Software developer Ziosoft is highlighting research using its Ziostation2 advanced visualization platform to reduce reading times for CT coronary artery calcium (CAC) scoring scans, presented last week at the Society of Cardiovascular Computed Tomography (SCCT) meeting in Baltimore.
The researchers used artificial intelligence (AI) algorithms within the Ziostation2 platform to supplement manual CT CAC scoring for patients at Advocate Lutheran General Hospital and Advocate Research Institute in Illinois. The clinically validated algorithms are capable of preprocessing CT CAC scans, reformatting them, and transmitting relevant results directly to PACS, according to the company.
Ultimately, incorporating these algorithms into CT CAC evaluation led to a 50% reduction in reading time, the researchers noted.
"We found that AI CAC scoring improved to high reliability and high accuracy when used in combination with manual readings ... [resulting in] significant reduction in manual reading time, which can equate to substantial efficiency improvement," presenter Dr. Edward Passen said in a statement.
