Clarke, Michelle J.

Study Design: Retrospective cohort analysis. Objective: To determine whether the C2 exposure technique was a predictor of change in cervical alignment and patient-reported outcomes measures (PROMs) after posterior cervical decompression and fusion (PCDF) for degenerative indications. Background: In PCDF handling of the C2 posterior paraspinal musculature during the operative approach varies by surgeon technique. To date, no studies have investigated whether maintenance of the upper cervical semispinalis cervicis attachments as compared with complete reflection of upper cervical paraspinal musculature from the posterior bony elements is associated with superior radiographic and clinical outcomes after PCDF. Patients and Methods: All adult patients who underwent C2–T2 PCDF for myelopathy or myeloradiculopathy at multi-institutional academic centers between 2013 and 2020 were retrospectively identified. Patients were dichotomized by the C2 exposure technique into semispinalis preservation or midline muscular reflection groups. Preoperative and short and long-term postoperative radiographic outcomes (upper cervical alignment, global alignment, and fusion status) and PROMs (Visual Analog Scale–Neck, Neck Disability Index, and Short Form-12) were collected. Univariate analysis compared patient factors, radiographic measures, and PROMs across C2 exposure groups. Results: A total of 129 patients met the inclusion/exclusion criteria (73 muscle preservation and 56 muscle reflection). Patients in the muscular preservation group were on average younger (P = 0.005) and more likely to have bone morphogenic protein (P < 0.001) and C2 pars screws (P = 0.006) used during surgery. Preoperative to postoperative changes in C2 slope, C2 tilt, C2–C3 segmental lordosis, C2–C3 listhesis, C0–C2 Cobb angle, proximal junctional kyphosis, ADI, C1 lamina-occiput distance, C2 sagittal vertical axis, C2–C7 lordosis, and PROMs at all follow-up intervals did not vary significantly by C2 exposure technique. Likewise, there were no significant differences in fusion status, C2–C3 pseudoarthrosis, C2 screw loosening, and complication and revision rates between C2 exposure groups. Conclusions: Preservation of C2 semispinalis attachments versus muscular reflection did not significantly impact cervical alignment, clinical outcomes, or proximal junction complications in long-segment PCDF. Level of Evidence: Level III.

Study Design. Retrospective review of prospective, multicenter and international cohort study. Objective. To describe the effect of gender on HRQoL, clinical outcomes and survival for patients with spinal metastases treated with either surgery and/or radiation. Summary of Background Data. Gender differences in health-related outcomes are demonstrated in numerous studies, with women experiencing worse outcomes and receiving lower standards of care than men, however, the influence that gender has on low health-related quality of life (HRQoL) and clinical outcomes after spine surgery remains unclear. Methods. Patient demographic data, overall survival, treatment details, perioperative complications, and HRQoL measures including EQ-5D, pain NRS, the short form 36 version 2 (SF-36v2) and the Spine Oncology Study Group Outcomes Questionnaire (SOSGOQ2.0) were reviewed. Patients were stratified by sex, and a separate sensitivity analysis that excluded gender-specific cancers (i.e., breast, prostate, etc.) was performed. Results. The study cohort included 207 female and 183 male patients, with age, smoking status, and site of primary cancer being significantly different between the two cohorts (P<0.001). Both males and females experienced significantly improved SOSGOQ2.0, EQ-5D, and pain NRS scores at all study time points from baseline (P<0.001). Upon sensitivity analysis, (gender-specific cancers removed from analysis), the significant improvement in SOSGOQ physical, mental, and social subdomains and on SF-36 domains disappeared for females. Males experienced higher rates of postoperative complications. Kaplan-Meier survival analysis of both the overall and sensitivity analysis cohorts showed females lived longer than males after treatment (P=0.001 and 0.043, respectively). Conclusion. Both males and females experienced significantly improved HRQoL scores after treatment, but females demonstrated longer survival and a lower complication rate. This study suggests that gender may be a prognostic factor in survival and clinical outcomes for patients undergoing treatment for spine metastases and should be taken into consideration when counseling patients accordingly.

Introduction: The differential diagnosis of a spinal intradural extramedullary mass lesion is broad and includes meningioma, schwannoma, neurofibroma, leptomeningeal metastasis, and myxopapillary ependymoma. Though rare, lymphoma should be included in the differential diagnosis of a dural mass lesion. Case Report: A 38-year-old man presented with back pain that progressed over 1 month with associated focal tenderness over his mid to lower thoracic spine. He developed intermittent numbness of the bilateral lower extremities, nuchal rigidity, difficulty sleeping, and night sweats. A magnetic resonance imaging of the thoracic spine demonstrated a dorsal intradural extramedullary enhancing lesion from T7 to T10 extending outside the spinal canal. Dural thickening across the entire circumference of the spinal cord was noted. Computed tomography (CT)-guided biopsy of the thoracic lesion was performed, and pathology was consistent with follicular lymphoma. Fluorodeoxyglucose positron emission tomography:CT demonstrated no systemic disease. Bone marrow biopsy was negative for malignancy. Symptoms resolved with dexamethasone therapy. He was treated with bendamustine and rituximab with follow-up positron emission tomography:CT 2 months later demonstrating a complete response. Conclusions: Lymphoma can rarely present as an isolated dural lesion and should be considered in the differential diagnosis of intradural extramedullary spinal mass lesions. Prompt diagnosis and initiation of treatment can lead to complete response and resolution of symptoms.

