Determining Differences in Perioperative Functional Mobility Patterns in Lumbar Decompression Versus Fusion Patients Using Smartphone Activity Data.

BACKGROUND AND OBJECTIVES: Smartphone activity data recorded through high-fidelity accelerometry can provide accurate postoperative assessments of patient mobility. The "big data" available through smartphones allows for advanced analyses, yielding insight into patient well-being. This study compared rate of change in functional activity data between lumbar fusion (LF) and lumbar decompression (LD) patients to determine preoperative and postoperative course differences. METHODS: Twenty-three LF and 18 LD patients were retrospectively included. Activity data (steps per day) recorded in Apple Health, encompassing over 70 000 perioperative data points, was classified into 6 temporal epochs representing distinct functional states, including acute preoperative decline, immediate postoperative recovery, and postoperative decline. The daily rate of change of each patient's step counts was calculated for each perioperative epoch. RESULTS: Patients undergoing LF demonstrated steeper preoperative declines than LD patients based on the first derivative of step count data (P = .045). In the surgical recovery phase, LF patients had slower recoveries (P = .041), and LF patients experienced steeper postoperative secondary declines than LD patients did (P = .010). The rate of change of steps per day demonstrated varying perioperative trajectories that were not explained by differences in age, comorbidities, or levels operated. CONCLUSION: Patients undergoing LF and LD have distinct perioperative activity profiles characterized by the rate of change in the patient daily steps. Daily steps and their rate of change is thus a valuable metric in phenotyping patients and understanding their postsurgical outcomes. Prospective studies are needed to expand upon these data and establish causal links between preoperative patient mobility, patient characteristics, and postoperative functional outcomes.

Advancements in dendritic cell vaccination: enhancing efficacy and optimizing combinatorial strategies for the treatment of glioblastoma.

Glioblastomas (GBM) are highly invasive, malignant primary brain tumors. The overall prognosis is poor, and management of GBMs remains a formidable challenge, necessitating novel therapeutic strategies such as dendritic cell vaccinations (DCVs). While many early clinical trials demonstrate an induction of an antitumoral immune response, outcomes are mixed and dependent on numerous factors that vary between trials. Optimization of DCVs is essential; the selection of GBM-specific antigens and the utilization of 18F-fludeoxyglucose Positron Emission Tomography (FDG-PET) may add significant value and ultimately improve outcomes for patients undergoing treatment for glioblastoma. This review provides an overview of the mechanism of DCV, assesses previous clinical trials, and discusses future strategies for the integration of DCV into glioblastoma treatment protocols. To conclude, the review discusses challenges associated with the use of DCVs and highlights the potential of integrating DCV with standard therapies.

Large Language Model-Based Neurosurgical Evaluation Matrix: A Novel Scoring Criteria to Assess the Efficacy of ChatGPT as an Educational Tool for Neurosurgery Board Preparation.

INTRODUCTION: Technological advancements are reshaping medical education, with digital tools becoming essential in all levels of training. Amidst this transformation, the study explores the potential of ChatGPT, an artificial intelligence model by OpenAI, in enhancing neurosurgical board education. The focus extends beyond technology adoption to its effective utilization, with ChatGPT's proficiency evaluated against practice questions from the Primary Neurosurgery Written Board Exam. METHODS: Using the Congress of Neurologic Surgeons (CNS) Self-Assessment Neurosurgery (SANS) Exam Board Review Prep questions, we conducted 3 rounds of analysis with ChatGPT. We developed a novel ChatGPT Neurosurgical Evaluation Matrix (CNEM) to assess the output quality, accuracy, concordance, and clarity of ChatGPT's answers. RESULTS: ChatGPT achieved spot-on accuracy for 66.7% of prompted questions, 59.4% of unprompted questions, and 63.9% of unprompted questions with a leading phrase. Stratified by topic, accuracy ranged from 50.0% (Vascular) to 78.8% (Neuropathology). In comparison to SANS explanations, ChatGPT output was considered better in 19.1% of questions, equal in 51.6%, and worse in 29.3%. Concordance analysis showed that 95.5% of unprompted ChatGPT outputs and 97.4% of unprompted outputs with a leading phrase were aligned. CONCLUSIONS: Our study evaluated the performance of ChatGPT in neurosurgical board education by assessing its accuracy, clarity, and concordance. The findings highlight the potential and challenges of integrating AI technologies like ChatGPT into medical and neurosurgical board education. Further research is needed to refine these tools and optimize their performance for enhanced medical education and patient care.

