Faculty Bibliography

OBJECTIVE:Spinal meningiomas (SMs) are common primary spinal tumors for which surgery is considered the first-line treatment when safe and feasible. The ability to extrapolate the tumor grade from preoperative imaging may significantly inform early patient expectation-setting regarding recurrence. Building on radiomics studies in cranial meningiomas, the authors aimed to construct a benchmark radiomics model to preoperatively identify the histological grade of SMs. METHODS:Institutional surgical records from May 2012 to November 2025 were queried for pathology-confirmed meningiomas below the foramen magnum, with preoperative contrast-enhanced imaging available for segmentation. SMs were classified as low-grade (WHO grade 1) and high-grade (WHO grade 2 tumors and grade 1 tumors with atypia). Tumors were manually segmented, and features were extracted using the PyRadiomics software package. An ensemble model of k-nearest neighbors, random forest, and support vector machine classifiers was trained using nested cross-validation on a subset of 10 features to differentiate tumor grades. Clinical data for the cohort were also extracted, and disease control in an adjunctive clinical series was assessed. RESULTS:Seventy-four patients were included in radiomics analysis, with an area under the receiver operating characteristic curve of 0.879 and a mean F1 score of 0.748. The model's top 5 features were all texture features that differed significantly (p < 0.05) across low- and high-grade SMs. These included measures of tumor textural and contrast-enhancement heterogeneity, with overlap with features reported in radiomics models for histological grading of intracranial meningiomas. Fifty-five patients with a median radiographic follow-up of 22.2 (range 1.9-86.4) months remained for clinical analysis after exclusion of patients with less than 1 month of follow-up and syndromic meningiomas. Four recurrences occurred at a median of 20.8 (range 1.8-41.8) months. High-grade tumor pathology did not significantly impact progression-free survival (p = 0.682, log-rank test; Cox regression high vs low grade hazard ratio [HR] 0.62, 95% CI 0.06-6.11, p = 0.685). Subtotal resection was associated with poorer progression-free survival than gross-total resection (p = 0.004, log-rank test; Cox regression subtotal vs gross-total resection HR 10.62, 95% CI 1.46-77.05, p = 0.019). These findings remain contextualized within a relatively limited follow-up window and small recurrence event count, suggesting a need to characterize the interplay between tumor grade and extent of resection as drivers of local disease control in SMs. CONCLUSIONS:A preoperative radiomics model can stratify high-grade SMs using open-source tools applied to single-institution data.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Anterior lumbar interbody fusion (ALIF) is an important technique offering biomechanical advantages including improved disk height restoration, correction of sagittal and coronal imbalance, and improved fusion. Although generally safe, vascular injury remains a serious complication. Specific vascular injury mechanisms, management, and outcomes are insufficiently reported. We seek to better characterize the incidence, mechanism, management, and sequelae of intraoperative vascular injuries during ALIF. METHODS:We performed a retrospective single-center study of adult patients undergoing ALIF between 2018 and 2022. All exposures were performed by a vascular surgeon. Data analyzed included patient demographics, operative characteristics, and vascular complications (classified as major or minor). The primary outcomes were the incidence of vascular injury and postoperative venous thromboembolism (VTE). Statistical analyses included χ2 testing and logistic regression. RESULTS:Of 418 patients, 26 (6.2%) sustained intraoperative vascular injuries, with 4 (1.0%) classified as major. Injuries were predominantly venous (n = 25), most frequently involving the left common iliac vein during L4-L5 exposure. One arterial dissection required stenting. Postoperative VTE occurred in 11 patients (2.6%); notably, 45.5% of these patients had sustained an intraoperative vascular injury. Vascular injury was a strong independent predictor of VTE (odds ratio [OR]: 15.9; P < .001; 95% CI: 4.3-58.8). The number of levels fused was significantly associated with both vascular injury (OR: 1.76; P = .007; 95% CI: 1.16-2.66) and VTE (OR: 1.91; P = .031; 95% CI: 1.03-3.42). No association was found between vascular complications and previous abdominal surgery, body mass index, revision surgery, age older than 50, spinal deformity, or sex. There was 0% perioperative mortality. CONCLUSION/CONCLUSIONS:Vascular complications during ALIF are infrequent but significantly elevate the risk of postoperative VTE. Injuries cluster at the L4-L5 level and often involve the left common iliac vein. Preoperative planning, careful surgical technique, and experienced vascular access support are critical to minimizing complications.