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510(k) Data Aggregation
(406 days)
The Longeviti Static Cranial Implants are designed and manufactured individually for each patient to correct bony voids and/or defects of the cranium.
The Longeviti PMMA Static Cranial Implants are patient specific, implantable prosthetic cranioplasty plates intended to correct and/or restore bony voids and/or defects of the cranium. The implants are manufactured from polymethyl methacrylate materials and are designed using the patient's CT scan data. The devices are provided sterile and can be fixated to cranial bone using commercially available fasteners. Typical maximum single plate sizes do not exceed a total surface area of 411 cm2 and should have a nominal thickness of 4mm, not to exceed 5mm, to ensure physical integrity.
The provided documents are a 510(k) Premarket Notification from the FDA to Longeviti Neuro Solutions, LLC for their Longeviti PMMA Static Cranial Implant. This document does not contain information about an AI/ML-driven medical device or any study proving a device meets acceptance criteria related to AI/ML performance.
The content focuses on:
- Substantial Equivalence: The FDA's determination that the Longeviti PMMA Static Cranial Implant is substantially equivalent to legally marketed predicate devices (OsteoSymbionics Patient Specific Cranial Plate K133082 and OsteoSymbionics Patient Specific Cranial Implant K072601).
- Device Description: The device is a patient-specific, implantable prosthetic cranioplasty plate manufactured from polymethyl methacrylate (PMMA) materials using patient CT scan data.
- Indications for Use: To correct bony voids and/or defects of the cranium.
- Testing Summary: Primarily focused on sterilization validation (ISO-14937) and mechanical strength tests (ASTM D638-03, D790-03, D4812-06) to demonstrate material equivalence to the predicate device.
Therefore, I cannot fulfill your request as the provided text does not contain any of the information required to describe acceptance criteria or a study related to an AI/ML device's performance. There is no mention of an algorithm, AI, machine learning, test sets, ground truth establishment, expert review, MRMC studies, or standalone algorithm performance.
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