90-Day Emergency Department Utilization and Readmission Rate After Full-Endoscopic Spine Surgery: A Multicenter, Retrospective Analysis of 821 Patients.

BACKGROUND AND OBJECTIVES: Emergency department (ED) utilization and readmission rates after spine surgery are common quality of care measures. Limited data exist on the evaluation of quality indicators after full-endoscopic spine surgery (FESS). The objective of this study was to detect rates, causes, and risk factors for unplanned postoperative clinic utilization after FESS. METHODS: This retrospective multicenter analysis assessed ED utilization and clinic readmission rates after FESS performed between 01/2014 and 04/2023 for degenerative spinal pathologies. Outcome measures were ED utilizations, hospital readmissions, and revision surgeries within 90 days postsurgery. RESULTS: Our cohort includes 821 patients averaging 59 years of age, who underwent FESS. Most procedures targeted the lumbar or sacral spine (85.75%) while a small fraction involved the cervical spine (10.11%). The most common procedures were lumbar unilateral laminotomies for bilateral decompression (40.56%) and lumbar transforaminal discectomies (25.58%). Within 90 days postsurgery, 8.0% of patients revisited the ED for surgical complications. A total of 2.2% of patients were readmitted to a hospital of which 1.9% required revision surgery. Primary reasons for ED visits and clinic readmissions were postoperative pain exacerbation, transient neurogenic bladder dysfunction, and recurrent disk herniations. Our multivariate regression analysis revealed that female patients had a significantly higher likelihood of using the ED (P = .046; odds ratio: 1.77, 95% CI 1.01-3.1 5.69% vs 10.33%). Factors such as age, American Society of Anesthesiologists class, body mass index, comorbidities, and spanned spinal levels did not significantly predict postoperative ED utilization. CONCLUSION: This analysis demonstrates the safety of FESS, as evidenced by acceptable rates of ED utilization, clinic readmission, and revision surgery. Future studies are needed to further elucidate the safety profile of FESS in comparison with traditional spinal procedures.

Computed tomography assessment of robotic versus fluoroscopic implant accuracy in sacroiliac joint fusion.

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.

Development and validation of an artificial intelligence model to accurately predict spinopelvic parameters.

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.

Virtual Reality-Enabled Resident Education of Lateral-Access Spine Surgery.

OBJECTIVE: Lateral-access spine surgery has many benefits, but adoption has been limited by a steep learning curve. Virtual reality (VR) is gaining popularity and lends itself as a useful tool in enhancing neurosurgical resident education. We thus sought to assess whether VR-based simulation could enhance the training of neurosurgery residents in lateral spine surgery. METHODS: Neurosurgery residents completed a VR-based lateral spine module on lateral patient positioning and performing lateral lumbar interbody fusion using the PrecisionOS VR system on the Meta Quest 2 headset. Simulation occurred 1×/week every other week for a total of 3 simulations over 6 weeks. Pre- and postintervention surveys as well as intrasimulation performance metrics were assessed over time. RESULTS: The majority of resident participants showed improvement in performance scores, including an automated PrecisionOS precision score, number of radiographs used within the simulation, and time to completion. All participants showed improvement in comfort with anatomic landmarks for lateral access surgery, confidence performing lateral surgery without direct supervision, and assessing fluoroscopy in spine surgery for hardware placement and image interpretation. Participant perception on the utility of VR as an educational tool also improved. CONCLUSIONS: VR-based simulation enhanced neurosurgical residents' ability to understand lateral access surgery. Immersive surgical simulation resulted in improved resident confidence with surgical technique and workflow, perceived improvement in anatomical knowledge, and simulation performance scores. Trainee perceptions on virtual simulation and training as a curriculum supplement also improved following completion of VR training.

Patients with progression of spinal metastases who present to the clinic have better outcomes compared to those who present to the emergency department.

