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The NovaProbe Inc. LED Light is used to illuminate the site of the surgery during minimally invasive surgical procedures in Arthroscopy (orthopedic surgery), Laparoscopy (general and gynecological surgery) and Endoscopy (general, gastroenterological and ENT surgery). The light is transmitted from the source through an optical cable and a scope.

The NOVAPROBE LED LEUKOS 175 is specifically designed to provide the cold light intensity required for modern day Endoscopic procedures. The LED light provides the color temp of 6500 deg K also known as white light. The white light offers unmatched quality for the single chip, three chip and HD cameras. The LED light intensity is controlled digitally. Using LED nullifies any skin burning problems that may occur due to the use of arc lamps. The NovaProbe LED Light source assures that the light passing through the fiber optic cable is a cold light.

The provided text is a 510(k) summary for the NovaProbe LED Light Source (LEUKOS 175). This document focuses on demonstrating substantial equivalence to pre-existing predicate devices rather than providing unique performance data or clinical study results for the new device. Therefore, it does not contain the specific information requested in your prompt regarding acceptance criteria, detailed study design, or specific performance metrics in the way a clinical trial report would.

Here's the breakdown of what can be extracted based on the provided text, and what cannot:

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

The document does not explicitly present a table of acceptance criteria with corresponding performance results. Instead, it states that "Design verification testing demonstrates that the devices function as intended, and the Performance did not raise any new issues of safety and effectiveness, and that formal user training is not required." It also mentions that the device "performs to its specifications, operates as intended, is safe and effective, and is substantially equivalent to legally marketed devices."

The "performance" information provided is primarily comparative to predicate devices, focusing on technological characteristics like:

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

The document explicitly states: "No clinical data was required to confirm safety and effectiveness." Therefore, there is no test set, sample size, or data provenance as would be found in a clinical study report. The evaluation was based on non-clinical design verification testing and comparison to predicate devices.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)

Not applicable, as no clinical data or test set involving expert review was utilized for this 510(k) submission.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set

Not applicable, as no clinical data or test set requiring adjudication was performed.

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 is an LED light source, not an AI-powered diagnostic or assistive tool for human readers. No MRMC study was conducted.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done

Not applicable. The device is a physical light source, not an algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

The concept of "ground truth" as typically defined in diagnostic algorithm studies is not applicable here. The evaluation of this device relies on non-clinical design verification testing to ensure it functions as intended and meets safety standards, and on its substantial equivalence to predicate devices which have already established their safety and effectiveness through their own approval processes.

8. The sample size for the training set

Not applicable. This device is a physical medical device (LED light source), not a machine learning algorithm that requires a training set.

9. How the ground truth for the training set was established

Not applicable, as there is no training set for this device.

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