Siemens Healthineers showcased works in progress and upcoming expansions of current products this weekend at the SNMMI 2019 Annual Meeting in Anaheim, California.
The functions behind the yet-to-be-released prototypes stem from the German-based company's greater emphasis on digital healthcare, and include teamplay, syngo Virtual Cockpit and a number of AI algorithms.
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Currently used to connect PACS systems to a cloud via a receiver software for fleet management, Siemens’ teamplay is undergoing development to provide the same capability for MI scanners. This type of connection will enable imaging users to receive and review protocols and dose information, as well as share images and information interactively, such as how a scanner is utilized, how many patients are used on it daily, downtime and uptime rates, and what types of scans are performed on it.
“The idea is that you will be able to view and compare protocols across different scanners. If there are multiple PET scanners connected to teamplay, you’ll be able to compare those protocols and optimize your fleets,” Katherina Swystun, marketing manager for Siemens Healthineers, told HCB News. “If you see one particular scan protocol is different from another, you’d be able to then optimize your fleet and share those protocols with one another, and distribute those protocols to other users.”
Another work in progress is the syngo Virtual Cockpit, which will help experienced technologists share information with their less experienced colleagues through remote video and audio in cases such as performing a specific scan.
Already introduced by Siemens for MR and CT, the next step is to supply it for PET, with the aim being to boost confidence and enhance workflow.
“You could have a centralized nuclear medicine technologist who is an expert at a scanner and they would be able to support other colleagues who are based at other locations with other scanners,” said Swystun.
In addition to teamplay and syngo Virtual Cockpit, Siemens showcased three new AI-POWERED prototypes, including PET-assisted reporting, which performs AI-based analysis to enable users to review and quantify lesions automatically, classify physiological and non-physiological uptake, and calculate total lesion glycolysis (TLG) and metabolic tumor volume; and MI whole-body analysis suite, which segments organs in the body automatically and can calculate organ-specific tumor burden as well as allow physiological uptake to be excluded based on organs. Both are designed for PET.
For the SPECT space, an algorithm is currently being designed to segment the lung so that users can automatically locate and contour the lungs.
“It would segment left and right lung lobes, and enable automatic quantification for ventilation and perfusion,” said Swystun.
The works shown are currently under development and not available for sale yet.