Episode Details

We unpack the FDA 510(k) clearance summary for Viz Subdural+, an AI tool designed to automatically label and measure collections in the subdural space from brain CT scans. Listeners will learn how the algorithm performed in retrospective testing, how it compares to its predicate device, and what its limitations mean for hospitals buying AI.

Key points

• Viz Subdural+ is cleared for the automatic labeling, visualization, and quantification of subdural collections and midline shift from non-contrast CT scans.
• The software operates in the background, analyzing images automatically and sending summary and segmentation series to a DICOM destination like a PACS.
• In a retrospective study of 203 cases, the AI achieved a mean DICE score of 73% for subdural collection volume, with a mean absolute error of 7.53.
• The testing showed significant variability, with a volume standard deviation of 13.91, highlighting why the FDA requires physician review of the outputs.
• The algorithm was cleared based on substantial equivalence to the Viz HDS predicate device, expanding capabilities from intracranial hyperdensities to subdural collections.
• The performance data is based on a limited data set from only two clinical sites, which may impact generalizability across different hospital systems.

Source: FDA 510(k) summary K250354: Viz Subdural+, Viz SUBDURAL PLUS (Viz.ai) - U.S. Food and Drug Administration, 2025

This episode is an AI-generated conversation summarising a public document; the hosts' voices are synthetic. It is for information only and is not medical advice. Always refer to the original source.

Full transcript: https://ai-in-medicine-podcast.vercel.app/episodes/company-spotlight-viz-ai-viz-subdural-quantifying-brain-scans-with-ai-59b5b6