BACKGROUND: As cancer therapies have improved, spinal metastases are increasingly common. Resulting complications have a significant impact on patient's quality of life. Optimal methods of surveillance and avoidance of neurologic deficits are understudied. This study compares the clinical course of patients who initially presented to the emergency department (ED) versus a multidisciplinary spine oncology clinic and who underwent stereotactic body radiation therapy (SBRT) secondary to progression/presentation of metastatic spine disease. METHODS: We performed a retrospective analysis of a prospectively maintained database of adult oncologic patients who underwent spinal SBRT at a single hospital from 2010 to 2021. Descriptive statistics and survival analyses were performed. RESULTS: We identified 498 spinal radiographic treatment sites in 390 patients. Of these patients, 118 (30.3%) presented to the ED. Patients presenting to the ED compared to the clinic had significantly more severe spinal compression (52.5% vs. 11.7%; p < 0.0001), severe pain (28.8% vs. 10.3%; p < 0.0001), weakness (24.5% vs. 4.5%; p < 0.0001), and difficulty walking (24.5% vs. 4.5%; p < 0.0001). Patients who presented to the ED compared to the clinic were significantly more likely to have surgical intervention followed by SBRT (55.4% vs. 15.3%; p < 0.0001) compared to SBRT alone. Patients who presented to the ED compared to the clinic had a significantly quicker interval to distant spine progression (5.1 ± 6.5 vs. 9.1 ± 10.2 months; p = 0.004), systemic progression (5.1 ± 7.2 vs. 9.2 ± 10.7 months; p < 0.0001), and worse overall survival (9.3 ± 10.0 vs. 14.3 ± 13.7 months; p = 0.002). CONCLUSION: The establishment of multidisciplinary spine oncology clinics is an opportunity to potentially allow for earlier, more data-driven treatment of their spinal metastatic disease.

Robotic versus nonrobotic sacroiliac joint fusion.

OBJECTIVE: Robot-assisted pedicle screw placement in spinal fusion has been well studied. However, few studies have evaluated robot-assisted sacroiliac joint (SIJ) fusion. The aim of this study was to compare surgical characteristics, accuracy, and complications between robot-assisted and fluoroscopically guided SIJ fusion. METHODS: A retrospective review of 110 patients with 121 SIJ fusions done at a single academic institution was conducted from 2014 to 2023. Inclusion criteria included adult age and a robot- or fluoroscopically guided approach to SIJ fusion. Patients were excluded if the SIJ fusion was part of a longer fusion construct, not minimally invasive, and/or had missing data. Demographics, approach type (robotic vs fluoroscopic), operative time, estimated blood loss (EBL), number of screws, intraoperative complications, 30-day complications, number of intraoperative fluoroscopic images (as a surrogate for radiation exposure), implant placement accuracy, and pain status at the first follow-up were recorded. Primary endpoints were SIJ screw placement accuracy and complications. Secondary endpoints were operative time, radiation exposure, and pain status at the first follow-up. RESULTS: Ninety patients were included who underwent a total of 101 SIJ fusions, of which 78 were robotic and 23 were fluoroscopic. The mean age of the cohort at the time of surgery was 55.9 ± 13.8 years; 46 patients were females (51.1%). No difference was found in screw placement accuracy between robotic and fluoroscopic fusion (1.3% vs 8.7%, p = 0.06). Chi-square analysis of robotic versus fluoroscopic fusion found no difference in the presence of 30-day complications (p = 0.62). Mann-Whitney U-test analysis found that robotic fusion had a significantly longer operative time than fluoroscopic fusion (72.0 vs 61.0 minutes, p = 0.01); however, robot-assisted fusions involved significantly lower radiation exposure (26.7 vs 187.4 fluoroscopic images, p < 0.001). No difference in EBL was noted (p = 0.17). No intraoperative complications were present in this cohort. Subgroup analysis comparing the 23 most recent robotic cases against the 23 fluoroscopic cases found that robotic fusion still was associated with significantly longer operative times than fluoroscopic fusion (74.0 ± 26.4 vs 61.0 ± 14.9 minutes, respectively; p = 0.047). CONCLUSIONS: SIJ screw placement accuracy did not significantly differ between robot-assisted and fluoroscopic SIJ fusion. Complications overall were low and similar between the two groups. The operative time was longer with robotic assistance, but there was markedly less radiation exposure to the surgeon and staff.

Local Control in Patients with Metastatic Renal Cell Carcinoma to the Spine: The Experience of an Institution with a Multidisciplinary Spine Oncology Program.

