A novel online calculator to predict nonroutine discharge, length of stay, readmission, and reoperation in patients undergoing surgery for intramedullary spinal cord tumors

The 4S of spinal astrocytoma: specific location, syrinx, spasticity and score on Modified Mccormick Scale (MMS) predict long term outcomes in patients undergoing surgical resection of intramedullary spinal astrocytomas

OBJECTIVES

The aim of this study was to explore the factors that could predict long term clinical outcomes in SA.

METHODS

A retrospective study was conducted wherein SA patients undergoing surgical resection with a minimum follow up of 12 months were included in this study. Modified Mccormick Scale (MMS) was utilized to record the neurological status of the patients both preoperatively and at last follow up. Outcomes were assessed as: long term neurological status, that is final MMS grade and neurological deterioration, defined as increase in MMS score as compared to preoperative MMS score. Survival analysis was performed using the kaplan meier curves.

RESULTS

71 patients were included in this study with mean age of 33.07years. At a mean follow up of 57 months, preoperative MMS was the single independent predictor for moderate-severe neurological deficit (MMS III to V) on multivariate analysis (OR: 30.2, p < 0.001) and had an outstanding AUC of 0.91. Six patients had neurological deterioration at long term follow up. Absence of spasticity (p = 0.028), thoracic-thoracolumbar tumors (p = 0.006), low MMS score (p = 0.01) and hypointense T1 weighted MRI (p = 0.009) were significant predictors of long term neurological deterioration. The median overall survival was 48 months and was significantly higher in low grade tumors (p < 0.001).

CONCLUSION

The study highlights the efficacy of clinical features as a predictor of long term functional outcomes in SA patients. Role of spasticity as a prognostic factor was explored for the first time in this study.

Astrocytomas of the spinal cord

Tumors of astrocytic origin represent one of the most frequent entities among the overall rare group of spinal cord gliomas. Initial clinical symptoms are often unspecific, and sensorimotor signs localizing to the spinal cord occur with progressing tumor growth. On MRI, a hyperintense intrinsic spinal cord signal on T2-weighted sequences with varying degrees of contrast enhancement raises suspicion for an infiltrative neoplasm. Blood and CSF analysis serves to exclude an infectious process, nutritional deficits, or metabolic disorders. When such other differential diagnoses have been ruled out, a neuropathological tissue-based analysis is warranted to confirm the diagnosis of a spinal cord astrocytoma and guide further patient management. As such, maximal safe resection forms the basis of any treatment. Meticulous preoperative planning is necessary to weigh the potential improvement in survival against the risk of functional deterioration. Intraoperative neuromonitoring and ultrasound may aid in achieving a more extensive resection. Depending on the assigned WHO tumor grade spanning from grade 1 to grade 4, the use of radiotherapy and chemotherapy might be indicated but also wait-and-scan approaches appear reasonable in tumors of lower grade. Close imaging follow-up is necessary given that recurrence inevitably occurs in astrocytomas of grades 2-4. Prognosis is so far dictated by tumor grade and histopathological findings, but also by age and clinical performance of the patient. Targeted therapies resting upon an in-depth tissue analysis are emerging in recurrent tumors, but no prospective study is available so far given the rarity of spinal cord astrocytomas.

Nondysraphic Intramedullary Spinal Cord Lipomas in the Adult Population

OBJECTIVE

Intramedullary spinal cord lipomas without spinal dysraphism are rare. Although they are benign tumors, they can cause significant neurological deficits. Their tight adherence to the spinal cord presents a challenge for resection. Therefore, we review our institutional experience treating adult patients with intramedullary lipomas in the absence of dysraphism and report long-term outcomes after resection.

METHODS

All adult patients undergoing resection of intramedullary spinal cord lipomas at a comprehensive cancer center between June 2011 and June 2023 were retrospectively identified. Patients with spinal dysraphism or extramedullary lipomas were excluded. Patients were included if they had microscopic surgical debulking with tissue sampling confirming the diagnosis.

RESULTS

Six patients were identified with a mean age of 35.0 ± 11.5 years, and 67% were female. Four cases localized to the thoracic spine. Symptoms included pain, numbness, and lower extremity motor weakness; only one patient reported bowel and bladder dysfunction. All patients experienced transient neurological decline in the immediate postoperative period. Five recovered to independent ambulation at long-term follow-up, including one recovering to full strength. One patient required a repeat resection after four years due to tumor progression and functional decline. Tumor progression was not recorded in the other patients.

CONCLUSIONS

Subtotal resection is a safe and effective treatment. Detethering of the spinal cord, resection of exophytic components, and tumor debulking can improve symptoms and prevent further deterioration in most cases. The resection can be assisted using a laser to vaporize the fatty tissue of the lipoma without physical manipulation of the spinal cord.

The application value and improved warning criterion of D-wave monitoring in intramedullary spinal cord tumor surgery

BACKGROUND CONTEXT

The primary treatment method for intramedullary spinal cord tumor (IMSCT) is surgical resection, but this procedure carries a significant risk of neurological damage. Intraoperative neurophysiological monitoring (IONM) has become a necessary adjunctive tool for IMSCT resection.

