinal metastases with SBRT, a machine learning model incorporating both clinical features and radiomic features from pretreatment imaging predicted VCF at 1 year after SBRT with excellent sensitivity and specificity, outperforming models developed from clinical features or components of the SINS alone. If validated, these findings may allow more judicious selection of patients for prophylactic interventions.

En bloc spinal tumor resections are technically demanding procedures with high morbidity because of the conventionally large exposure area and aggressive resection goals. Stereotactic surgical navigation presents an opportunity to perform the smallest possible resection plan while still achieving an en bloc resection. Augmented reality (AR)–mediated spine surgery (ARMSS) via a mounted display with an integrated tracking camera is a novel FDA-approved technology for intraoperative “heads up” neuronavigation, with the proposed advantages of increased precision, workflow efficiency, and cost-effectiveness. As surgical experience and capability with this technology grow, the potential for more technically demanding surgical applications arises. Here, the authors describe the use of ARMSS for guidance in a unique osteotomy execution to achieve an en bloc wide marginal resection of an L1 chordoma through a posterior-only approach while avoiding a tumor capsule breach. A technique is described to simultaneously visualize the navigational guidance provided by the contralateral surgeon’s tracked pointer and the progress of the BoneScalpel aligned in parallel with the tracked instrument, providing maximum precision and safety. The procedure was completed by reconstruction performed with a quad-rod and cabled fibular strut allograft construct, and the patient did well postoperatively. Finally, the authors review the technical aspects of the approach, as well as the applications and limitations of this new technology.

Low-flow spinal extradural arteriovenous fistulas (SEAVFs) are frequently misdiagnosed as spinal dural arteriovenous fistulas (SDAVFs), and their true prevalence is unknown. The principal feature distinguishing low-flow SEAVFs from SDAVFs is the location of the shunt, which involves a pouch of epidural plexus in SEAVFs and a radiculomedullary vein (RMV) in SDAVFs. A venous hypertensive myelopathy comparable to the one observed with SDAVFs develops when the arterialized venous pouch of an SEAVF is connected to an RMV. Depending on the size of the epidural pouch, a low-flow SEAVF may uncommonly drain into multiple RMVs. The authors present an observation of a low-flow SEAVF whose double radiculomedullary drainage was revealed only after intraoperative digital subtraction angiography, and they discuss the surgical implications of this anatomical configuration.