Freedman, Brett A.

BACKGROUND Septic facet cysts are a rare phenomenon reported in the literature among immunocompromised hosts and may require operative intervention for appropriate source and symptomatic control. OBSERVATIONS A 70-year-old male with a past medical history of immunoglobulin A lambda smoldering myeloma degenerative lumbar disease who presented with low back and radicular lower extremity pain was found to have a left L4–5 septic facet cyst with extension to the epidural space. Intraoperative cultures were positive for Nocardia species. Staging workup revealed progression to high-risk-profile multiple myeloma. LESSONS Patients with septic facet cysts may require operative intervention for appropriate source control. Nocardia spine infections and septic facet cysts are rare and require investigation of preexisting risk factors and any potential underlying immunocompromise. https://thejns.org/doi/10.3171/CASE25220

Background: Estimating operative time with low accuracy and precision leads to suboptimal scheduling of available operating rooms (ORs) and waste of healthcare resources. We aimed to develop a predictive machine learning (ML) model for operative time using our institutional data to improve the scheduling of neurosurgical ORs, minimize waste, and maximize resource utilization. Methods: We developed a predictive model using our institution’s multicenter registry, which included diverse neurosurgical cases across three tertiary hospitals. We applied multiple ML techniques, including linear regression, support vector regression, deep neural networks, and extreme gradient boosting regression (XGBR). The best model was combined with the first fit decreasing bin-packing algorithm to create a practical OR scheduling system based on prior data. Results: The XGBR model exhibited the best performance, with lower mean absolute errors (MAEs) (root mean squared error: 52.24, MAE: 37.25) and higher R2 (0.76) values than other models. Implementing this model in a simulated OR scheduling scenario using institutional data, we successfully scheduled 30 random procedures with minimal residual time, such that the model ran out of procedures for the week with 86 and 171 min remaining in the cranial and spinal ORs, respectively, demonstrating potential efficiency gains. The cranial procedures were scheduled over 4 days and spinal procedures over 6 days, optimizing available OR time. Conclusion: Integrating ML models into operative time prediction can significantly improve the accuracy and efficiency of surgical schedules. This approach minimizes wasted OR time and enhances resource allocation, potentially improving patient outcomes and satisfaction by reducing waiting times.

OBJECTIVE Proximal junctional kyphosis (PJK) affects 5%–61% of patients following thoracolumbar fusion. Many patients are asymptomatic, but a plurality require surgical revision at a cost of $75,000 per case. This analysis sought to analyze the degree to which bone quality and paraspinal muscle sarcopenia influence PJK failure mode. METHODS Patients undergoing thoracolumbar instrumented fusion with an upper instrumented vertebra (UIV) at the thoracolumbar junction (T10–L2) were identified and data were gathered on surgery, bone quality, pre- and postoperative sagittal alignment, and paraspinal muscle cross-sectional area (CSA). PJK was defined as a ≥ 10° increase in proximal junctional angle from the first postoperative radiograph. PJK was classified as discoligamentous failure (type 1), bone failure (type 2), or screw-bone interface failure (type 3) according to the Yagi-Boachie system. Bone quality was assessed by Hounsfield units (HUs) and the vertebral bone quality (VBQ) score at the UIV. RESULTS One hundred fifty patients were identified (median age 67 years, 53.3% female), 46 of whom experienced PJK (22 type 1, 13 type 2, 11 type 3). The median time to onset was most rapid for type 2 events (2.6 months). There were no differences between patients experiencing PJK versus controls regarding bone quality (HUs or VBQ score) or paraspinal muscle CSA on univariate comparison. However, subdivision by PJK type showed patients experiencing bone failure (type 2) PJK had significantly lower HUs at the UIV and UIV+1 relative to those experiencing type 1 PJK or no PJK (all p < 0.05). The VBQ score trended toward being significant, with a higher VBQ score (worse bone quality) in those suffering type 2 PJK, but did not reach statistical significance (p = 0.07). Patients experiencing discoligamentous failure PJK (type 1) had small multifidus CSA (390 mm 2 ) relative to patients experiencing type 2 (516 mm 2 ) or type 3 (440 mm 2 ) PJK and patients who did not experience PJK (481 mm 2 ), although the difference did not reach statistical significance. On time-to-event analysis, low HUs of the UIV/UIV+1 predicted type 2 (hazard ratio [HR] 0.81, 95% CI 0.70–0.93; p = 0.002) and type 2/3 PJK (HR 0.87, 95% CI 0.78–0.96; p = 0.006) but not type 1 PJK. Low UIV multifidus CSA trended toward being a significant predictor of type 1 PJK (HR 0.85, 95% CI 0.69–1.05; p < 0.10). CONCLUSIONS The combination of underlying bone quality and paraspinal musculature CSA at the UIV appeared to influence failure mode among patients who underwent lumbosacral instrumented fusion terminating at the thoracolumbar junction.