BACKGROUND: The outcomes for patients with metastatic renal cell carcinoma (RCC) to the spine who underwent stereotactic body radiotherapy (SBRT) through a multidisciplinary spine oncology program are not well described. We sought to describe the clinical course and local control rates at 1 and 2 years for these patients. METHODS: A retrospective analysis of a prospectively maintained database of adult oncologic patients receiving SBRT to the spine through a multidisciplinary spine oncology program at a single institution from 2010 to 2021 was performed. Patients with a pathologic diagnosis of RCC were included. RESULTS: A total of 75 spinal sites were treated in 60 patients. Of the 60 patients, 75.0% were men, and the mean patient age was 59.2 ± 11.3 years. At 1 year after treatment, 6 of the 60 patients were lost to follow-up. Of the remaining 54 patients, 18 were censored by death and 7 treatment sites showed local recurrence, for 37 of 44 treatment sites with local control (87.8%). At 2 years, 1 additional local recurrence had developed, 15 patients were censored by death, and no additional patients had been lost to follow-up, resulting in 28 of 36 treatment sites with local control (83.2%). None of the patients who had undergone repeat SBRT had local recurrence at 1 or 2 years. For those with local recurrence, the average time from treatment to progression was 6.6 ± 6.5 months. CONCLUSIONS: In this cohort, one of the largest reported studies of spine SBRT for metastatic RCC, local control was high at 1 and 2 years. Our findings support the role of coordinated, algorithmic treatment for these patients.

Single-cell RNA sequencing and spatial transcriptomics reveal cancer-associated fibroblasts in glioblastoma with protumoral effects.

Cancer-associated fibroblasts (CAFs) were presumed absent in glioblastoma given the lack of brain fibroblasts. Serial trypsinization of glioblastoma specimens yielded cells with CAF morphology and single-cell transcriptomic profiles based on their lack of copy number variations (CNVs) and elevated individual cell CAF probability scores derived from the expression of 9 CAF markers and absence of 5 markers from non-CAF stromal cells sharing features with CAFs. Cells without CNVs and with high CAF probability scores were identified in single-cell RNA-Seq of 12 patient glioblastomas. Pseudotime reconstruction revealed that immature CAFs evolved into subtypes, with mature CAFs expressing actin alpha 2, smooth muscle (ACTA2). Spatial transcriptomics from 16 patient glioblastomas confirmed CAF proximity to mesenchymal glioblastoma stem cells (GSCs), endothelial cells, and M2 macrophages. CAFs were chemotactically attracted to GSCs, and CAFs enriched GSCs. We created a resource of inferred crosstalk by mapping expression of receptors to their cognate ligands, identifying PDGF and TGF-ß as mediators of GSC effects on CAFs and osteopontin and HGF as mediators of CAF-induced GSC enrichment. CAFs induced M2 macrophage polarization by producing the extra domain A (EDA) fibronectin variant that binds macrophage TLR4. Supplementing GSC-derived xenografts with CAFs enhanced in vivo tumor growth. These findings are among the first to identify glioblastoma CAFs and their GSC interactions, making them an intriguing target.

How closely are outcome questionnaires correlated to patient satisfaction after cervical spine surgery for myelopathy?

