In Artificial Intelligence at RSNA 2019, ITN Contributing Editor Greg Freiherr offers an overview of artificial intelligence (AI) advances at the Radiological Society of North America (RSNA) 2019 annual meeting.
Technology Report: Artificial Intelligence 2019
While electronic medical record systems have helped consolidate most patient data into one location, medical imaging IT systems has proved to be more difficult to replicate by large EMR vendors. This has made room in the market for third-party radiology information system vendors that allow easy integration with the larger EMRs like Epic and Cerner. This image shows Agfa's enterprise imaging system, leveraging its ability to be accessed anywhere with an internet connection and able to pull in images from both radiology and surgery.
This image is of an 80 kg woman with a newly diagnosed IDH-wildtype glioblastoma. The quarter dose image on the left was obtained after the administration of 4 ml of MultiHance. Subsequently, an additional 12 ml of MultiHance was administered and the cumulative full dose image in the center was obtained. The image on the right was rendered following artificial intelligence processing of the 4 ml image using eGad genetic algorithms. This image has the quality of triple dose gadolinium even though only one quarter dose gadolinium was given.