OBJECTIVE The present investigation aimed to 1) develop a new CT-based assessment of endplate bone density (endplate Hounsfield unit [EP-HU]) and 2) analyze if EP-HU was a better predictor than vertebral Hounsfield unit (HU) for subsidence after anterior cervical discectomy and fusion (ACDF). METHODS All adult patients who underwent one- to three-level ACDF with a titanium interbody for radiculopathy and/or myelopathy at an academic center between 2018 and 2020 were retrospectively identified. Based on preoperative sagittal CT scans (left, right, and middle cuts), 2-mm superior and inferior endplate regions were circumscribed with the free draw tool to account for endplate surface undulations. The average of the superior and inferior EP-HUs on all CT cuts was used to calculate EP-HU. Cervical vertebral HUs were determined from the average of axial CT cranial, middle, and caudal cuts circumscribing only trabecular bone. The interbody subsidence of the cranial and caudal endplates of each ACDF level was directly measured on the endplate-facing surface of both coronal and sagittal cuts of postoperative CT scans (at 1 year) to determine the maximum subsidence (subsidence defined as ≥ 2 mm). Univariate and stepwise logistic regression analyses were used to compare subsidence based on CT bone metrics. Receiver operating characteristic (ROC) curve analyses were used to determine the probability of subsidence based on EP-HUs and vertebral HUs. RESULTS A total of 35 patients were included. Subsidence occurred at 32 of 67 unique fusion levels. Subsidence was associated with older age (p = 0.008), diabetes diagnosis (p = 0.015), and decreased interbody length (p = 0.019). EP-HUs exhibited moderate correlation with cervical vertebral HUs (Pearson’s ρ = 0.63). Subsidence was significantly associated with decreased total EP-HUs (subsidence: 475 HU, no subsidence: 543 HU; p = 0.019) and decreased lumbar vertebral HUs (subsidence: 296 HU, no subsidence: 341 HU; p = 0.011). ROC curve analysis identified an optimal EP-HU cutoff of 512.30 (area under the curve [AUC] = 0.701) to predict subsidence. The AUC of the vertebral HUs with respect to subsidence was 0.662. EP-HUs < 512.30 predicted subsidence (OR 6.67, p = 0.001) independent of significant demographic and surgical factors. CONCLUSIONS CT cervical EP-HUs rather than vertebral cervical trabecular HUs may be more efficacious in predicting subsidence after ACDF.

