Race-Ethnicity, Rurality, and Age in Prospective Preferences and Concerns Regarding Closed-Loop Implanted Neural Devices.

OBJECTIVE: Responsive and human-centered neurotechnology development requires attention to public perceptions, particularly among groups underserved by existing treatments. METHODS: The authors conducted a preregistered nationally representative survey (https://osf.io/ej9h2) using the NORC at the University of Chicago AmeriSpeak panel. One vignette compared an implanted neural device with surgical resection in a scenario involving epilepsy, and another compared an implanted neural device with medications in a scenario involving mood disorders. The survey also contained questions about respondents' confidence that a device would be available if needed and confidence that enough research has been conducted among people like themselves. Responses were entered into nested survey-weighted logistic regression models, including a base demographic model (to test the overall effect of demographic factors) and an adjusted model that also included socioeconomic, religious and political, and health care access predictors. RESULTS: A total of 1,047 adults responded to the survey, which oversampled Black non-Hispanic (N=214), Hispanic (N=210), and rural (N=219) Americans. In the base demographic model, older Americans were more likely to prefer an implanted device in the two scenarios, and non-Hispanic Black Americans were less likely than non-Hispanic White Americans to prefer a device; rural Americans were less confident than urban or suburban Americans in having access, and non-Hispanic Black and rural Americans were less confident that enough research has been conducted among people like themselves. In adjusted models, income was a key mediator, partially explaining the effect of age and the contrast between Black and White non-Hispanic respondents on preferences for a device in the epilepsy scenario and fully explaining the effect of rurality on confidence in access. CONCLUSIONS: Demographic differences in prospective preferences and concerns highlight the importance of including members of underserved communities in neurotechnology development.

Use of minimally invasive ultrasound transducer during tubular microdiscectomy.

Minimally invasive ultrasound during tubular microdiscectomy is novel. The authors report the technique during surgery for L5-S1 herniated disc. Ultrasound provided real-time visualization of the pathology and neural elements. After discectomy and tactile assessment, ultrasound showed decompression of the thecal sac and traversing nerve root. The patient tolerated the procedure well, with resolution of preoperative pain and strength improvement. Postoperative MRI revealed a residual asymptomatic disc fragment that was retrospectively identified on ultrasonography. Minimally invasive ultrasound could become a useful supplement to direct visual and tactile assessment during tubular microdiscectomy, but further experience with surgical anatomy on ultrasound is required. The video can be found here: https://stream.cadmore.media/r10.3171/2024.1.FOCVID23206.

Personalized Approaches to Spine Surgery.

Patient-centric decision-making has imbued all aspects of health care, including spine surgery. This review describes how spine surgeons can use evolving technologies and knowledge of disease and pain states to tailor their surgical approach to the individual patient. This includes preoperative screening for and optimization of low bone mineral density, intraoperative selection of implant material and customization of interbody cages and screws, and postoperative personalization of pain regimens and rehabilitation courses. By working in a multidisciplinary fashion, spine surgeons can avail themselves of these advances to provide individualized care.

Enhancing neuro-oncology care through equity-driven applications of artificial intelligence.

The disease course and clinical outcome for brain tumor patients depend not only on the molecular and histological features of the tumor but also on the patient's demographics and social determinants of health. While current investigations in neuro-oncology have broadly utilized artificial intelligence (AI) to enrich tumor diagnosis and more accurately predict treatment response, postoperative complications, and survival, equity-driven applications of AI have been limited. However, AI applications to advance health equity in the broader medical field have the potential to serve as practical blueprints to address known disparities in neuro-oncologic care. In this consensus review, we will describe current applications of AI in neuro-oncology, postulate viable AI solutions for the most pressing inequities in neuro-oncology based on broader literature, propose a framework for the effective integration of equity into AI-based neuro-oncology research, and close with the limitations of AI.

Surgical resection of lumbar intradural metastatic renal cell carcinoma.

A 60-year-old male with renal cell carcinoma (RCC) presented with back pain, weakness, and bowel and bladder urgency. MRI demonstrated a cauda equina tumor at L2. Following L1-3 laminectomies, intraoperative ultrasound localized the tumor. After dural opening, a vascular tumor was adherent to the cauda equina. Intraoperative nerve stimulation helped to identify the nerve rootlets. Tumor was removed in a piecemeal fashion. Tumor dissection caused periodic spasms in L1-3 distributions. A neuromonitoring checklist was used to recover motor evoked potential signals with elevated mean arterial pressures. Hemostasis was challenging with the vascular tumor. Intraoperative ultrasound confirmed tumor debulking. Pathology confirmed metastatic RCC.