Shimadzu Medical Systems USA introduced the new Trinias system, which uses artificial intelligence deep learning to improve the visibility of medical devices while using lower X-ray doses than previous models, at the Society of Interventional Radiology Annual Meeting (SIR 2022; 11–16 June, Boston, USA).
This is the first time AI has been incorporated into the image-processing engine of an angiography system, the company declared in a press release.
The new Trinias system also offers an extensive new feature set to simplify workflow, allowing a more efficient clinical operation in any medical setting, the company reported. Shimadzu has also launched a subscription service that ensures software can always be updated to the current version, making the Trinias system a more sustainable product designed for long-term use.
Angiography systems are used to perform angiographic examinations, where the physician inserts a catheter through a blood vessel in the patient’s wrist or inguinal region to a specific site and observes an area of disease or concern, and to perform catheterisation procedures, where a therapeutic device is inserted in the patient and used to dilate blood vessels or perform other interventional procedures.
Medical facilities are increasingly operating angiography systems at low radiation levels to reduce X-ray doses, but low radiation levels also lead to X-ray noise that reduces device visibility. To support the low-dose operation of angiography systems by medical facilities and ever-smaller therapeutic devices that reduce the burden on patients, Shimadzu has developed SCORE Opera, a new image-processing technology that uses AI to ensure catheterisation procedures are safe even at low radiation doses.