Study Design Retrospective cohort analysis. Objective (1) Develop a novel computed tomography (CT)-based assessment of endplate bone density (EP-HU), (2) Determine if EP-HU was a stronger predictor than trabecular HU for subsidence after transforaminal lumbar interbody fusion (TLIF). Methods All adult patients who underwent single-level TLIF for lumbar degenerative conditions at an academic center between 2017-2022 were retrospectively identified. EP-HU was calculated from a 2 mm superior and inferior endplate region on the preoperative mid sagittal CT scans, accounting for surface undulations. Lumbar vertebral HUs (trabecular region) were determined in a standard fashion on axial CT. EP-HU + vertebral HU served as an aggregate bone quality metric. Interbody subsidence (≥2 mm threshold) was directly measured on the endplate-facing surface of 1 year CT scans. Univariate and multivariate analysis compared subsidence based on CT bone metrics. Results A total of 114 patients met the inclusion/exclusion criteria. There was no significant difference in fusion or reoperation rate based on subsidence occurrence. Both vertebral HU ( P = .012) and EP-HU ( P < .001) were associated with subsidence. In receiver operating curves, EP-HU was more optimal for subsidence prediction than vertebral HU, but the aggregate metric further optimized the specificity and total area under the curve. In a predictive logistic regression model EP-HU + vertebral HU (aggregate HU < 515 odds ratio: 7.82, P < .001) was a strong independent predictor of subsidence. Conclusion Preoperative calculation of EP-HUs in addition to vertebral HUs may enhance prediction of TLIF subsidence where aggregate endplate and vertebral HU < 515 can be used to identify high risk patients.

OBJECTIVE The purpose of this study was to evaluate the risks and benefits of removing painful pelvic/iliac screws in spine fusion surgery patients. METHODS A retrospective review identified patients who had traditional iliac and S2-alar-iliac (S2AI) screws removed for pain. The minimum follow-up was 24 months. RESULTS Fifty-two patients (75% women) were included with a mean age of 63 years, BMI of 28, and follow-up of 65 months. Most of the removed screws were S2AI (83%) compared with traditional iliac screws (17%). Forty-three patients (83%) had improvement in their pelvic screw related–pain following removal. Eight patients (15%) experienced lumbosacral mechanical complications following pelvic screw removal including sacral fracture (n = 3, 6%) and/or L4–5 or L5–S1 rod fracture (n = 7, 13%). On multivariable analysis, risk factors for mechanical complications following pelvic screw removal included a longer fusion construct (OR 1.34, p = 0.035), greater postoperative L4–S1 lordosis (OR 1.14, p = 0.04, ideal cutoff > 40°), and lack of bone morphogenetic protein (BMP; OR 0.03, p = 0.02). Ten patients (19%) underwent subsequent SI joint fusion following pelvic screw removal, and higher standing pelvic incidence (OR 1.10, p = 0.03) was the only independent predictor of SI fusion. CONCLUSIONS Removal of painful pelvic screws resulted in a high rate of postoperative pain relief, albeit with a risk of lumbosacral mechanical complications and subsequent SI joint fusion. Patients at risk for lumbosacral mechanical complications following pelvic screw removal included those with longer fusion constructs, more lordosis from L4 to S1 (> 40°), and lack of BMP. Patients at risk for receiving an instrumented SI joint fusion following pelvic screw removal included those with a higher pelvic incidence.

Study Design Retrospective Cohort Study. Objectives To determine if 3D printed porous titanium (Ti) cages compared to non-porous polyetheretherketone (PEEK) cages predicted improved fusion rate or clinical outcomes after transforaminal lumbar interbody fusion (TLIF). Methods All adult patients who underwent one- and two-level TLIF for degenerative conditions by a single surgeon at an academic center between 2017-2021 were retrospectively identified. Patients were dichotomized into porous Ti and non-porous PEEK interbody cage groups. Fusion status was assessed by at 6-months and 1-year postoperatively by CT Bridwell scale and flexion/extension X-Rays. Postoperative complications (CT-based subsidence, adjacent segment disease, reoperation rates) and interval changes in lumbar radiographic alignment at short- and long-term follow-up were determined. Univariate and multivariate analysis compared patient and surgical factors, fusion rates, alignment, and complications across interbody groups. Results A total of 136 patients with 169 unique fusion levels (125 Ti cages, 44 PEEK cages) met the inclusion/exclusion criteria. Ti relative to PEEK interbodies had significantly decreased surface area and increased height and lordosis. Ti cage use was associated with greater subsidence ( P < 0.001) but did not independently predict maximum subsidence on regression ( P = 0.109). In the overall cohort, there were no significant differences in fusion rates or lumbopelvic alignment between interbody groups. Reoperation (Ti: 10.9% vs PEEK: 28.6%, P = 0.026) and reoperation for pseudoarthrosis (Ti: 2.0% vs PEEK: 11.4%, P = 0.038) was significantly more likely in the PEEK relative to the Ti group. Conclusions Use of 3D printed porous Ti cages relative to non-porous PEEK cages may mitigate pseudoarthrosis related reoperation after TLIF.