OBJECTIVE Spine metastases are commonly treated with radiotherapy for local tumor control; pathologic fracture is a potential complication of spinal radiotherapy. Both Hounsfield units (HUs) on CT and vertebral bone quality (VBQ) on MRI have been argued to predict stability as measured by odds of pathologic fracture, although it is unclear if there is a difference in the predictive power between the two methodologies. The objective of the present study was to examine whether one methodology is a better predictor of pathologic fracture following radiotherapy for mobile spine metastases. METHODS Patients who underwent radiotherapy (conventional external-beam radiation therapy, stereotactic body radiation therapy, or intensity-modulated radiation therapy) for mobile spine (C1–L5) metastases at a tertiary care center were retrospectively identified. Details regarding underlying pathology, patient demographics, and tumor morphology were collected. Vertebral involvement was assessed using the Weinstein-Boriani-Biagini (WBB) system. Bone quality of the non–tumor-involved bone was assessed on both pretreatment CT and MRI. Univariable analyses were conducted to identify independent predictors of fracture, and Kaplan-Meier analyses were used to identify significant predictors of time to pathologic fracture. Stepwise Cox regression analysis was used to determine independent predictors of time to fracture. RESULTS One hundred patients were included (mean age 62.7 ± 11.9 years; 61% male), of whom 35 experienced postradiotherapy pathologic fractures. The most common histologies were lung (22%), prostate (21%), breast (14%), and renal cell (13%). On univariable analysis, the mean HUs of the vertebrae adjacent to the fractured vertebra were significantly lower among those experiencing fracture; VBQ was not significantly associated with fracture odds. Survival analysis showed that average HUs ≤ 132, nonprostate pathology, involvement of ≥ 3 vertebral body segments on the WBB system, Spine Instability Neoplastic Score (SINS) ≥ 7, and the presence of axial pain all predicted increased odds of fracture (all p < 0.001). Cox regression found that HUs ≤ 132 (OR 2.533, 95% CI 1.257–5.103; p = 0.009), ≥ 3 WBB vertebral body segments involved (OR 2.376, 95% CI 1.132–4.987; p = 0.022), and axial pain (OR 2.036, 95% CI 0.916–4.526; p = 0.081) predicted increased fracture odds, while prostate pathology predicted decreased odds (OR 0.076, 95% CI 0.009–0.613; p = 0.016). Sensitivity analysis suggested that an HU threshold of ≤ 132 and a SINS of ≥ 7 identified patients at increased risk of fracture. CONCLUSIONS The present results suggest that bone density surrogates as measured on CT, but not MRI, can be used to predict the risk of pathologic fracture following radiotherapy for mobile spine metastases. More extensive vertebral body involvement and the presence of mechanical axial pain additionally predict increased fracture odds.

Spinal subependymomas (SE) are rare, often indolent benign tumors presenting most frequently as intramedullary tumors in the cervical spine or cervicothoracic junction. When symptomatic, patients often present with years of sensory changes, weakness, paresthesias, or bowel and bladder dysfunction. Preoperatively, SE are difficult to distinguish radiographically from ependymomas or astrocytomas; however, it is important to make the distinction intraoperatively as complete resection can be curative. Here the authors present a rare case of recurrent, symptomatic cervical subependymoma which underwent gross-total resection and discussion of management strategies and outcomes of all SE at their institution.

OBJECTIVE Chordomas are slow-growing tumors derived from notochord remnants. Despite margin-negative excision and postoperative radiation therapy, spinal chordomas (SCs) often progress. The potential of immunohistochemical (IHC) markers, such as epithelial membrane antigen (EMA), combined with machine learning algorithms to predict long-term (≥ 12 months) postoperative tumor progression, has been understudied. The authors aimed to identify IHC markers using trained tree-based algorithms to predict long-term (≥ 12 months) postoperative tumor progression. METHODS The authors reviewed the records of patients who underwent resection of SCs between January 2017 and June 2021 across the Mayo Clinic enterprise. Demographics, type of treatment, histopathology, and other relevant clinical factors were abstracted from each patient’s record. Low tumor progression was defined as more than a 94.3-mm3 decrease in the tumor size at the latest radiographic follow-up. Decision trees and random forest classifiers were trained and tested to predict the long-term volumetric progression after an 80/20 data split. RESULTS Sixty-two patients diagnosed with and surgically treated for SC were identified, of whom 31 were found to have a more advanced tumor progression based on the tumor volume change cutoff of 94.3 mm3. The mean age was 54.3 ± 13.8 years, and most patients were male (62.9%) and White (98.4%). The most common treatment modality was subtotal resection with radiation therapy (35.5%), with proton beam therapy being the most common (71%). Most SCs were sacrococcygeal (41.9%), followed by cervical (32.3%). EMA-positive SCs had a postoperative progression risk of 67%. Pancytokeratin-positive SCs had a progression rate of 67%; however, patients with S100 protein–positive SCs had a 54% risk of progression. The accuracy of this model in predicting the progression of unseen test data was 66%. Pancytokeratin (mean minimal depth = 1.57), EMA (mean minimal depth = 1.58), cytokeratin A1/A3 (mean minimal depth = 1.59), and S100 protein (mean minimal depth = 1.6) predicted the long-term volumetric progression. Multiway variable importance plots show the relative importance of the top 10 variables based on three measures of varying significance and their predictive role. CONCLUSIONS These IHC variables with tree-based machine learning tools successfully demonstrate a high capacity to identify a patient’s tumor progression pattern with an accuracy of 66%. Pancytokeratin, EMA, cytokeratin A1/A3, and S100 protein were the IHC drivers of a low tumor progression. This shows the power of machine learning algorithms in analyzing and predicting outcomes of rare conditions in a small sample size.