Neurosurgery

Single pulse electrical stimulation of the medial thalamic surface induces narrower high gamma band activities in the sensorimotor cortex.

The human thalamus projects nerve fibers to all cortical regions and propagates epileptic activity. However, opportunities to directly record thalamic and cortical neural activities simultaneously are extremely limited and their electrophysiological interactions remain largely unexplored. Therefore, in this study, we recruited six patients who underwent awake craniotomy with opened lateral ventric...

Development and validation of a prognostic prediction model for lumbar-disc herniation based on machine learning and fusion of clinical text data and radiomic features.

OBJECTIVE: Based on preoperative clinical text data and lumbar magnetic resonance imaging (MRI), we applied machine learning (ML) algorithms to construct a model that would predict early recurrence in lumbar-disc herniation (LDH) patients who underwent percutaneous endoscopic lumbar discectomy (PELD). We then explored the clinical performance of this prognostic prediction model via multimodal-data...

Plasma proteomics profiles predict the risk of future aortic aneurysm and aortic dissection.

BACKGROUND: Aortic aneurysms and aortic dissections (AA/AD) are serious vascular conditions that often progress without symptoms and are associated wi...

Novel Application of Connectomics to the Surgical Management of Pediatric Arteriovenous Malformations.

Introduction The emergence of connectomics in neurosurgery has allowed for construction of detailed maps of white matter connections, incorporating bo...

The role of generative artificial intelligence in deciding fusion treatment of lumbar degeneration: a comparative analysis and narrative review.

PURPOSE: This study analyzed responses and readability of generative artificial intelligence (AI) models to questions and recommendations from the 201...

Adolescent lumbar disc herniation: etiology, diagnosis, and treatment options.

Adolescent lumbar disc herniation (ALDH) is a type of disease with a much lower incidence than adult lumbar disc herniation (LDH), which has a trend o...

Feasibility of Ultralow-Dose CT With Deep-Learning Reconstruction for Aneurysm Diameter Measurement in Post-EVAR Follow-Up: A Prospective Comparative Study With Conventional CT.

PURPOSE: We conducted a prospective study to evaluate the usefulness of ultralow-dose computed tomography (ULD-CT) with deep-learning reconstruction (...

Deciphering the transcriptomic characteristic of lactate metabolism and the immune infiltration landscape in abdominal aortic aneurysm.

BACKGROUND: Abdominal aortic aneurysm (AAA) is a common degenerative vascular disease characterized by progressive dilation of the abdominal aorta, wh...

Minimizing human-induced variability in quantitative angiography for a robust and explainable AI-based occlusion prediction in flow diverter-treated aneurysms.

BACKGROUND: Bias from contrast injection variability is a significant obstacle to accurate intracranial aneurysm (IA) occlusion prediction using quant...

Artery fragment guided approach for enhancing cerebral aneurysm detection in TOF-MRA imaging.

BACKGROUND: Cerebral aneurysms are a type of cerebrovascular disease that poses a severe threat to life and health. Early screening using Time-of-Flig...

Inconsistency of AI in intracranial aneurysm detection with varying dose and image reconstruction.

Scanner-related changes in data quality are common in medical imaging, yet monitoring their impact on diagnostic AI performance remains challenging. I...

Where are all the neurosurgery robots?

Despite substantial advances in engineering, robotics, and artificial intelligence, autonomous robots have yet to revolutionize neurosurgery. In this ...

An Appraisal of the Quality of Development and Reporting of Predictive Models in Spine Surgery.

Study DesignLiterature review.ObjectiveThe Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) st...

Machine Learning-Based Rupture Risk Prediction for Intracranial Aneurysms: A Systematic Review and Meta-Analysis.

BACKGROUND AND OBJECTIVES: Aneurysm risk prediction remains an imprecise science that places patients at risk for either over or undertreatment. Machi...

Enhancing precision in aneurysm volume measurement: A comparative study of techniques including an artificial intelligence-based method for endovascular coiling.

BACKGROUND: Durable occlusion after endovascular coiling can be compromised by recanalization, underscoring the need for accurate cerebral aneurysm as...

Comparison of quality, empathy and readability of physician responses versus chatbot responses to common cerebrovascular neurosurgical questions on a social media platform.

BACKGROUND: Social media platforms are utilized by patients prior to scheduling formal consultations and also serve as a means of pursuing second opin...

A Joint Geometric Topological Analysis Network (JGTA-Net) for Detecting and Segmenting Intracranial Aneurysms.

OBJECTIVE: The rupture of intracranial aneurysms leads to subarachnoid hemorrhage. Detecting intracranial aneurysms before rupture and stratifying the...

Integration of machine learning and bulk sequencing revealed exosome-related gene FOSB was involved in the progression of abdominal aortic aneurysm.

BACKGROUND: Abdominal aortic aneurysm (AAA), characterized by the pathological dilation of the abdominal aorta, was associated with immune response an...

Transforming Neurosurgical Practice with Large Language Models: Comparative Performance of ChatGPT-Omni and Gemini in Complex Case Management.

BACKGROUND: Recent advancements in artificial intelligence, particularly in large language models (LLMs), have catalyzed new opportunities within medi...

Multi-centric AI Model for Unruptured Intracranial Aneurysm Detection and Volumetric Segmentation in 3D TOF-MRI.

The aim of this study was to develop an open-source nnU-Net-based AI model for combined detection and segmentation of unruptured intracranial aneurysm...