AI-Powered Software Aims to Achieve 6x Reduction in Radiation Dose of Fluoroscopy Exams

Subtle Medical, Inc. (Menlo Park, CA, USA) has been awarded an NIH SBIR grant to develop the AI-powered software, SubtleIR, in line with the company's mission to accelerate access to faster, safer, and smarter medical imaging. This is the second NIH SBIR grant awarded to Subtle. The first was for SubtleGAD, an AI-based software using deep learning to drastically reduce contrast dosage needed during contrast-enhanced medical imaging exams.

Fluoroscopy is a common tool for image-guided interventions in surgeries. The new software will potentially reduce radiation exposure in the operating room, minimizing the risk of cancer development for both patients and radiology staff. Subtle aims to enhance fluoroscopy videos acquired with up to 83% lower dose levels into videos with full-dose quality. This conversion will be performed in real-time, such that the surgeon can receive video feedback without delay while greatly reducing radiation exposure to both the patient and operating clinicians.

In addition, Subtle aims to optimize the processing speed of these DL models by leveraging various software and hardware accelerations for real-time application to achieve over a 30 fps processing rate, which will enable a seamless integration between video capture and subsequent display. Recent research on SubtleIR's technology was published at MICCAI showing a 4x dose reduction while providing equivalent or better video quality to the normal dosage level, as supported by quantitative metrics and surgeon review.

"Receiving this SBIR grant will allow us to meet the demand for new AI applications that support image guided therapy and surgeries. With this technology, hospitals and imaging centers will be able to deliver safer low-dose fluoroscopy exams without sacrificing the clinical quality of the images," said Enhao Gong, PhD, Co-founder & CEO. "We appreciate the NIH's support in the development of this novel AI product and look forward to deploying it in clinical settings."

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