PeekMed web

PeekMed web is a cloud-based software system designed to help healthcare professionals perform pre-operative surgical planning for orthopedic procedures (hip, knee, upper limb, and foot surgeries) in adult patients. The system imports patient medical imaging studies, allows interactive 2D and 3D visualization, measurement, and positioning of digital prosthetic material templates, and generates a final planning report. Clinical judgment and experience are required for proper use.

PeekMed web is a distributed cloud-based system with the same architecture, workflow, and functional capabilities as its predicate (K222767). Key differences in the subject device include: expanded anatomical coverage to include foot surgery planning (in addition to hip, knee, and upper limb); updated and improved machine learning model variants for bone segmentation, landmarking, and classification; and enhanced ML model performance validated against acceptance criteria. All other features—image processing, digital template overlap, interactive positioning and dimensioning, and output validation—remain equivalent.

Not stated in this summary. The document references internal acceptance criteria for ML models (DICE ≥90%, HD-95 ≤8, MRE ≤7mm, Accuracy ≥90%) but does not cite external consensus standards such as ISO, IEC, or ASTM.

Substantial equivalence is established because the subject device shares identical intended use, indications for use, end-user population (healthcare professionals), patient population (adults), clinical purpose, workflow, and core technical architecture with the predicate device K222767. Both are decision support tools for orthopedic pre-surgical planning using medical imaging in a cloud-based environment. The main differences—expanded foot anatomy support and improved ML models—do not raise new safety or performance questions because: (1) foot surgery planning uses the same development, verification, validation, and release processes as existing anatomical regions; (2) ML model improvements were validated using rigorous testing against predefined acceptance criteria and external validation datasets; and (3) these enhancements improve device capability without affecting other anatomical regions or core functionality.