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Intradural extramedullary spinal tumors (IDEMs) are ideally managed with gross total resection (GTR) for optimal local disease control in the absence of established adjuvant regimens. In this retrospective cohort study, we investigated the utility of morphology-based analysis of optimal IDEM resection quality compared with current linear measurement benchmarks. METHODS:Tumors were manually segmented from preoperative contrast-enhanced MRI. Morphological features of sphericity, elongation, and volume were extracted from masks, along with manual anteroposterior, craniocaudal, and transverse linear measurements. Optimal resection was defined as Simpson Grade 1 or 2 for meningiomas or en bloc GTR for myxopapillary ependymomas (MPEs) and was predicted for dorsal and ventral spinal meningiomas plus conus and nonconus MPEs. RESULTS:We identified 103 tumors, including 71 meningiomas and 32 MPEs. Linear measurement did not reliably predict optimal resection across anatomic subtypes of meningiomas or MPEs (all P > .05). Instead, optimal resection was determined by higher sphericity across meningiomas and, specifically, dorsal meningiomas (optimal resection median 0.80 (IQR: 0.77-0.82) vs suboptimal 0.76 (0.72-0.77), P = .027). Shape features were not predictive in ventral meningiomas. En bloc GTR was limited to nonconus MPEs, in which sphericity again emerged as a predictor (0.74 (0.69-0.77) for en bloc vs 0.68 (0.64-0.72) for piecemeal, P = .047), likely reflecting resectability for encapsulated tumors. After excluding patients with <1 year of surveillance to determine nonrecurrence, 62 patients without genetic syndromes remained for recurrence analysis with a median follow-up of 36.1 months. Optimal resection was associated with significantly lower recurrence (optimal 8.6% vs suboptimal 29.6%, P = .045). This protective effect remained, although statistically insignificant after adjusting for adjuvant radiation and tumor grade (recurrence odds ratio = 0.22, 95% CI: 0.04-1.07, P = .077). CONCLUSION/CONCLUSIONS:IDEM tumor morphology is predictive of optimal resection for dorsal meningiomas and nonconus MPEs, whereas linear measurements offer less consistent predictive value. Morphological assessment is feasible with standard MRI and may be further automated.

BACKGROUND AND OBJECTIVES/OBJECTIVE:The objective of this study was to compare sociodemographic factors, presenting characteristics, and outcomes between cohorts of patients receiving surgery for spinal metastases at 2 neighboring institutions, 1 private and 1 public, affiliated with a single major academic medical center in a large metropolitan area. METHODS:This analysis included all patients who underwent decompressive surgery for extradural spinal metastases. Sociodemographic factors, treatment characteristics, and outcomes were compared between those treated at a private hospital and a neighboring public hospital using Rao-Scott χ 2 tests for categorical variables, Student t tests for continuous variables, and the Kaplan-Meier product-limit method for overall survival and progression-free survival. RESULTS:Compared with those treated at our private hospital, patients treated at our public hospital were more often younger ( P = .005), of Black or Hispanic race (72.6% vs 19%, P < .001), and uninsured (16% vs 5.6%, P = .005). They more frequently presented with epidural spinal cord compression grade 3 (76% vs 56.8%, P = .027), were nonambulatory before surgery (56.9% vs 13.5%, P < .001), and had increased neurological impairment as denoted by American Spinal Injury Association Impairment Scale grades of A, B, or C (39.2% vs 7.5%). Patients treated at our public hospital had shorter median follow-up time (92 vs 302.5 days, P = .004). Multivariate analysis did not reveal a significant difference in overall survival or progression-free survival between hospitals, instead demonstrating associations with primary tumor histology and number of spinal metastases ( P < .05). CONCLUSION/CONCLUSIONS:There were substantial disparities in sociodemographic factors, presenting local disease burden, and postoperative neurological outcome but no difference in survival outcome, between patients treated at our public and private hospitals. These findings underscore the need for more equitable screening, surveillance, and referral structures.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Myxopapillary ependymomas (MPE) and intradural lumbosacral schwannomas may be challenging to distinguish based on presenting characteristics and preoperative imaging. Accurate differentiation is crucial, as MPEs carry a risk of cerebrospinal fluid dissemination and warrant earlier intervention, a more tailored surgical strategy, consideration for adjuvant radiation, and frequent surveillance. Here, we describe our institutional experience with these tumors and develop a radiomics-based machine learning model to help distinguish them on preoperative imaging. METHODS:Institutional surgical records from 2011 to 2025 were queried and clinical data were extracted for the retrospective cohort analysis. Tumors were manually segmented in ITK-Snap from T1 postcontrast images, and radiomics features were extracted