OBJECTIVE: Patient-reported outcomes (PROs) have become the standard means to measure surgical outcomes. Insurers and policy makers are also increasingly utilizing PROs to assess the value of care and measure different aspects of a patient's condition. For cervical myelopathy, it is currently unclear which outcome measure best reflects patient satisfaction. In this investigation, the authors evaluated patients treated for cervical myelopathy to determine which outcome questionnaires best correlate with patient satisfaction. METHODS: The Quality Outcomes Database (QOD), a prospectively collected multi-institutional database, was used to retrospectively analyze patients undergoing surgery for cervical myelopathy. The North American Spine Society (NASS) satisfaction index, Neck Disability Index (NDI), numeric rating scales for neck pain (NP-NRS) and arm pain (AP-NRS), EQ-5D, and modified Japanese Orthopaedic Association (mJOA) scale were evaluated. RESULTS: The analysis included 1141 patients diagnosed with myelopathy, of whom 1099 had an NASS satisfaction index recorded at any of the follow-up time points. Concomitant radiculopathy was an indication for surgery in 368 (33.5%) patients, and severe neck pain (NP-NRS ≥ 7) was present in 471 (42.8%) patients. At the 3-month follow-up, NASS patient satisfaction index scores were positively correlated with scores for the NP-NRS (r = 0.30), AP-NRS (r = 0.32), and NDI (r = 0.36) and negatively correlated with EQ-5D (r = -0.38) and mJOA (r = -0.29) scores (all p < 0.001). At the 12-month follow-up, scores for the NASS index were positively correlated with scores for the NP-NRS (r = 0.44), AP-NRS (r = 0.38), and NDI (r = 0.46) and negatively correlated with scores for the EQ-5D (r = -0.40) and mJOA (r = -0.36) (all p < 0.001). At the 24-month follow-up, NASS index scores were positively correlated with NP-NRS (r = 0.49), AP-NRS (r = 0.36), and NDI (r = 0.49) scores and negatively correlated with EQ-5D (r = -0.44) and mJOA (r = -0.38) scores (all p < 0.001). CONCLUSIONS: Neck pain was highly prevalent in patients with myelopathy. Notably, improvement in neck pain-associated disability rather than improvement in myelopathy was the most prominent PRO factor for patients. This finding may reflect greater patient concern for active pain symptoms than for neurological symptoms caused by myelopathy. As commercial payers begin to examine novel remuneration strategies for surgical interventions, thoughtful analysis of PRO measurements will have increasing relevance.

Correlation between tumor volume and serum prolactin and its effect on surgical outcomes in a cohort of 219 prolactinoma patients.

OBJECTIVE: Prolactinoma is the most common pituitary adenoma and can be managed medically or surgically. The authors assessed the correlation between tumor volume and prolactin level and its effect on surgical outcomes. METHODS: The authors reviewed 219 patients who underwent transsphenoidal prolactinoma resection at a single institution from 2012 to 2019. Outcomes were compared between patients with and without biochemical remission. Tumor volumes were quantified with BrainLab Smartbrush. Correlation analysis and linear regression were used to examine the association between tumor volume and serum prolactin level. Volume-adjusted prolactin level was defined as serum prolactin level divided by tumor volume. The authors utilized receiver operating characteristic (ROC) curve analysis to determine the thresholds for predicting biochemical remission status. RESULTS: The mean tumor volume was 5.66 cm3, and the mean preoperative prolactin level was 752.3 µg/L. Men had larger prolactinomas than women (mean volume 11.32 vs 2.54 cm3; p < 0.001), and women had a greater volume-adjusted prolactin level (mean 412.5 vs 175.9 µg/L/cm3, p < 0.001). In total, 66.7% of surgical patients achieved biochemical remission 6 weeks after surgery, whereas a similar cohort of medically treated patients during the same time frame demonstrated a 69.4% remission rate. Pearson correlation and linear regression analysis revealed a strong association between preoperative tumor volume and prolactin levels, with an increase in serum prolactin level of 101.31 µg/L per 1-cm3 increase in tumor volume (p < 0.001). This held true for men (R = 0.601, p < 0.001) and women (R = 0.935, p < 0.001), with women demonstrating a greater increase in prolactin level per 1-cm3 increase in volume (185.70 vs 79.77 µg/L, p < 0.001). Patients who achieved remission exhibited a 66.08-µg/L increase in preoperative prolactin level per 1 cm3 of preoperative tumor volume (p < 0.001), which was less than the 111.46-µg/L increase per 1 cm3 in patients without remission (p < 0.001). Patients who failed to achieve remission had residual tumors with a 77.77-µg/L increase in prolactin per 1 cm3 of remaining tumor volume after resection (p < 0.001). ROC curve analysis revealed significant thresholds that optimally predicted lack of postoperative remission on the basis of preoperative prolactin and tumor volume. These thresholds were rendered nonsignificant in patients with documented Knosp grade ≥ 3. CONCLUSIONS: Although the authors found a correlation between prolactinoma volume and serum prolactin level, patients without remission had a greater increase in serum prolactin level per increase in preoperative tumor volume than those who achieved remission, suggesting unique tumor composition. The authors also identified prolactin and tumor volume thresholds that optimally predicted biochemical remission status. The authors hope that their results can be used to identify prolactinomas for which surgery could achieve remission as an alternative to medical management.