OBJECTIVE Pelvic incidence (PI) is a key parameter of sagittal alignment. While conventionally held to be fixed, increasing evidence suggests PI may be variable. This study aimed to identify predictors of change in PI with patient position and to assess the association of preoperative radiographic characteristics and intraoperative maneuvers with postoperative PI. METHODS Patients who underwent thoracolumbosacral fusion were identified, and data were gathered on preoperative spinopelvic parameters, patient demographic characteristics, and operative details. Preoperative spinopelvic parameters were measured on upright, supine, and prone radiographs. Univariable comparisons of PI between the different patient positions were performed. Multivariable analysis was performed to identify variables independently correlated with PI on 6-week postoperative radiographs. Change in PI was defined as ≥ 5° change between positions. RESULTS In total, 138 patients were identified (mean ± SD age 66.0 ± 8.7 years; 38.4% male). Statistically significant differences in PI were noted between preoperative standing and supine (mean −3.2° ± 4.2°, p < 0.001), preoperative supine and prone (3.5° ± 4.7°, p < 0.001), preoperative and 6-week postoperative standing (1.5° ± 6.2°, p = 0.01), and immediate and 6-week upright (1.1° ± 3.9°, p = 0.007) radiographs. Univariable comparisons showed PI decrease from standing to supine was predicted only by weight (87.0 ± 15.0 vs 81.1 ± 19.3 kg, p = 0.04); there were no significant predictors of increase in PI from standing to prone. Increase in PI from preoperative to 6-week standing radiographs was predicted by lower preoperative PI class (p < 0.001), L5/S1 interbody placement (74.4% vs 52.0%, p = 0.02), and change in PI from preoperative standing to supine (12.8% vs 39.8%, p = 0.002) and from standing to prone (51.3% vs 13.3%, p < 0.001). Multivariable analysis showed that 6-week postoperative PI was associated with only preoperative supine PI (B = 0.293, 95% CI 0.10–0.48, p = 0.003) and prone PI (B = 0.647, 95% CI 0.44–0.85, p < 0.001). CONCLUSIONS There are position-dependent changes in PI among patients without prior pelvic fixation. Statistically significant changes in PI are seen even after pelvic fixation with a single S2-alar-iliac screw bilaterally. Postoperative PI was best predicted by preoperative PI on supine and prone radiographs rather than upright radiographs, suggesting that preoperative prone and supine radiographs may provide surgeons with the best information for achieving PI–lumbar lordosis mismatch < 10°.