using the PyRadiomics package. An ensemble of random forest, k-nearest neighbors, and naive Bayes classifiers was trained on a subset of radiomics features using nested cross-validation. RESULTS:< .001) in MPEs, likely due to longitudinal tumor growth along the filum. Excluding scoliotic patients did not significantly alter discrimination, suggesting robustness to vertebral column malalignment that may coexist with intradural tumors. CONCLUSION/CONCLUSIONS:A radiomics-based machine learning model demonstrated excellent discriminative ability between MPE and lumbosacral schwannoma, achieving high accuracy and robustness to vertebral alignment variations. These results suggest that radiomics-based models may be developed into a useful tool for preoperative planning and patient counseling.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Intramedullary spinal cord tumor (IMSCT) resection carries a high risk of postoperative neurological deficit because of neural tract manipulation and myelotomy. Although short-term and long-term neurological recovery represent key treatment outcomes, current prognostication methods are lacking and would benefit from further complex analysis. METHODS:From March 2009 to August 2025, all adult IMSCT resections at our institution were reviewed. Demographic, oncologic, and perioperative data were extracted from electronic medical records. This included preoperative and follow-up neurological examination data in the form of American Spinal Injury Association Impairment Scale (AIS) grading, Modified McCormick Scale (MMCS), and ambulatory status. Independent ambulation served as the primary outcome for 4 machine learning models. Each model was sequentially evaluated using area under the receiver operating characteristic curve (AUROC). RESULTS:Fifty-four patients underwent 55 surgeries for IMSCT resection. Encapsulated lesions predominated IMSCT pathology, with grade II ependymoma comprising 28 (50.9%) resections, 5 hemangioblastomas (9.1%), and 5 cavernous hemangiomas (9.1%). Gross total resection was achieved in 36 cases (65.5%), with encapsulated tumors more readily achieving gross total resection vs unencapsulated (84.6% vs 18.8%, P < .01). By 4 weeks, conversion of MMCS, but not AIS grade, significantly correlated with concurrent ambulatory conversion (P < .01 vs P = .15). At 6 months, both AIS grade conversion (P < .01) and MMCS conversion (P < .01) significantly correlated with ambulatory conversion. For predicting ambulation at latest follow-up from 4 weeks postoperatively, the comprehensive granular model achieved an AUROC of 0.833, outperforming the AIS grade (0.583), American Spinal Injury Association Motor Score (0.667), and MMCS (0.667) models. By the 6-month follow-up, the comprehensive granular model achieved strong discrimination (AUROC 1.00). CONCLUSION/CONCLUSIONS:Follow-up IMSCT data demonstrate a postoperative lability that stabilizes by 6 months into a reliably modeled outcome. By enhancing the granularity of recovery data, accurate independent ambulation modeling may improve counseling for patients with IMSCT.

OBJECTIVE:Salvaged red blood cells (sRBCs) are frequently used in spine surgery, despite concerns about their quality and efficacy as a blood substitute. This study aimed to evaluate the association of sRBC transfusion with postoperative complications in spinal deformity surgery. METHODS:This single-center, prospective, nonrandomized controlled trial included patients undergoing posterior-based multilevel thoracolumbar instrumented fusion for spinal deformity from June 2022 to July 2023. Participants were grouped based on whether they received an sRBC transfusion. Postoperative complications were analyzed using frequentist methods, with and without propensity score matching (PSM), and a series of five Bayesian models of varying complexity that included hierarchical structures and covariates. Model comparison followed by weighted model averaging based on predictive performance was performed to integrate the results from the different models into a composite model. RESULTS:After PSM (specifically matching surgical invasiveness and blood loss), sRBC transfusion was associated with increased odds of infection (OR 3.77, 95% CI 0.99-14.33; p = 0.046), acute kidney injury (OR 3.36, 95% CI 1.37-8.22; p = 0.007), liver injury (OR 3.52, 95% CI 1.64-7.54; p < 0.001), pulmonary complications (OR 2.26, 95% CI 1.13-4.53; p = 0.025), and thrombocytopenia (OR 9.02, 95% CI 2.54-32.0; p < 0.001). The composite Bayesian model yielded consistent results, with additional associations noted for cardiac events (OR 2.18, 95% highest density interval [HDI] 1.36-3.03) and coagulopathy (OR 3.13, 95% HDI 1.85-4.50). In contrast, allogeneic RBC transfusion was only associated with infection (OR 1.65, 95% HDI 1.04-2.59) and pulmonary complications (OR 1.73, 95% HDI 1.08-2.89). CONCLUSIONS:Salvaged RBC transfusion in complex spine surgery was found to be independently associated with increased risks of various complications. These findings reinforce concerns about the safety of sRBC transfusion, suggesting a need for caution in their use in this setting.