Aging and Cerebral Glucose Metabolism: 18F-FDG-PET/CT Reveals Distinct Global and Regional Metabolic Changes in Healthy Patients.

Alterations in cerebral glucose metabolism can be indicative of both normal and pathological aging processes. In this retrospective study, we evaluated global and regional neurological glucose metabolism in 73 healthy individuals (mean age: 35.8 ± 13.1 years; 82.5% female) using 18F-Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT). This population exhibited a low prevalence of comorbidities associated with cerebrovascular risk factors. We utilized 18F-FDG-PET/CT imaging and quantitative regional analysis to assess cerebral glucose metabolism. A statistically significant negative correlation was found between age and the global standardized uptake value mean (SUVmean) of FDG uptake (p = 0.000795), indicating a decrease in whole-brain glucose metabolism with aging. Furthermore, region-specific analysis identified significant correlations in four cerebral regions, with positive correlations in the basis pontis, cerebellar hemisphere, and cerebellum and a negative correlation in the lateral orbital gyrus. These results were further confirmed via linear regression analysis. Our findings reveal a nuanced understanding of how aging affects glucose metabolism in the brain, providing insight into normal neurology. The study underscores the utility of 18F-FDG-PET/CT as a sensitive tool in monitoring these metabolic changes, highlighting its potential for the early detection of neurological diseases and disorders related to aging.

Bilateral Carotid Artery Molecular Calcification Assessed by [18F] Fluoride PET/CT: Correlation with Cardiovascular and Thromboembolic Risk Factors.

Atherosclerosis, a leading cause of mortality and morbidity worldwide, involves inflammatory processes that result in plaque formation and calcification. The early detection of the molecular changes underlying these processes is crucial for effective disease management. This study utilized positron emission tomography/computed tomography (PET/CT) with [18F] sodium fluoride (NaF) as a tracer to visualize active calcification and inflammation at the molecular level. Our aim was to investigate the association between cardiovascular risk factors and [18F] NaF uptake in the left and right common carotid arteries (LCC and RCC). A cohort of 102 subjects, comprising both at-risk individuals and healthy controls, underwent [18F] NaF PET/CT imaging. The results revealed significant correlations between [18F] NaF uptake and cardiovascular risk factors such as age (ß = 0.005, 95% CI 0.003-0.008, p < 0.01 in LCC and ß = 0.006, 95% CI 0.004-0.009, p < 0.01 in RCC), male gender (ß = -0.08, 95% CI -0.173--0.002, p = 0.04 in LCC and ß = -0.13, 95% CI -0.21--0.06, p < 0.01 in RCC), BMI (ß = 0.02, 95% CI 0.01-0.03, p < 0.01 in LCC and ß = 0.02, 95% CI 0.01-0.03, p < 0.01 in RCC), fibrinogen (ß = 0.006, 95% CI 0.0009-0.01, p = 0.02 in LCC and ß = 0.005, 95% CI 0.001-0.01, p = 0.01), HDL cholesterol (ß = 0.13, 95% CI 0.04-0.21, p < 0.01 in RCC only), and CRP (ß = -0.01, 95% CI -0.02-0.001, p = 0.03 in RCC only). Subjects at risk showed a higher [18F] NaF uptake compared to healthy controls (one-way ANOVA; p = 0.02 in LCC and p = 0.04 in RCC), and uptake increased with estimated cardiovascular risk (one-way ANOVA, p < 0.01 in LCC only). These findings underscore the potential of [18F] NaF PET/CT as a sensitive tool for the early detection of atherosclerotic plaque, assessment of cardiovascular risk, and monitoring of disease progression. Further research is needed to validate the technique's predictive value and its potential impact on clinical outcomes.

