Imaging studies for predicting hematoma expansion: from traditional imaging signs to artificial intelligence-based multimodal fusion - Scorecard - MDSpire
Advertisement
Imaging studies for predicting hematoma expansion: from traditional imaging signs to artificial intelligence-based multimodal fusion
Clinical Scorecard: Advancements in Imaging Techniques for Forecasting Hematoma Expansion: Transitioning from Conventional Indicators to AI-Enhanced Multimodal Approaches
At a Glance
Category
Detail
Condition
Hematoma Expansion (HE)
Key Mechanisms
Traditional imaging markers and AI-driven methodologies for predicting HE.
Target Population
Patients with acute intracerebral hemorrhage (ICH).
Care Setting
Clinical practice and future research in stroke management.
Key Highlights
HE is a critical and modifiable event following acute ICH.
Approximately 20–30% of patients experience HE within 24 hours of onset.
Revised hematoma expansion (rHE) includes intraventricular hemorrhage growth.
Ultraearly hematoma growth (uHG) emphasizes the rate of bleeding.
AI-driven methods outperform traditional imaging markers.
Guideline-Based Recommendations
Diagnosis
Utilize traditional imaging markers such as CTA spot sign and NCCT signs.
Management
Prevent HE through blood pressure control, coagulation correction, or hemostatic agents.
Monitoring & Follow-up
Monitor for signs of HE using both traditional and AI-enhanced imaging techniques.
Risks
HE is associated with early neurological deterioration, disability, and increased mortality.
Patient & Prescribing Data
Patients with acute ICH at risk of hematoma expansion.
Targeted interventions based on accurate prediction of HE.
Clinical Best Practices
Incorporate multimodal data fusion for individualized HE prediction.
Adopt revised HE (rHE) as a primary outcome measure in clinical assessments.
Utilize uHG for ultra-early risk stratification and treatment decisions.
