Search Results

The Smith & Nephew Image Guided Surgical System for Knee Applications is indicated for use in total knee procedures, including but not limited to, primary and revision total knee arthroplasty and unicompartmental knee arthroplasty, in which the use of stereotactic surgery may be appropriate, and where a reference to a rigid anatomical structure, such as a long bone can be identified relative to a CT or MR based model or fluoroscopy images of the anatomy.

The Smith & Nephew Image Guided Surgical System for Knee Applications is intended to assust the surgeon in precisely locating anatomical structures in either open or percutaneous procedures. The Smth & Nephew Image Guided Surgical System for Knee Applications uses image-guided arrays to transmit or reflect infrared LEDs (light emitting diodes) that are emitted by an IGS Platform System. Thus allows the instruments to be recognized and tracked in real time in the surgical field.

The provided text does not contain detailed information about the acceptance criteria or a specific study proving the device meets those criteria. The submission is a 510(k) summary for the "Smith & Nephew Image Guided Surgical System for Knee Applications," which focuses on establishing substantial equivalence to previously cleared devices rather than presenting a performance study with detailed acceptance criteria.

However, based on the provided text, we can infer some general information about the device and its regulatory context:

1. Table of Acceptance Criteria and Reported Device Performance:

No specific numerical acceptance criteria or performance metrics are provided in the document. The filing relies on the concept of "substantial equivalence."

2. Sample Size Used for the Test Set and Data Provenance:

The document does not detail a specific "test set" or its sample size for a performance study. The statement "Performance data was provided to support the claim of substantial equivalence" suggests that some form of data was analyzed, but the specifics of that data (e.g., number of cases, retrospective/prospective, country of origin) are not disclosed in this summary.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:

This information is not provided. Since the submission focuses on substantial equivalence, there is no mention of a ground truth established by experts for a specific test set.

4. Adjudication Method for the Test Set:

This information is not provided.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done:

No, there is no mention of an MRMC comparative effectiveness study that assesses how much human readers improve with AI vs. without AI assistance. The device is an image-guided surgical system, not a diagnostic AI tool for human readers.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done:

The document does not detail a standalone performance study. The device is described as an "Image Guided Surgical System for Knee Applications" that "assists the surgeon," implying that it is a human-in-the-loop system designed to be used by a surgeon.

7. The Type of Ground Truth Used:

The document does not explicitly state the type of ground truth used as it does not detail a specific performance study with a test set. For image-guided surgical systems, ground truth often involves highly accurate measurements of instrument tip position relative to anatomical landmarks, verified by external tracking systems or highly precise imaging techniques. Given the reliance on substantial equivalence, the "ground truth" for showing equivalence would be the established performance and safety profiles of the predicate devices.

8. The Sample Size for the Training Set:

This information is not provided. The document does not mention any machine learning or AI models with distinct training sets. The "Image Guided Surgical System" uses infrared LEDs to track instruments, suggesting a hardware and software system for navigation, not necessarily one that would typically involve a "training set" in the context of deep learning.

9. How the Ground Truth for the Training Set Was Established:

This information is not provided, as there is no mention of a training set.

Ask a specific question about this device