RapidAI, a health technology company that specializes in stroke imaging analysis, announced Tuesday that it has received FDA 510 (k) clearance for its product, which aims to identify potential cases of central pulmonary embolism and alerts.
The Rapid PE Triage & Notification tool analyzes CT pulmonary angiogram (CPTA) images and alerts the care team if a suspicious case is found, so that providers can try to care for patients.
Company, also known as According to the FDA’s database, iSchemaView now has six FDA 510 (k) clearances. It has a Rapid Aspects device that helps physicians detect brain injury and determine if a patient is eligible for thrombectomy.
“Based on our expertise in stroke, we are confident that this technology will help modernize PE care and significantly improve patient outcomes,” CEO Karim Karti said in a statement.
“Our goal is to develop solutions that address specific challenges related to the treatment of various conditions, as well as the communication and workflow issues facing hospitals across the globe. Excited to go. “
Why it matters
A pulmonary embolism is an obstruction in one of the pulmonary arteries of the lungs, which is often caused by blood clots forming from the veins in the legs.
The condition can be life-threatening. According to the Mayo Clinic, about one-third of people who have not been diagnosed and have untreated pulmonary embolism do not survive, but improve treatment outcomes, such as medication or blood clot removal.
There are many companies that focus on using artificial intelligence in imaging. Aidoc recently received FDA 510 (k) clearance To find out possible cases of pneumothorax flagging and trimming and another possible brain aneurysm. The company also has an FDA-clear tool for incidental pulmonary embolism.
In February, Viz.ai. Got a 510 (k) for its algorithm aimed at detecting brain aneurysms from CT scans. It scored a De Novo score in 2018 for its tool that analyzes CT results and highlights cases that could lead to a stroke.
However, with the proliferation of AI in healthcare and life sciences, some studies have raised concerns about bias and the need for rigorous testing. A Published in the study The Lancet Digital Health A deep-learning model could be trained to predict self-reported race from imaging results earlier this month, the results of which researchers wrote could make existing health inequalities permanent or worse.
Another one The Lancet An April study found that an algorithm used to detect hip fractures surpassed that of human radiologists, but further analysis found problems that would make it unsafe to use in new environments. Algorithms sometimes make the mistake that a person would find easy to explain.