The Role of FDG-PET in the Evaluation of Hidradenitis Suppurativa: A Systematic Review.

Hidradenitis suppurativa (HS) is a chronic skin disorder characterized by nodules, comedones, and sinus tracts that often leave prominent scarring. In recent years, non-invasive imaging techniques have been used to assess the inflammatory activity, vascularization, and treatment response of lesions. Specifically, fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) scans may aid in identifying systemic inflammation in patients with HS, improving diagnosis. Inflamed hypermetabolic tissues exhibit a greater uptake of FDG due to increased glucose uptake and vascularity. A systematic review was conducted to summarize the utility of nuclear imaging techniques in the diagnosis and treatment follow-up of HS. PubMed, Scopus, and ScienceDirect databases were utilized for relevant articles discussing the utility of PET scans in managing HS. A total of 51 citations were identified in the initial search. Following the review of titles, abstracts, and duplicates, 43 articles were excluded, leaving a total of eight articles for analysis. Data were extracted from each article, encompassing the number of patients, imaging techniques employed, and final results. An analysis of the data demonstrated that FDG-PET showed evidence of identifying subclinical lesions of the disease, improving the visualization of HS, and providing an objective method of assessing severity.

Defining the minimal clinically important difference in smartphone-based mobility after spine surgery: correlation of survey questionnaire to mobility data.

OBJECTIVE: Patient-reported outcome measures (PROMs) are the gold standard for assessing postoperative outcomes in spine surgery. However, PROMs are also limited by the inherent subjectivity of self-reported qualitative data. Recent literature has highlighted the utility of patient mobility data streamed from smartphone accelerometers as an objective measure of functional outcomes and complement to traditional PROMs. Still, for activity-based data to supplement existing PROMs, they must be validated against current metrics. In this study, the authors assessed the relationships and concordance between longitudinal smartphone-based mobility data and PROMs. METHODS: Patients receiving laminectomy (n = 21) or fusion (n = 10) between 2017 and 2022 were retrospectively included. Activity data (steps-per-day count) recorded in the Apple Health mobile application over a 2-year perioperative window were extracted and subsequently normalized to allow for intersubject comparison. PROMS, including the visual analog scale (VAS), Patient Reported Outcome Measurement Information System Pain Interference (PROMIS-PI), Oswestry Disability Index (ODI), and EQ-5D, collected at the preoperative and 6-week postoperative visits were retrospectively extracted from the electronic medical record. Correlations between PROMs and patient mobility were assessed and compared between patients who did and those who did not achieve the established minimal clinically important difference (MCID) for each measure. RESULTS: A total of 31 patients receiving laminectomy (n = 21) or fusion (n = 10) were included. Change between preoperative and 6-week postoperative VAS and PROMIS-PI scores demonstrated moderate (r = -0.46) and strong (r = -0.74) inverse correlations, respectively, with changes in normalized steps-per-day count. In cohorts of patients who achieved PROMIS-PI MCID postoperatively, indicating subjective improvement in pain, there was a 0.784 standard deviation increase in normalized steps per day, representing a 56.5% improvement (p = 0.027). Patients who did achieve the MCID of improvement in either PROMIS-PI or VAS after surgery were more likely to experience an earlier sustained improvement in physical activity commensurate to or greater than their preoperative baseline (p = 2.98 × 10-18) than non-MCID patients. CONCLUSIONS: This study demonstrates a strong correlation between changes in mobility data extracted from patient smartphones and changes in PROMs following spine surgery. Further elucidating this relationship will allow for more robust supplementation of existing spine outcome measure tools with analyzed objective activity data.