Object Jugulotympanic paragangliomas (JTPs) are rare benign tumors whose surgical treatment is usually associated with partial resection of the lesion, high morbidity, and even death. Gamma Knife radiosurgery (GKRS) has been reported as a useful treatment option. The goal of this retrospective study is to analyze the role of GKRS in tumor volume control and clinical outcomes of these patients. Methods A total of 75 patients with JTPs were treated with GKRS at the authors' center from 1995 to 2012. The authors analyzed those treated during this period to allow for a minimal observation time of 2 years. The MR images and clinical reports of these patients were reviewed to assess clinical and volumetric outcomes of the tumors. The radiological and clinical assessments, along with a group of prognostic factors measured, were analyzed using descriptive methods. The time to volumetric and clinical progression was analyzed using the Kaplan-Meier method. Prognostic factors were identified using log-rank statistics and multivariate Cox regression models. Results The mean follow-up was 86.4 months. The authors observed volumetric tumor control in 94.8% of cases. In 67.2% of cases, tumor volume decreased by a mean of 40.1% from the original size. Of patients with previous tinnitus, 54% reported complete recovery. Improvement of other symptoms was observed in 34.5% of cases. Overall, clinical control was achieved in 91.4% of cases. Previous embolization and familial history of paraganglioma were selected as significant prognostic factors for volumetric response to GKRS treatment in the univariate analysis. In multivariate analysis, no factors were significantly correlated with progression-free survival. No patient died of side effects related to GKRS treatment or tumor progression. Conclusions Gamma Knife radiosurgery is an effective, safe, and efficient therapeutic option for the treatment of these tumors as a first-line treatment or in conjunction with traditional surgery, endovascular treatment, or conventional fractionated radiotherapy.

OBJECTIVEThe 6-minute walking test (6WT) is used to determine restrictions in a subject’s 6-minute walking distance (6WD) due to lumbar degenerative disc disease. To facilitate simple and convenient patient self-measurement, a free and reliable smartphone app using Global Positioning System coordinates was previously designed. The authors aimed to determine normative values for app-based 6WD measurements.METHODSThe maximum 6WD was determined three times using app-based measurement in a sample of 330 volunteers without previous spine surgery or current spine-related disability, recruited at 8 centers in 5 countries (mean subject age 44.2 years, range 16–91 years; 48.5% male; mean BMI 24.6 kg/m2, range 16.3–40.2 kg/m2; 67.9% working; 14.2% smokers). Subjects provided basic demographic information, including comorbidities and patient-reported outcome measures (PROMs): visual analog scale (VAS) for both low-back and lower-extremity pain, Core Outcome Measures Index (COMI), Zurich Claudication Questionnaire (ZCQ), and subjective walking distance and duration. The authors determined the test-retest reliability across three measurements (intraclass correlation coefficient [ICC], standard error of measurement [SEM], and mean 6WD [95% CI]) stratified for age and sex, and content validity (linear regression coefficients) between 6WD and PROMs.RESULTSThe ICC for repeated app-based 6WD measurements was 0.89 (95% CI 0.87–0.91, p < 0.001) and the SEM was 34 meters. The overall mean 6WD was 585.9 meters (95% CI 574.7–597.0 meters), with significant differences across age categories (p < 0.001). The 6WD was on average about 32 meters less in females (570.5 vs 602.2 meters, p = 0.005). There were linear correlations between average 6WD and VAS back pain, VAS leg pain, COMI Back and COMI subscores of pain intensity and disability, ZCQ symptom severity, ZCQ physical function, and ZCQ pain and neuroischemic symptoms subscores, as well as with subjective walking distance and duration, indicating that subjects with higher pain, higher disability, and lower subjective walking capacity had significantly lower 6WD (all p < 0.001).CONCLUSIONSThis study provides normative data for app-based 6WD measurements in a multicenter sample from 8 institutions and 5 countries. These values can now be used as reference to compare 6WT results and quantify objective functional impairment in patients with degenerative diseases of the spine using z-scores. The authors found a good to excellent test-retest reliability of the 6WT app, a low area of uncertainty, and high content validity of the average 6WD with commonly used PROMs.

Objective: We assess the efficacy of the metabolomic profile from glioma biopsies in providing estimates of postsurgical Overall Survival in glioma patients. Methods: Tumor biopsies from 46 patients bearing gliomas, obtained neurosurgically in the period 1992–1998, were analyzed by high resolution 1 H magnetic resonance spectroscopy (HR- 1 H MRS), following retrospectively individual postsurgical Overall Survival up to 720 weeks. Results: The Overall Survival profile could be resolved in three groups; Short (shorter than 52 weeks, n = 19), Intermediate (between 53 and 364 weeks, n = 19) or Long (longer than 365 weeks, n = 8), respectively. Classical histopathological analysis assigned WHO grades II–IV to every biopsy but notably, some patients with low grade glioma depicted unexpectedly Short Overall Survival, while some patients with high grade glioma, presented unpredictably Long Overall Survival. To explore the reasons underlying these different responses, we analyzed HR- 1 H MRS spectra from acid extracts of the same biopsies, to characterize the metabolite patterns associated to OS predictions. Poor prognosis was found in biopsies with higher contents of alanine, acetate, glutamate, total choline, phosphorylcholine, and glycine, while more favorable prognosis was achieved in biopsies with larger contents of total creatine, glycerol-phosphorylcholine, and myo-inositol. We then implemented a multivariate analysis to identify hierarchically the influence of metabolomic biomarkers on OS predictions, using a Classification Regression Tree (CRT) approach. The CRT based in metabolomic biomarkers grew up to three branches and split into eight nodes, predicting correctly the outcome of 94.7% of the patients in the Short Overall Survival group, 78.9% of the patients in the Intermediate Overall Survival group, and 75% of the patients in the Long Overall Survival group, respectively. Conclusion: Present results indicate that metabolic profiling by HR- 1 H MRS improves the Overall Survival predictions derived exclusively from classical histopathological gradings, thus favoring more precise therapeutic decisions.

Background Indications and outcomes in lumbar spinal fusion for degenerative disease are notoriously heterogenous. Selected subsets of patients show remarkable benefit. However, their objective identification is often difficult. Decision-making may be improved with reliable prediction of long-term outcomes for each individual patient, improving patient selection and avoiding ineffective procedures. Methods Clinical prediction models for long-term functional impairment [Oswestry Disability Index (ODI) or Core Outcome Measures Index (COMI)], back pain, and leg pain after lumbar fusion for degenerative disease were developed. Achievement of the minimum clinically important difference at 12 months postoperatively was defined as a reduction from baseline of at least 15 points for ODI, 2.2 points for COMI, or 2 points for pain severity. Results Models were developed and integrated into a web-app (https://neurosurgery.shinyapps.io/fuseml/) based on a multinational cohort [N = 817; 42.7% male; mean (SD) age: 61.19 (12.36) years]. At external validation [N = 298; 35.6% male; mean (SD) age: 59.73 (12.64) years], areas under the curves for functional impairment [0.67, 95% confidence interval (CI): 0.59–0.74], back pain (0.72, 95%CI: 0.64–0.79), and leg pain (0.64, 95%CI: 0.54–0.73) demonstrated moderate ability to identify patients who are likely to benefit from surgery. Models demonstrated fair calibration of the predicted probabilities. Conclusions Outcomes after lumbar spinal fusion for degenerative disease remain difficult to predict. Although assistive clinical prediction models can help in quantifying potential benefits of surgery and the externally validated FUSE-ML tool may aid in individualized risk–benefit estimation, truly impacting clinical practice in the era of “personalized medicine” necessitates more robust tools in this patient population.

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