Navigated retrodiaphragmatic/retroperitoneal approach for the treatment of symptomatic kyphoscoliosis: an operative video.

Retropleural, retrodiaphragmatic, and retroperitoneal approaches are utilized to access difficult thoracolumbar junction (T10-L2) pathology. The authors present a 58-year-old man with chronic low-back pain who failed years of conservative therapy. Preoperative radiographs demonstrated significant levoconvex scoliosis with coronal and sagittal imbalance. He underwent a retrodiaphragmatic/retroperitoneal approach for T12-L1, L1-2, L2-3, and L3-4 interbody release and fusion in conjunction with second-stage facet osteotomies, L4-5 TLIF, and T10-iliac posterior instrumented fusion. This video focuses on the retrodiaphragmatic approach assisted by 3D navigation. The video can be found here: https://stream.cadmore.media/r10.3171/2022.3.FOCVID2215.

High tumor amplification burden is associated with TP53 mutations in the pan-cancer setting.

Next-generation sequencing data is fundamentally changing the clinical management of patients with cancer. The most frequent genomic alterations in malignancy are mutations and amplifications, with a subset of tumors having multiple amplifications - "amplificators". We sought to understand the molecular correlates of high tumor amplification burden in a pan-cancer context. Using both national registries and a single-institution dataset, our results demonstrate that cancers with TP53 mutations (as compared to those with wild-type TP53) exhibited significantly higher tumor amplification burden across all datasets. Amplifications, generally associated with overexpression, may be potentially actionable secondary consequences of TP53 mutations.

Cardiac Complications After 3-Column Osteotomy for Adult Spinal Deformity Patients With Formal Cardiac Clearance: Identifying Key Risk Factors and Threshold Cutoffs Via Recursive Partitioning Analysis.

BACKGROUND: Despite formal cardiac clearance, a subset of 3-column osteotomy (3CO) patients still experience cardiac complications (CCs). OBJECTIVE: To define the incidence and risk factors for CC in 3CO patients who had formal cardiac clearance and assess the utility of the Revised Cardiac Risk Index (RCRI) and preoperative metabolic equivalent (MET) functional ability in predicting perioperative CC. METHODS: Patients with adult spinal deformity (ASD) who underwent 3CO deformity correction from 2006 to 2019 were retrospectively reviewed. Multivariate and recursive partitioning analyses were performed to assess risk factors. RESULTS: A total of 390 patients with ASD were included. The mean age was 64.6 years, and 60.3% were female. The CC rate was 9.7%. Patients with CCs were older ( P < .001), had an increased history of heart disease ( P = .001), and higher blood loss ( P = .045). RCRI score ( P = .646) or MET functional ability ( P = .493) were not associated with CC. On multivariate analysis, age ( P < .001), blood loss ( P = .008), and prior spinal fusion ( P = .025) were independent risk factors for CC. Patients age older than 81 years had a significantly higher CC rate than those younger than 81 years. In patients age 81 years and younger, if blood loss was >3900 mL, CC rate was significantly higher. Among patients age 81 years and younger and with >3900 mL blood loss, CC rate is significantly higher in patients with ejection fraction (EF) ≤54.5%. CONCLUSION: RCRI and MET functional ability are limited risk assessment tools in ASD 3CO patients with formal cardiac clearance. Patients older than 81 years are at high risk for CC. In younger patients, cardiac EF and blood loss are significant components to risk stratify for CC.

Rapid Automated Analysis of Skull Base Tumor Specimens Using Intraoperative Optical Imaging and Artificial Intelligence.

