Artificial Intelligence in Acute Ischemic Stroke Subtypes According to Toast Classification: A Comprehensive Narrative Review.
Giuseppe MiceliMaria Grazia BassoGiuliana RizzoChiara PintusElena CocciolaAndrea Roberta PennacchioAntonino TuttolomondoPublished in: Biomedicines (2023)
The correct recognition of the etiology of ischemic stroke (IS) allows tempestive interventions in therapy with the aim of treating the cause and preventing a new cerebral ischemic event. Nevertheless, the identification of the cause is often challenging and is based on clinical features and data obtained by imaging techniques and other diagnostic exams. TOAST classification system describes the different etiologies of ischemic stroke and includes five subtypes: LAAS (large-artery atherosclerosis), CEI (cardio embolism), SVD (small vessel disease), ODE (stroke of other determined etiology), and UDE (stroke of undetermined etiology). AI models, providing computational methodologies for quantitative and objective evaluations, seem to increase the sensitivity of main IS causes, such as tomographic diagnosis of carotid stenosis, electrocardiographic recognition of atrial fibrillation, and identification of small vessel disease in magnetic resonance images. The aim of this review is to provide overall knowledge about the most effective AI models used in the differential diagnosis of ischemic stroke etiology according to the TOAST classification. According to our results, AI has proven to be a useful tool for identifying predictive factors capable of subtyping acute stroke patients in large heterogeneous populations and, in particular, clarifying the etiology of UDE IS especially detecting cardioembolic sources.
Keyphrases
- artificial intelligence
- atrial fibrillation
- deep learning
- machine learning
- big data
- left atrial
- magnetic resonance
- oral anticoagulants
- catheter ablation
- left atrial appendage
- direct oral anticoagulants
- healthcare
- high resolution
- convolutional neural network
- heart failure
- liver failure
- type diabetes
- percutaneous coronary intervention
- cardiovascular disease
- electronic health record
- cerebral ischemia
- magnetic resonance imaging
- optical coherence tomography
- intensive care unit
- stem cells
- coronary artery disease
- acute respiratory distress syndrome
- left ventricular
- computed tomography