SubtlePET is currently in pilot clinical use in multiple university hospitals and imaging centers in the U.S. and abroad. “Focusing Subtle Medical’s SubtlePET AI platform on faster image acquisition, we have been able to dramatically increase PET scan efficiency and provide a superior patient experience. SubtlePET technology allows us to scan a patient four times faster than normal, yet maintain equal image quality, not otherwise impacting work flow,” said Michael Brant-Zawadzki, MD, FACR, Hoag Hospital, Newport Beach, California. “This creates immediate ROI benefit for our hospital and a compelling value proposition. I’m looking forward to seeing more groundbreaking technology from the Subtle team.”
Subtle Medical’s deep learning solution enables completion of more exams in a day compared to conventional PET imaging without the need for capital expenditures. It reduces patient time in the scanner and helps hospitals and imaging centers enhance their bottom line in today’s competitive healthcare environment. The company’s technology utilizes deep learning algorithms that integrate seamlessly with any OEM scanner and PACS system to enhance images during acquisition without any interruption or alteration in the imaging specialists’ workflow. SubtlePET delivers a significant improvement in the image quality of noisy images resulting from shorter scans, which is particularly beneficial for children and those undergoing repeat PET exams.
SubtlePET is the first product in Subtle Medical’s growing portfolio of new AI technologies to receive FDA clearance. “This FDA clearance is a key milestone in Subtle Medical’s mission to bring novel and empathetic deep learning to improve patient satisfaction,” said Enhao Gong, PhD, Founder and CEO of Subtle Medical. “The accomplishment of having the first AI cleared for use in nuclear medicine applications validates our team’s strength and the commitment of our collaborators. Our focus on image acquisition and workflow differentiates us from other AI companies that are working on post-processing and computer-aided diagnosis products. We are not replacing radiologists–we are addressing the tremendous cost to U.S. healthcare by leveraging deep learning in imaging at the infrastructure level to enable better and higher quality care.”