The combination of artificial intelligence (AI) and a new noninvasive cardiac imaging technique can perform comparably to current imaging tests used to detect coronary artery disease (CAD) - without requiring cardiac stress, contrast agents, or radiation exposure
This machine-learning algorithm analyzes cardiac phase space tomography (CPST) - a novel imaging method that uses a handheld instrument to capture the heart's resting phase signals. In testing, the algorithm was more than 90% sensitive for diagnosing significant CAD.
To train the algorithm to analyze the unique features associated with flow-limiting CAD, mathematical and tomographic features were extracted from the phase data and paired with the angiography results. The algorithm was trained using data from 512 subjects and then prospectively tested on the remaining 94 participants.