OBJECTIVE Transforaminal lumbar interbody fusion (TLIF) offers both indirect decompression and segmental correction through restoration of disc height. However, stresses exerted on the vertebral endplates by the interbody device can result in implant subsidence and loss of correction. The present time-to-event analysis aimed to identify predictors of interbody subsidence. METHODS Patients who underwent 1- or 2-level TLIF were identified. Data on demographics, surgical details, preoperative bone quality using CT-based Hounsfield units (HU), and pre- and postoperative lumbopelvic parameters were collected. Univariable analyses were conducted to identify predictors of subsidence (≥ 2-mm intrusion of interbody into cranial or caudal vertebrae) and significant subsidence (≥ 4-mm intrusion). Multivariable Cox regression was performed to identify independent predictors of subsidence, expressed as hazard ratios with 95% confidence intervals. RESULTS A total of 198 patients treated at 241 levels were included (median age 66.6 years, IQR 59.5, 73.7 years; 56.6% were women). In 92 levels (38.2%) there was some subsidence and in 25 (10.4%) there was significant subsidence. Implanted levels demonstrating subsidence (≥ 2 mm) were associated with lower HU in cranial and caudal vertebrae; had interbodies positioned farther from the anterior apophyseal ring; were implanted with taller, more lordotic interbodies; and underwent greater disc height restoration. Those showing significant subsidence (≥ 4 mm) were similarly associated with lower HU in the cranial and caudal vertebrae; had interbodies positioned farther from the anterior apophyseal ring of the caudal vertebrae; and underwent greater disc height restoration. Multivariable Cox regression showed that time to subsidence was predicted by greater implant height (HR 1.20/mm, 95% CI 1.05–1.38; p = 0.009), greater postoperative disc height (HR 1.21/mm, 95% CI 1.09–1.34; p < 0.001), and greater disc height restoration (HR 1.11/mm, 95% CI 1.04–1.19; p = 0.002). The time-to-subsidence analysis for significant (≥ 4 mm) subsidence showed that it was predicted by lower HU in the cranial vertebrae (HR 0.98/unit, 95% CI 0.97–0.99; p = 0.001); increasing number of levels instrumented (HR 1.26, 95% CI 1.04–1.52; p = 0.016); and greater disc height restoration (HR 1.33/mm, 95% CI 1.18–1.51; p < 0.001). CONCLUSIONS This time-to-event analysis suggests that interbody subsidence following TLIF is best predicted by implantation of a taller interbody and aggressive disc height restoration. Significant subsidence is similarly predicted by aggressive disc height restoration along with poor baseline bone quality. The results suggest the need to balance aggressive correction at the time of surgery against the increased risk of subsequent interbody subsidence.

Introduction: Bone health optimization is a key component of the preoperative management of spine surgery patients, as poor bone quality increases the odds of mechanical complications. The present study aimed to achieve the following: (1) compare the relative efficacy of current osteoporosis medications in improving bone quality; (2) identify factors influencing treatment response in preoperative spine surgery patients. Methods: Patients treated at a single, multisite institution who received osteoporosis treatment were identified. Data were gathered on pre- and post-treatment lumbar spine Hounsfield Unit (HU) measurements, patient demographics, frailty scores (modified Frailty Index/mFI, risk analysis index/RAI), and pharmacologic treatment details. The primary outcome was a ≥7 point improvement in lumbar HU, and baseline and logistic regression models were utilized to identify factors associated with this improvement. Medications were grouped as anabolic (teriparatide, romosozumab) and antiresorptive (denosumab, alendronate) therapies. Results: A total of 267 patients were included (median age: 74 years; IQR [66–81]; 67.3% female), with 127 (47.6%) improving by ≥7 HU. The treatment agents used were alendronate (95), denosumab (113), romosozumab (31), and teriparatide (28). Univariable comparisons revealed significant differences across medication groups in age (p < 0.001), sex (p < 0.001), mFI (p < 0.001), RAI (p = 0.004), BMI (p < 0.001), pre-treatment HU (p = 0.022), and treatment duration (p < 0.001). The highest HU improvement rates (ΔHU ≥ 7) were observed in patients receiving the anabolic medications romosozumab (67.7%) and teriparatide (60.7%). Univariable logistic regression identified male sex (OR 0.54, p = 0.019), higher pre-treatment HU (OR 0.99, p = 0.006), and longer treatment duration (OR 0.97, p = 0.003) as factors associated with lower odds of HU improvement. Only romosozumab was associated with significantly higher odds of HU improvement relative to alendronate (OR 3.02, p = 0.012). In our multivariable analysis, male sex (OR 0.53, p = 0.028) and higher pre-treatment HU (OR 0.99, p = 0.002) remained significant predictors of HU improvement. However, medication type was not significant in the multivariable analysis. Conclusions: Our study highlights that male sex and higher pre-treatment HU were independently associated with lower odds of HU improvement, while medication type was not a significant predictor. Additionally, anabolic agents offered superior improvement relative to antiresorptive therapies.