Radiomics-Based Prediction of Collateral Status from CT Angiography of Patients Following a Large Vessel Occlusion Stroke.
Emily W AveryAnthony Abou-KaramSandra Abi-FadelJonas BehlandAdrian MakStefan P HaiderTal ZeeviPina C SanelliChristopher G FilippiJoseph SchindlerCharles C MatoukGuido J FalconeNils PetersenLauren H SansingKevin N ShethSeyedmehdi PayabvashPublished in: Diagnostics (Basel, Switzerland) (2024)
Automated tools for the assessment of collateral status from admission CTA-such as the radiomics models described here-can generate clinically relevant and reproducible collateral scores to facilitate a timely treatment triage in patients experiencing an acute LVO stroke.
Keyphrases
- end stage renal disease
- emergency department
- ejection fraction
- newly diagnosed
- chronic kidney disease
- peritoneal dialysis
- magnetic resonance
- machine learning
- squamous cell carcinoma
- magnetic resonance imaging
- liver failure
- deep learning
- contrast enhanced
- respiratory failure
- blood brain barrier
- brain injury
- patient reported