PURPOSE

The current study aimed to explore the application value of D-wave monitoring in IMSCT surgery, and tried to investigate a tailored criterion for its early warning.

STUDY DESIGN

A retrospective clinical study.

PATIENT SAMPLE

A retrospective analysis was conducted based on the data of patients who underwent IMSCT surgeries performed by the same neurosurgical team at our hospital. IONM was applied in all surgeries. According to inclusion and exclusion criteria, ultimately 90 patients were enrolled in the study.

OUTCOME MEASURES

The McCormick Scale (MMS) was applied to assess the functional outcome through outpatient visits or telephone follow-up at one month and six months postoperatively. Patients with an MMS grade over II one month after surgery were considered to have newly developed postoperative motor dysfunction (PMD). If the MMS grade could be restored to I or II six months after surgery, it was defined as a short-term PMD. Otherwise, it was defined as a long-term PMD.

METHODS

The predictive value of different IONM modalities, including somatosensory evoked potential (SEP), muscle motor evoked potential (MEP), and D-wave for PMD, was assessed with sensitivity, specificity, positive predictive value, negative predictive value, and subsequent logistic regression analysis. At last, the cut-off value of the D-wave amplitude reduction ratio for predicting PMD was obtained through the receiver operating characteristic (ROC) curve analysis.

RESULTS

SEP showed the worst performance in predicting short-term and long-term PMD. Significant MEP changes were indicated as an independent predictive factor for short-term PMD (OR 5.062, 95% CI 1.947-13.166, p=.001), while D-wave changes were demonstrated as an independent predictor for long-term PMD (OR 339.433, 95% CI 11.337-10770.311, p=.001). The optimum cut-off value of the D-wave amplitude reduction ratio for predicting long-term PMD was 42.18%, with a sensitivity of 100% and a specificity of 93.8% (AUC=0.981, p<.001).

CONCLUSIONS

D-wave monitoring showed extremely high specificity in predicting PMD compared to SEP and MEP monitoring. Moreover, the authors suggested that a D-wave amplitude reduction of over 40% during IMSCT surgery generally indicates long-term PMD for patients.

What Factors Predict the Development of Neurologic Deficits Following Resection of Intramedullary Spinal Cord Tumors: A Multi-Center Study

BACKGROUND

Intramedullary spinal cord tumors are challenging to resect, and their postoperative neurological outcomes are often difficult to predict, with few studies assessing this outcome.

METHODS

We reviewed the medical records of all patients surgically treated for Intramedullary spinal cord tumors at our multisite tertiary care institution (Mayo Clinic Arizona, Mayo Clinic Florida, Mayo Clinic Rochester) between June 2002 and May 2020. Variables that were significant in the univariate analyses were included in a multivariate logistic regression. "MissForest" operating on the Random Forest algorithm, was used for data imputation, and K-prototype was used for data clustering. Heatmaps were added to show correlations between postoperative neurological deficit and all other included variables. Shapley Additive exPlanations were implemented to understand each feature's importance.

RESULTS

Our query resulted in 315 patients, with 160 meeting the inclusion criteria. There were 53 patients with astrocytoma, 66 with ependymoma, and 41 with hemangioblastoma. The mean age (standard deviation) was 42.3 (17.5), and 48.1% of patients were women (n = 77/160). Multivariate analysis revealed that pathologic grade >3 (OR = 1.55; CI = [0.67, 3.58], P = 0.046 predicted a new neurological deficit. Random Forest algorithm (supervised machine learning) found age, use of neuromonitoring, histology of the tumor, performing a midline myelotomy, and tumor location to be the most important predictors of new postoperative neurological deficits.

CONCLUSIONS

Tumor grade/histology, age, use of neuromonitoring, and myelotomy type appeared to be most predictive of postoperative neurological deficits. These results can be used to better inform patients of perioperative risk.

Development and Validation of an Online Calculator to Predict Proximal Junctional Kyphosis After Adult Spinal Deformity Surgery Using Machine Learning

OBJECTIVE

Although adult spinal deformity (ASD) surgery aims to restore and maintain alignment, proximal junctional kyphosis (PJK) may occur. While existing scoring systems predict PJK, they predominantly offer a generalized 3-tier risk classification, limiting their utility for nuanced treatment decisions. This study seeks to establish a personalized risk calculator for PJK, aiming to enhance treatment planning precision.

METHODS

Patient data for ASD were sourced from the Korean spinal deformity database. PJK was defined a proximal junctional angle (PJA) of ≥ 20° at the final follow-up, or an increase in PJA of ≥ 10° compared to the preoperative values. Multivariable analysis was performed to identify independent variables. Subsequently, 5 machine learning models were created to predict individualized PJK risk post-ASD surgery. The most efficacious model was deployed as an online and interactive calculator.