BACKGROUND: Accurate specimen analysis of skull base tumors is essential for providing personalized surgical treatment strategies. Intraoperative specimen interpretation can be challenging because of the wide range of skull base pathologies and lack of intraoperative pathology resources. OBJECTIVE: To develop an independent and parallel intraoperative workflow that can provide rapid and accurate skull base tumor specimen analysis using label-free optical imaging and artificial intelligence. METHODS: We used a fiber laser-based, label-free, nonconsumptive, high-resolution microscopy method (<60 seconds per 1 × 1 mm2), called stimulated Raman histology (SRH), to image a consecutive, multicenter cohort of patients with skull base tumor. SRH images were then used to train a convolutional neural network model using 3 representation learning strategies: cross-entropy, self-supervised contrastive learning, and supervised contrastive learning. Our trained convolutional neural network models were tested on a held-out, multicenter SRH data set. RESULTS: SRH was able to image the diagnostic features of both benign and malignant skull base tumors. Of the 3 representation learning strategies, supervised contrastive learning most effectively learned the distinctive and diagnostic SRH image features for each of the skull base tumor types. In our multicenter testing set, cross-entropy achieved an overall diagnostic accuracy of 91.5%, self-supervised contrastive learning 83.9%, and supervised contrastive learning 96.6%. Our trained model was able to segment tumor-normal margins and detect regions of microscopic tumor infiltration in meningioma SRH images. CONCLUSION: SRH with trained artificial intelligence models can provide rapid and accurate intraoperative analysis of skull base tumor specimens to inform surgical decision-making.

Machine Learning Applications of Surgical Imaging for the Diagnosis and Treatment of Spine Disorders: Current State of the Art.

Recent developments in machine learning (ML) methods demonstrate unparalleled potential for application in the spine. The ability for ML to provide diagnostic faculty, produce novel insights from existing capabilities, and augment or accelerate elements of surgical planning and decision making at levels equivalent or superior to humans will tremendously benefit spine surgeons and patients alike. In this review, we aim to provide a clinically relevant outline of ML-based technology in the contexts of spinal deformity, degeneration, and trauma, as well as an overview of commercial-level and precommercial-level surgical assist systems and decisional support tools. Furthermore, we briefly discuss potential applications of generative networks before highlighting some of the limitations of ML applications. We conclude that ML in spine imaging represents a significant addition to the neurosurgeon's armamentarium-it has the capacity to directly address and manifest clinical needs and improve diagnostic and procedural quality and safety-but is yet subject to challenges that must be addressed before widespread implementation.

Incidence and Risk Factors of Mechanical Complications After Posterior-Based Osteotomies for Correction of Moderate to Severe Adult Cervical Deformity: 1-Year and 2-Year Follow-up.

BACKGROUND: Rigid cervical deformity (CD) requires multilevel and/or high-grade osteotomies and long-construct fusions to achieve adequate correction. The incidence of mechanical complications (MCs) remains incompletely studied. OBJECTIVE: To define the incidence and risk factors for MC. METHODS: A retrospective review of consecutive patients with CD who underwent correction from 2010 to 2018 was performed. Inclusion criteria were cervical kyphosis >20° and/or cervical sagittal vertical axis (cSVA) >4 cm. MCs (junctional kyphosis/failure, pseudarthrosis, and implant failure) and reoperation at 1 and 2 yr were examined. RESULTS: Eighty-three patients were included. The mean age was 63.4 yr, and 61.0% were female. Fifty-three percent underwent 3-column osteotomies. After surgery, cervical parameters were significantly improved: cSVA (6.2 vs 3.8 cm, P < .001), cervical lordosis (6.3 vs -8.3°, P < .001), cervical scoliosis (CS) (6.5 vs 2.2°, P < .001), and T1 slope (41.7 vs 36.3°, P = .007). The MC rate was 28.9%: junctional (18.1%), implant (16.9%), and pseudarthrosis (10.8%). MC rates at 1 and 2 yr were 14.5% and 25.5%, respectively: junctional (9.6% and 17.6%), implant (9.6% and 17.6%), and pseudarthrosis (2.4% and 7.8%). The overall reoperation rate was 24.1%: 14.5% at 1 yr and 19.6% at 2 yr. Body mass index (BMI) (P = .015) and preoperative CS (P = .040) were independently associated with higher odds of MC. Receiver operating characteristic curves defined CS >5° to be the threshold of risk for MCs and reoperation. CONCLUSION: Correction of CD is effective by posterior-based osteotomes, but MCs are relatively high at 1 and 2 yr. BMI >30 and preoperative CS >5° predispose patients for MC and reoperation.

