CT-Based Analysis Platform Detects Brain Bleeds

The software app uses non-contrast CT images and processes them in the cloud, using proprietary algorithms that note changes and highlight suspicious, potential areas of bleeding. The enhanced images are sent back to the doctor’s workstation, together with the original CT scan.

The algorithms were developed using deep learning (DL) and billions of images from millions of cases acquired through collaborations with hospitals such as Hadassah Medical Center (Jerusalem, Israel) and Massachusetts General Hospital (Boston, MA, USA). By analyzing multiple series of images, the Accipio Ix algorithm learned what an ICH looks like and set benchmarks for baseline readings. Using the platform, emergency healthcare providers can prioritize clinical assessment and care of patients with hemorrhagic stroke or intracranial trauma within three to five minutes.

“MaxQ’s Accipio application, of which Accipio Ix is the first part of the ecosystem, provides physicians with actionable intelligence, improving their future ability to make a timely, accurate, and confident diagnosis of a brain bleed,” said Gene Saragnese, chairman and CEO of MaxQ AI. “The Accipio line is designed to be integrated with most existing medical workflow platforms and imaging technologies, including CT, MRI and ultrasound, both locally and on cloud-based servers.”

MaxQ has announced partnerships with IBM Watson and Samsung NeuroLogica to integrate its products into their radiology software and hardware platforms. Samsung NeuroLogica plans to use the software in mobile stroke units equipped with its CereTom CT scanner to allow staff to differentiate between ischemic strokes and hemorrhagic strokes in the field, and allow them to give clot busters while en-route to the hospital. The company also signed a five-year distribution deal with GE Healthcare in November 2017.

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