BACKGROUND: Large-vessel vasculopathy (LVV) increases stroke risk in pediatric sickle cell disease beyond the baseline elevated stroke risk in this vulnerable population. The mechanisms underlying this added risk and its unique impact on the developi...
OBJECTIVES: Artificial intelligence (AI) software including Brainomix "e-CTA" which detect large vessel occlusions (LVO) have clinical potential. We hypothesized that in real world use where prevalence is low, its clinical utility may be overstated.
Purpose To develop a deep learning model for the morphologic measurement of unruptured intracranial aneurysms (UIAs) based on CT angiography (CTA) data and validate its performance using a multicenter dataset. Materials and Methods In this retrospect...
Background Deep learning (DL) could improve the labor-intensive, challenging processes of diagnosing cerebral aneurysms but requires large multicenter data sets. Purpose To construct a DL model using a multicenter data set for accurate cerebral aneur...
BACKGROUND: Artificial intelligence (AI) models in real-world implementation are scarce. Our study aimed to develop a CT angiography (CTA)-based AI model for intracranial aneurysm detection, assess how it helps clinicians improve diagnostic performan...
OBJECTIVE: Computed tomography angiography (CTA) is the most widely used imaging modality for intracranial aneurysm (IA) management, yet it remains inferior to digital subtraction angiography (DSA) for IA detection, particularly of small IAs in the c...
BACKGROUND: Cranial accelerometry is used to detect cerebral vasospasm and concussion. We explored this technique in a cohort of code stroke patients to see whether a signature could be identified to aid in the diagnosis of large vessel occlusion (LV...
Aneurysm size correlates with rupture risk and is important for treatment planning. User annotation of aneurysm size is slow and tedious, particularly for large data sets. Geometric shortcuts to compute size have been shown to be inaccurate, particul...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
Stroke is the fifth leading cause of death in the United States. Subarachnoid hemorrhage (SAH) is a type of stroke often caused by the spontaneous rupture of a cerebral aneurysm. About 30% of the SAH patients develop delayed cerebral ischemia (DCI) a...
OBJECTIVES: Anterior communicating artery (ACOM) aneurysms are the most common intracranial aneurysms, and predicting their rupture risk is challenging. We aimed to predict this risk using a two-layer feed-forward artificial neural network (ANN).