Arterys Introduces First Complete AI- and Cloud-powered Solution for Most Challenging Medical Imaging Analysis Workflow

Cardio AI(MR) Web-Based Image Analysis Solution Leverages Power of Deep Learning and Cloud Supercomputing for Improved Radiologist Efficiency and Rapid Analysis of Cardiac Mr Images

Arterys, the leader in intelligent, cloud-based medical imaging software, has introduced more than 80 enhancements to its Cardio AI solution, which combines the power of deep learning and cloud computing to automate analysis of cardiac MR images. With these additions, Arterys Cardio AI^MR is the first and only commercial solution to offer deep learning-based perfusion* and delayed enhancement analysis*. The new features also improve clinician workflow, streamlining and speeding analysis with automated and easily editable ventricular volume measurements.

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“The Arterys Cardio AI^MR innovations are game changers in data-driven medicine,” said Arterys CEO Fabien Beckers. “With Cardio AI^MR we are creating a growing base of collective intelligence that enables clinicians to eliminate tedious manual tasks, and quickly and easily detect, predict and track heart problems.”

Recent enhancements to Arterys Cardio AI^MR include support of:

• Quantitative Delayed Enhancement – Deep learning-based segmentation of myocardium and identification of reference points. Users can obtain scar quantification and extent enhancement on a 17-segment AHA plot.
• Semi-Quantitative Perfusion – Deep learning-based segmentation of myocardium, identification of reference points and co-registration. Users can simply create a blood pool ROI to obtain signal intensity graphs and semi-quantitative values, such as upslope and time to peak, on a 17-segment AHA plot.

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“Arterys Cardio AI^MR is a powerful tool that leverages deep learning to automate both routine analysis and some advanced capabilities, such as the quantification of total delayed enhancement mass of the left ventricle — a crucial finding for prognosis of diseases like hypertrophic cardiomyopathy,” said Arshid Azarine, MD, head of Cardiovascular Imaging, Department of Radiology at Saint Joseph Hospital, Paris. “Before Cardio AI^MR, these measurements were so time consuming that we considered them impossible in our routine practice and workflow. But now the process is automated, enabling more detailed measurements and requiring minimal corrections.”

“The Arterys solution enables our team to spend less time with the post processing, supporting greater efficiency and arming us with new, and more detailed, information,” added Dr. Azarine. “Review of some complex cardiac MR cases that once took an hour or longer with manual processing, can now be done in as little as 10-15 minutes. Thanks to powerful cloud computing, we gain more time to address our patients’ needs, and can more easily collaborate on their care with colleagues and experts around the world.”

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