Tethered postoperative drains are not uncommon complications that often require open removal in the operating room, which can increase risks of surgical site infection as well as length of hospitalization. We present a novel method of tethered drain removal through guidewire electrification. A retained deep drain following a posterior cervical laminectomy and fusion was identified after failed manual removal. Under fluoroscopic guidance, the retaining suture was indirectly identified through the obstruction of an inserted guidewire, through which monopolar cautery was applied, breaking the suture and allowing drain removal. The original incision did not need to be re-opened. While further investigation is necessary for validation, this technique shows great promise as an alternative to open removal.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Scholarly output is accelerating in medical domains, making it challenging to keep up with the latest neurosurgical literature. The emergence of large language models (LLMs) has facilitated rapid, high-quality text summarization. However, LLMs cannot autonomously conduct literature reviews and are prone to hallucinating source material. We devised a novel strategy that combines Reference Publication Year Spectroscopy-a bibliometric technique for identifying foundational articles within a corpus-with LLMs to automatically summarize and cite salient details from articles. We demonstrate our approach for four common spinal conditions in a proof of concept. METHODS:Reference Publication Year Spectroscopy identified seminal articles from the corpora of literature for cervical myelopathy, lumbar radiculopathy, lumbar stenosis, and adjacent segment disease. The article text was split into 1024-token chunks. Queries from three knowledge domains (surgical management, pathophysiology, and natural history) were constructed. The most relevant article chunks for each query were retrieved from a vector database using chain-of-thought prompting. LLMs automatically summarized the literature into a comprehensive narrative with fully referenced facts and statistics. Information was verified through manual review, and spine surgery faculty were surveyed for qualitative feedback. RESULTS:Our tandem approach cost less than $1 for each condition and ran within 5 minutes. Generative Pre-trained Transformer-4 was the best-performing model, with a near-perfect 97.5% citation accuracy. Surveys of spine faculty helped refine the prompting scheme to improve the cohesion and accessibility summaries. The final artificial intelligence-generated text provided high-fidelity summaries of each pathology's most clinically relevant information. CONCLUSION/CONCLUSIONS:We demonstrate the rapid, automated summarization of seminal articles for four common spinal pathologies, with a generalizable workflow implemented using consumer-grade hardware. Our tandem strategy fuses bibliometrics and artificial intelligence to bridge the gap toward fully automated knowledge distillation, obviating the need for manual literature review and article selection.

BACKGROUND AND OBJECTIVE/OBJECTIVE:Neurofibromatosis-1 (NF1) dystrophic scoliosis is a challenging disease to manage surgically, with multiplanar curves progressing rapidly and unpredictably. Conservative management with bracing is often unsuccessful, and many patients necessitate instrumented fusion to halt progression of their curves. In rare cases, patients can present with spontaneous vertebral subluxation, significantly complicating the surgical management of this already complex disease process. The objective here was to describe 2 cases of vertebral subluxation in NF1-associated dystrophic scoliosis along with their surgical corrections and clinical courses. METHODS:A retrospective review of 2 cases at the authors' institution was performed to describe their preoperative symptom complexes, surgical corrections, and postoperative courses. A narrative review of the literature surrounding NF1-associated dystrophic scoliosis and subluxation is also presented. RESULTS:Two cases of vertebral subluxation at T4-5 and C7-T1 are presented. Both patients had significant dystrophic features throughout their spines, and halo-gravity traction was unsuccessful in 1 patient and led to vertebral and subclavian artery injuries in the other. One patient underwent an uncomplicated deformity correction with partial vertebral column resection to facilitate his deformity correction. The other patient, after her vascular injuries, ultimately suffered a spinal cord injury after a fall and underwent emergent instrumentation, decompression, and partial vertebral column resection at the site of subluxation, with improvement in her neurological function afterward. CONCLUSION/CONCLUSIONS:Dystrophic scoliosis in NF1 remains a difficult disease to treat, and deformity correction in patients with subluxation is particularly complex. These cases here highlight the unpredictability and possible complications of halo-gravity traction, need for good fixation to facilitate subluxation reduction, high chance of hardware complications and proximal or distal failure, and importance of cooperative management of these patients in conjunction with other surgical services.