RESULTS

From a pool of 201 patients, 49 (24.4%) exhibited PJK during the follow-up period. Through multivariable analysis, postoperative PJA, body mass index, and deformity type emerged as independent predictors for PJK. When testing machine learning models using study results and previously reported variables as hyperparameters, the random forest model exhibited the highest accuracy, reaching 83%, with an area under the receiver operating characteristics curve of 0.76. This model has been launched as a freely accessible tool at: (https://snuspine.shinyapps.io/PJKafterASD/).

CONCLUSION

An online calculator, founded on the random forest model, has been developed to gauge the risk of PJK following ASD surgery. This may be a useful clinical tool for surgeons, allowing them to better predict PJK probabilities and refine subsequent therapeutic strategies.

Approaches to Incidental Intradural Tumors of the Spine in the Pediatric Population

BACKGROUND

Incidental intradural tumors of the spine in the pediatric population are rare lesions whose management remains unclear. Surgeons must balance the risks of iatrogenic deficits and complications after surgical resection against the risks from progressive growth of the tumor. Moreover, the natural history of an incidental finding can be difficult to predict. Here, we review the literature on incidental intradural tumors of the spine and present considerations for their management.

SUMMARY

Growth of the tumor or changes in radiographic features are usually indications for resection. Asymptomatic lesions can be found in patients with genetic syndromes that predispose to tumor formation, such as neurofibromatosis type 1 and 2, schwannomatosis, and Von-Hippel-Lindau syndrome, and careful workup of a genetic cause is warranted in any patient presenting with multiple tumors and/or cutaneous features. Close follow-up is generally favored given the heavy tumor burden; however, some recommend pre-emptive resection to prevent permanent neurological deficits. Incidental intradural tumors can also occur in association with hydrocephalus, significant syringomyelia, and cord compression, and surgical treatment is usually warranted. Tumors may also be discovered as part of the workup for scoliosis, where they are not truly incidental to the scoliosis but rather are contributing to curve deformation.

KEY MESSAGES

Thorough workup of patients for associated genetic syndromes or comorbidities should be undertaken in pediatric patients with incidental intradural tumors. Further research is needed into the natural history of these incidental lesions. Incidental tumors can often be managed conservatively with close follow-up, with surgical intervention warranted for expanding tumors or new-onset symptoms.

Current Applications of Machine Learning for Spinal Cord Tumors

Spinal cord tumors constitute a diverse group of rare neoplasms associated with significant mortality and morbidity that pose unique clinical and surgical challenges. Diagnostic accuracy and outcome prediction are critical for informed decision making and can promote personalized medicine and facilitate optimal patient management. Machine learning has the ability to analyze and combine vast amounts of data, allowing the identification of patterns and the establishment of clinical associations, which can ultimately enhance patient care. Although artificial intelligence techniques have been explored in other areas of spine surgery, such as spinal deformity surgery, precise machine learning models for spinal tumors are lagging behind. Current applications of machine learning in spinal cord tumors include algorithms that improve diagnostic precision by predicting genetic, molecular, and histopathological profiles. Furthermore, artificial intelligence-based systems can assist surgeons with preoperative planning and surgical resection, potentially reducing the risk of recurrence and consequently improving clinical outcomes. Machine learning algorithms promote personalized medicine by enabling prognostication and risk stratification based on accurate predictions of treatment response, survival, and postoperative complications. Despite their promising potential, machine learning models require extensive validation processes and quality assessments to ensure safe and effective translation to clinical practice.

Surgical approaches to intramedullary spinal cord astrocytomas in the age of genomics

Intramedullary astrocytomas represent approximately 30%–40% of all intramedullary tumors and are the most common intramedullary tumor in children. Surgical resection is considered the mainstay of treatment in symptomatic patients with neurological deficits. Gross total resection (GTR) can be difficult to achieve as astrocytomas frequently present as diffuse lesions that infiltrate the cord. Therefore, GTR carries a substantial risk of new post-operative deficits. Consequently, subtotal resection and biopsy are often the only surgical options attempted. A midline or paramedian sulcal myelotomy is frequently used for surgical resection, although a dorsal root entry zone myelotomy can be used for lateral tumors. Intra-operative neuromonitoring using D-wave integrity, somatosensory, and motor evoked potentials is critical to facilitating a safe resection. Adjuvant radiation and chemotherapy, such as temozolomide, are often administered for high-grade recurrent or progressive lesions; however, consensus is lacking on their efficacy. Biopsied tumors can be analyzed for molecular markers that inform clinicians about the tumor’s prognosis and response to conventional as well as targeted therapeutic treatments. Stratification of intramedullary tumors is increasingly based on molecular features and mutational status. The landscape of genetic and epigenetic mutations in intramedullary astrocytomas is not equivalent to their intracranial counterparts, with important difference in frequency and type of mutations. Therefore, dedicated attention is needed to cohorts of patients with intramedullary tumors. Targeted therapeutic agents can be designed and administered to patients based on their mutational status, which may be used in coordination with traditional surgical resection to improve overall survival and functional status.