Identifying risk factors for postoperative diabetes insipidus in more than 2500 patients undergoing transsphenoidal surgery: a single-institution experience.

OBJECTIVE: Diabetes insipidus (DI) following transsphenoidal surgery can adversely impact quality of life and be difficult to manage. This study sought to characterize pre- and perioperative risk factors that may predispose patients to DI after pituitary surgery. METHODS: A retrospective review of patients treated at a single institution from 2007 to 2019 was conducted. DI was defined as postoperative sodium > 145 mEq/L and urine output > 300 ml/hr and/or postoperative desmopressin (ddAVP) use. DI was further characterized as transient or permanent. Uni- and multivariate analyses were performed to determine variables associated with postoperative DI. RESULTS: The authors identified 2529 patients who underwent transsphenoidal surgery at their institution. Overall, DI was observed in 270 (10.7%) of the 2529 patients, with 114 (4.5%) having permanent DI and 156 (6.2%) with transient symptoms. By pathology type, DI occurred in 31 (46.3%) of 67 craniopharyngiomas, 10 (14.3%) of 70 apoplexies, 46 (14.3%) of 322 Rathke's cleft cysts, 77 (7.7%) of 1004 nonfunctioning pituitary adenomas (NFPAs), and 62 (7.6%) of 811 functioning pituitary adenomas (FPAs). Final lesion pathology significantly affected DI rates (p < 0.001). Multivariate analysis across pathologies showed that younger age (odds ratio [OR] 0.97, p < 0.001), intraoperative CSF encounter (OR 2.74, p < 0.001), craniopharyngioma diagnosis (OR 8.22, p = 0.007), and postoperative hyponatremia (OR 1.50, p = 0.049) increased the risk of DI. Because surgery for each pathology created specific risk factors for DI, the analysis was then limited to the 1815 pituitary adenomas (PAs) in the series, comprising 1004 NFPAs and 811 FPAs. For PAs, younger age (PA: OR 0.97, p < 0.001; NFPA: OR 0.97, p < 0.001; FPA: OR 0.97, p = 0.028) and intraoperative CSF encounter (PA: OR 2.99, p < 0.001; NFPA: OR 2.93, p < 0.001; FPA: OR 3.06, p < 0.001) increased DI rates in multivariate analysis. Among all PAs, patients with DI experienced peak sodium levels later than those without DI (postoperative day 11 vs 2). Increasing tumor diameter increased the risk of DI in FPAs (OR 1.52, p = 0.008), but not in NFPAs (p = 0.564). CONCLUSIONS: In more than 2500 patients treated at a single institution, intraoperative CSF encounter, craniopharyngioma diagnosis, and young age all increased the risk of postoperative DI. Patients with postoperative hyponatremia exhibited higher rates of DI, suggesting possible bi- or triphasic patterns to DI. Greater vigilance should be maintained in patients meeting these criteria following transsphenoidal surgery to ensure early recognition and treatment of DI.

Socioeconomic predictors of case presentations and outcomes in 225 nonfunctional pituitary adenoma resections.

