Search Results

The Lens Integrated system and LENS Camera Head are used in diagnostic and operative procedures for arthroscopic and endoscopic procedures to provide illumination and capture of still and motion pictures of surgical sites within articular cavities, body cavities, hollow organs and canals.

Additionally, the LENS Integrated System and Camera Head are indicated for use in endoscopic surgical procedures in the thoracic cavity when used with an appropriately indicated thoracoscope.

The LENS Application, when used in conjunction with the LENS Integrated System WiFi version, is indicated for capture of still and motion pictures, patient file management and limited redundant control of the LENS camera control unit within articular cavities, body cavities, hollow organs, canals and the thoracic cavity.

The Smith & Nephew LENS Integrated System is an integrated camera/ LED light source/ image management device that provides visualization, illumination and image capture combined in a single console. The LENS Integrated System control units will be offered in two versions, Wi-Fi and Non-Wi-Fi. The LENS Integrated system works in conjunction with the LENS camera head, appropriate light guides, couplers and endoscopes.

The optional LENS application acts as a tool to remotely capture still and motion pictures, patient file management and limited redundant control of the LENS control unit wirelessly from the LENS camera system.

The application provides the ability to view and annotate by voice or graphics or to text captured patient data and sharing of patient data via a USB storage device, email, or printing to the local tablet camera roll. The application is downloaded from the Apple APP store to a surgeon's tablet.

The provided text is a 510(k) summary for the Smith & Nephew LENS Integrated System and LENS Camera Head. It outlines the device's characteristics, intended use, and comparison to predicate devices to establish substantial equivalence. However, it does not contain the detailed information necessary to complete the requested table and answer all questions regarding acceptance criteria and the study that proves the device meets them.

Specifically, the document states generally that "Bench testing was conducted to ensure that devices functioned as intended and met design specifications and acceptance criteria." It also mentions "light output testing, performance testing, thermal testing and ship testing." However, it does not provide:

• Specific acceptance criteria values (e.g., minimum light output intensity, specific performance metrics for image quality, thermal limits, etc.).
• Reported device performance values against those criteria.
• Details of the study methodology for these bench tests (sample sizes, ground truth establishment, expert involvement, etc.).

Therefore, many parts of your request cannot be answered from the provided text.

Here's what can be extracted and what is missing:

1. A table of acceptance criteria and the reported device performance:

2. Sample size used for the test set and the data provenance: Not specified in the text. The document refers to "bench testing" generally, without detailing specific test sets or sample sizes used for performance validation. Data provenance (country of origin, retrospective/prospective) is also not mentioned.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not specified. As the document mainly describes bench testing for technical specifications (light output, thermal, performance of hardware/software), there's no indication of clinical expert involvement for establishing "ground truth" in the way it would be for a diagnostic AI device analyzing medical images.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable based on the information provided. This type of adjudication is typically for clinical studies involving human interpretation or performance, which is not detailed here for the "bench testing."

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance: Not applicable. The device described is an endoscope camera system, not an AI-assisted diagnostic tool that would typically involve human readers and MRMC studies. There is an "optional LENS application" that acts as a tool to remotely capture images and manage patient files and provide limited redundant control, but it's not presented as an AI for diagnostic improvement.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: The document describes the system as an "integrated camera/ LED light source/ image management device." The "LENS application" is described as a tool for remote capture, management, and control. This implies a human-in-the-loop system, as the camera is used by a surgeon. No "standalone algorithm" performance is discussed.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): For the bench testing, the "ground truth" would be the engineering specifications and design requirements (e.g., a light output sensor measuring a specific lumen value, a thermal sensor reading a specific temperature). No clinical ground truth (expert consensus, pathology, outcomes) is mentioned for the performance testing.

8. The sample size for the training set: Not applicable. The device is a camera system, not an AI algorithm that would typically involve a "training set" in the context of machine learning. The software development follows a life cycle process, not an AI training paradigm.

9. How the ground truth for the training set was established: Not applicable for the reasons stated above.

Ask a specific question about this device