Keywords: Analysis/Processing, Diagnosis/Prediction
Motivation: Left ventricular function is a strong predictor of survival, but atrial function is less well understood.
Goal(s): Assessing atrial function is time-consuming and labour-intensive, requiring manual tracing of the atrial borders frame-by-frame.
Approach: We developed an artificial intelligence tool capable of automating this process and can run on scanners in real time.
Results: We found that the proportion of blood ejected by the left atrium with each beat (left atrial ejection fraction) strongly predicts survival in a large cohort of patients, beyond and incremental to similar established left ventricular measures.
Impact: Atrial function measured automatically using inline AI is a strong and incremental predictor of patient survival. This enables new biomarkers to be easily translated into clinical workflow for improved patient care.
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