System and Method for Medical Image Based Cardio-Embolic Stroke Risk Prediction

An apparatus for medical image based patient-specific stroke risk prediction, comprising:

• means for extracting left atrium (LA) and left atrium appendage (LAA) measurements from medical image data of a patient;
• means for computing derived metrics for the LA and LAA of the patient using a patient-specific computational model of cardiac function based on the LA and LAA measurements extracted from the medical image data of the patient;
• and
• means for calculating a stroke risk score for the patient based on the extracted LA and LAA measurements and the computed derived metrics for the LA and LAA of the patient using a trained machine learning based classifier, wherein the extracted LA and LAA measurements and the computed derived metrics for the LA and LAA are input as features to the trained machine learning based classifier.

A non-transitory computer readable medium storing computer program instructions for medical image based patient-specific stroke risk prediction, the computer program instructions when executed by a processor cause the processor to perform operations comprising:

• extracting left atrium (LA) and left atrium appendage (LAA) measurements from medical image data of a patient;
• computing derived metrics for the LA and LAA of the patient using a patient-specific computational model of cardiac function based on the LA and LAA measurements extracted from the medical image data of the patient;
• and
• calculating a stroke risk score for the patient based on the extracted LA and LAA measurements and the computed derived metrics for the LA and LAA of the patient using a trained machine learning based classifier, wherein the extracted LA and LAA measurements and the computed derived metrics for the LA and LAA are input as features to the trained machine learning based classifier.