Neurosurgery

AneuSI: A software tool to isolate a region of interest in cerebral aneurysms from full geometrical models.

BACKGROUND AND OBJECTIVE: Modeling cerebral aneurysms using patient-specific geometries demands significant computational resources, particularly when analyzing large datasets or to retrieve training data for machine learning techniques. Smaller domains representing the aneurysm and nearby vasculature are preferred to reduce computational cost, but manual extraction of these regions introduces lim...

Exploratory comparative analysis of automated morphologic and perfusion features derived from one-stop computed tomography angiography and computed tomography perfusion in large unruptured intracranial aneurysms.

PURPOSE: To compare rupture-related signals captured by automatically extracted computed tomography angiography (CTA) morphologic features and threshold-based computed tomography perfusion (CTP) metrics in large unruptured intracranial aneurysms (UIAs), and to explore a parsimonious feature combination for rupture status. METHODS: This retrospective cohort included 60 patients with UIAs who underw...

AI for prognosis and treatment stratification in glioblastoma neurosurgery: a systematic review.

BACKGROUND: Glioblastoma (GBM) remains one of the most lethal adult primary brain tumors, and neurosurgical decision-making increasingly depends on in...

Practical pathways for evaluating artificial intelligence in intracranial aneurysm detection.

Global gender representation in neurointerventional surgery: a natural language processing analysis of journal publications.

BACKGROUND: Despite increased awareness of diversity and inclusion in neurointerventional surgery, the representation of women in neurointerventional ...

Heterogeneity of Clazosentan Benefit after Aneurysmal Subarachnoid Hemorrhage Demonstrated in an Externally Validated Causal Policy Tree.

BACKGROUND: Clazosentan reduces angiographic vasospasm after aneurysmal subarachnoid hemorrhage (aSAH), but functional benefit may vary across patient...

Time-to-event ensemble machine learning approach for predicting long-term survival of abdominal aortic aneurysm patients undergoing endovascular aneurysm repair.

BACKGROUND: Endovascular aneurysm repair (EVAR) for abdominal aortic aneurysm (AAA) is associated with risks such as endoleaks and late aneurysm ruptu...

A CLIP-based framework for multiclass lung histopathology classification with prompt engineering and class-imbalance-aware focal optimization.

Lung cancer remains one of the leading causes of cancer-related mortality worldwide, and accurate histopathological classification is essential for ti...

Identifying Unmonitored Tone Drift in Patient Education Materials Transcribed to a Lower Reading Level by a Large Language Model.

BACKGROUND AND OBJECTIVES: Effective patient education is essential in neurosurgery, but many materials exceed recommended readability levels, which c...

Preoperative hypoalbuminemia predicts early complications, mortality, and discharge disposition following surgical resection of spinal metastases: a nationwide study.

PURPOSE: Patients undergoing surgery for spinal metastases often have limited physiologic reserve. Although hypoalbuminemia is a recognized risk marke...

ACADM-mediated fatty acid β-oxidation pathway in atherosclerosis and abdominal aortic aneurysm.

BACKGROUND AND AIMS: Atherosclerosis (AS) and abdominal aortic aneurysm (AAA) are both metabolism-associated vascular diseases, yet the role of lipid ...

Application of Focused Ultrasound in Alzheimer's Disease: A Bibliometric Analysis.

OBJECTIVE: This study uses bibliometric analysis and knowledge mapping methods to systematically explore the emerging research frontiers and developme...

Diagnostic performance of machine learning models versus established risk stratification for intracranial aneurysm rupture: a systematic review and bivariate meta-analysis.

BACKGROUND: Machine learning (ML) models have been proposed to improve the discrimination of intracranial aneurysm rupture status beyond established c...

Study Design Differences and Temporal Morphology Bias in Intracranial Aneurysm Rupture Research: Toward Prospectively Validated Risk Models: An Umbrella Review.

BACKGROUND AND OBJECTIVE: Risk stratification for unruptured intracranial aneurysms largely relies on meta-analyses that synthesize heterogeneous prim...

Accuracy of machine learning in predicting recurrence risk of lumbar disc herniation after percutaneous endoscopic lumbar discectomy: a systematic review and meta-analysis.

BACKGROUND: Lumbar disc herniation (LDH) is a major cause of low back pain and radicular leg pain. Percutaneous endoscopic lumbar discectomy (PELD) is...

Beyond Broca and Wernicke: Epilepsy surgery in the language areas.

Epilepsy surgery in language areas is challenged by the intricacies of presurgical workup and surgical planning. In recent decades, the view of langua...

Utilization of artificial intelligence-based writing assistance in contemporary spine literature.

OBJECTIVE: With the advent of artificial intelligence (AI), scientific research and writing has benefitted from large language models to generate hypo...

Genome-Wide Association Study and Fine Mapping Uncover Key Genetic Loci and Credible Genes of Intracranial Aneurysm and Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND: Intracranial aneurysm (IA) is a common neurovascular disorder; rupture causes aneurysmal subarachnoid hemorrhage with high mortality. Desp...

Angioarchitectural features of hemorrhagic presentation of brain arteriovenous malformations: A multivariate and explainable machine learning study.

PURPOSE: Brain arteriovenous malformations (BAVM) pose a significant rupture risk, leading to morbidity and mortality. Identifying features associated...

Immersive spatial computing in neurosurgery.

PURPOSE: Immersive spatial computing technologies, including virtual reality (VR), augmented reality (AR), and mixed reality (MR), are increasingly ap...