AI System To Detect Calcium Buildup In Arteries

The platform was designed to help identify heart disease in order to start patients on treatment plans before a coronary event occurs, which is a substantial step forward to current trends in which up to half of the patients are not even aware that they have cardiovascular disease until they experience their first unfortunate cardiac event. 

According to the company, coronary artery calcium scoring is a major indicator of heart disease, studies show a strong correlation between these levels and the severity of the disease; those with the highest levels of calcium build up in their arteries may be more than 20 times more likely to experience a cardiac event. 

Typically cardiac-gated CT scans are used to measure calcium scoring, this is also where electrocardiograms monitor heart rates throughout the scanning process. This platform, according to the company, analyzes existing non-gated CT scans which require less radiation exposure than gated scans and are less costly, representing 2 potential benefits. The AI software will then place patients into one of three categories to indicate the severity of cardiovascular disease after calculating the amount of calcium buildup from the imaging data.

This machine-learning algorithm is suggested to be a stronger predictor of CVD incidence and mortality than the current standard of manually calculating the risk in a retrospective analysis involving over 12,000 participants in the National Lung Screening Trial; with the study concluding the software further outperformed manual prediction by being fully automated allowing for better time management and assessment of more potential risk factors being analyzed at the same time. 

This biotech gained its first FDA clearance for an AI algorithm in July 2018 for another calcium scoring tool which was able to automatically calculate the amount of buildup from gated CT scans. Since then this company has been gaining other clearances for other AI systems that are designed to calculate bone measurements from X-rays, detect potentially cancerous lesions in mammograms, detection of pneumothorax, and detection of pleural effusion in chest scans among other platforms. 

All of these advances gained the company much attention, most specifically from digital X-ray machine maker Nanox which led to the decision to acquire Zebra Medical in a $200 million deal providing Zebra Medical with half of the money right away and the rest paid out at certain milestones. The AI algorithms will now be embedded into Nanox’s digital X-ray systems which will now be able to collect, process, and analyze imaging data all within the same platform. 

“We understand that in order to truly lead and shape this new AI-enabled diagnostic space, we’ll need both the superb hardware capabilities and coming install base, which Nanox delivers, and the AI and cloud delivery capabilities, combined with proven regulatory and quality framework, which Zebra Medical Vision has built over seven years,” said Eyal Gura, co-founder of Zebra Medical Vision.