Neurosurgery

Pfirrmann Grading and Features of Internal Derangement Identified in Discs Studied By Lumbar Discography in Patients with Chronic Low Back Pain.

BACKGROUND AND PURPOSE: Lumbar disc degeneration Pfirrmann Grade (PfGr) is commonly used to evaluate clinical studies assessing patient outcomes or evolving MR imaging sequences. To our knowledge the association between the features of annular internal derangement and PfGr has not been evaluated. This study's purpose was to compare disc PfGr to the observed internal derangement features identified...

From Static Diagnosis to Dynamic Guidance : Evolution of Artificial Intelligence in Pediatric Neuroimaging.

The pediatric brain represents a dynamic biological target characterized by rapid myelination and functional reorganization, which presents unique challenges for conventional, adult-centric artificial intelligence (AI) models. This review provides a structured overview of the evolution of AI applications in pediatric neuroimaging and neurosurgery, tracing the transition from early standardized pip...

Preface : Digital and Robotic Transformation of Pediatric Neurosurgery.

This Pediatric Issue of the Journal of Korean Neurosurgical Society addresses the digital and robotic transformation of pediatric neurosurgery. It rev...

AI-driven navigated hematoma aspiration vs. conservative treatment for spontaneous intracerebral hemorrhage: study protocol for a randomized controlled trial.

BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) remains one of the most devastating types of stroke, with high mortality and long-term disabili...

Development and External Validation of a Deep Learning Model to Predict Mortality in Aneurysmal Subarachnoid Hemorrhage Using Admission Computed Tomography.

BACKGROUND AND OBJECTIVES: Traditional prognostication after aneurysmal subarachnoid hemorrhage depends on subjective clinical grading and radiologica...

Unlocking the mind: brain mapping for the exploratory quest of functional and cognitive networks in awake neurosurgery.

This retrospective study investigated the efficacy of intraoperative brain stimulation in 18 awake patients undergoing resection of intracranial lesio...

Single-Cell Profiling Identifies CLEC5A+ Macrophages as Key Drivers of Thoracic Aortic Aneurysm Via CCL5-Mediated M1 Polarization.

BACKGROUND: Thoracic aortic aneurysm (TAA) is a life-threatening disease with limited therapeutic options, largely due to an incomplete understanding ...

Mammography-based artificial intelligence model for predicting axillary lymph node status after neoadjuvant therapy in breast cancer.

OBJECTIVES: Our objective is to develop a deep learning-based artificial intelligence (AI) model capable of analyzing digital mammography (DM) images ...

AI-Powered Pipeline Transforms Neurosurgical Articles Into High-Quality Graphical Abstracts.

BACKGROUND AND OBJECTIVES: Neurosurgery Publications encourages the creation of graphical abstracts to accompany published articles. The goal of this ...

Development and validation of a deep learning radiomics model for predicting adjacent segment degeneration following anterior cervical discectomy and fusion.

Low-field strength MRI (0.55T) for stereotactic and functional neurosurgery using deep learning-based reconstruction algorithm: Preliminary experiences.

BACKGROUND: There has been a trend toward exclusive use of high MRI field strength (1.5 T or above) for stereotactic neurosurgery imaging. However, lo...

Enhancing Readability of Surgical Patient Education Resources Using ChatGPT.

INTRODUCTION: Patient education materials are essential for informed decision-making. However, their readability often exceeds the sixth-grade reading...

Extended Reality in Neurosurgery : Surgical Planning, Navigation, Education, and Patient Communication.

Extended reality (XR), encompassing virtual reality (VR), augmented reality (AR), and mixed reality (MR), has emerged as a transformative technology i...

An Emerging Role of Artificial Intelligence in Pediatric Neuroanesthesia.

Anesthesia for pediatric neurosurgery represents a highly complex and challenging field, characterized by age-dependent physiological variability, het...

Artificial intelligence-based detection of acute postoperative airway complications following anterior cervical spine surgery: a retrospective imaging evaluation.

STUDY DESIGN: Retrospective imaging evaluation using an artificial intelligence (AI)-generated model. PURPOSE: To develop novel AI software for early ...

Generation of virtual abdominal aortic aneurysm shape evolution using a physics-based G&R model and its applications to aneurysm growth prediction.

The computational growth and remodeling (G&R) of aortic aneurysms has been extensively investigated to better understand vascular disease progression ...

Large language models in artificial intelligence to answer patient questions in spine surgery: an evaluation of current evidence.

INTRODUCTION: Large language models (LLMs) are increasingly being explored in healthcare, particularly for enhancing patient education. In spine surge...

Neurosurgical Application of Artificial Intelligence in Pediatric Neuro-Oncology.

Pediatric neuro-oncology is a critical field of neurosurgery, representing the leading cause of disease-related mortality in children. Despite its rar...

AI-Guided 4D Printing of Carnivorous Plants-Inspired Microneedles for Accelerated Wound Healing.

Artificial intelligence (AI) integrated with bioinspired design enables the development of materials that adapt and dynamically respond to biological ...

Multiphysics learning with graph neural networks for thrombosis prediction in intracranial aneurysms.

Intracranial aneurysms are pathological dilations of cerebral arteries affecting 3-5% of the population. Their rupture can cause subarachnoid hemorrha...