OBJECTIVE: Clinical presentations and outcomes of nonfunctional pituitary adenoma (NFPA) resections can vary widely, and very little prior research has analyzed this variance through a socioeconomic lens. This study sought to determine whether socioeconomic status (SES) influences NFPA presentations and postoperative outcomes, as these associations could aid physicians in understanding case prognoses and complications. METHODS: The authors retrospectively analyzed 225 NFPA resections from 2012 to 2019 at their institution. Race, ethnicity, insurance status, estimated income, and having a primary care provider (PCP) were collected as 5 markers of SES. These markers were correlated with presenting tumor burden, presenting symptoms, surgical outcomes, and long-term clinical outcomes. RESULTS: All 5 examined SES markers influenced variance in patient presentation or outcome. Insurance status's effects on patient presentations disappeared when examining only patients with PCPs. Having a PCP was associated with significantly smaller tumor size at diagnosis (effect size = 0.404, p < 0.0001). After surgery, patients with PCPs had shorter postoperative hospital lengths of stay (p = 0.043) and lower rates of readmission within 30 days of discharge (OR 0.256, p = 0.047). Despite continuing follow-up for longer durations (p = 0.0004), patients with PCPs also had lower rates of tumor recurrence (p < 0.0001). Higher estimated income was similarly associated with longer follow-up (p = 0.002) and lower rates of tumor recurrence (p = 0.013). Among patients with PCPs, income was not associated with recurrence. CONCLUSIONS: This study found that while all 5 variables (race, ethnicity, insurance, PCP status, and estimated income) affected NFPA presentations and outcomes, having a PCP was the single most important of these socioeconomic factors, impacting hospital lengths of stay, readmission rates, follow-up adherence, and tumor recurrence. Having a PCP even protected low-income patients from experiencing increased rates of tumor recurrence. These protective findings suggest that addressing socioeconomic disparities may lead to better NFPA presentations and outcomes.

Artificial intelligence for adult spinal deformity: current state and future directions.

As we experience a technological revolution unlike any other time in history, spinal surgery as a discipline is poised to undergo a dramatic transformation. As enormous amounts of data become digitized and more readily available, medical professionals approach a critical juncture with respect to how advanced computational techniques may be incorporated into clinical practices. Within neurosurgery, spinal disorders in particular, represent a complex and heterogeneous disease entity that can vary dramatically in its clinical presentation and how it may impact patients' lives. The spectrum of pathologies is extremely diverse, including many different etiologies such as trauma, oncology, spinal deformity, infection, inflammatory conditions, and degenerative disease among others. The decision to perform spine surgery, especially complex spine surgery, involves several nuances due to the interplay of biomechanical forces, bony composition, neurologic deficits, and the patient's desired goals. Adult spinal deformity as an example is one of the most complex, given its involvement of not only the spine, but rather the entirety of the skeleton in order to appreciate radiographic completeness. With the vast array of variables contributing to spinal disorders, treatment algorithms can vary significantly, and it is very difficult for surgeons to predict how patients will respond to surgery. As such, it will become imperative for spine surgeons to utilize the burgeoning availability of advanced computational tools to process unprecedented amounts of data and provide novel insights into spinal disease. These tools range from predictive models built using machine learning algorithms, to deep learning methods for imaging analysis, to natural language processing that can mine text from electronic medical records or transcribed patient visits - all to better treat the intricacies of spinal disorders. The adoption of such techniques will empower patients and propel spine surgeons into the era of personalized medicine, by allowing clinical plans to be tailored to address individual patients' needs. This paper, which exists in the context of a larger body of literatutre, provides a comprehensive review of the current state and future of artificial intelligence and machine learning with a particular emphasis on Adult spinal deformity surgery.

State-of-the-art reviews predictive modeling in adult spinal deformity: applications of advanced analytics.

Adult spinal deformity (ASD) is a complex and heterogeneous disease that can severely impact patients' lives. While it is clear that surgical correction can achieve significant improvement of spinopelvic parameters and quality of life measures in adults with spinal deformity, there remains a high risk of complication associated with surgical approaches to adult deformity. Over the past decade, utilization of surgical correction for ASD has increased dramatically as deformity correction techniques have become more refined and widely adopted. Along with this increase in surgical utilization, there has been a massive undertaking by spine surgeons to develop more robust models to predict postoperative outcomes in an effort to mitigate the relatively high complication rates. A large part of this revolution within spine surgery has been the gradual adoption of predictive analytics harnessing artificial intelligence through the use of machine learning algorithms. The development of predictive models to accurately prognosticate patient outcomes following ASD surgery represents a dramatic improvement over prior statistical models which are better suited for finding associations between variables than for their predictive utility. Machine learning models, which offer the ability to make more accurate and reproducible predictions, provide surgeons with a wide array of practical applications from augmenting clinical decision making to more wide-spread public health implications. The inclusion of these advanced computational techniques in spine practices will be paramount for improving the care of patients, by empowering both patients and surgeons to more specifically tailor clinical decisions to address individual health profiles and needs.