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EB-530H, EB-530S, and EB-530T are intended for the observation, diagnosis, and endoscopic treatment of the trachea and bronchial tree.

FUJIFILM Video Bronchoscopes EB-530H, EB-530T are comprised of three general sections: a control portion, an insertion and an umbilicus. The control portion controls the angulation of the endoscope. This portion also controls the distal end in the endoscope. The insertion portion contains glass fiber bundles, several channels and a complementary Charge-Coupled Device (CCD) image sensor in its distal end. The insertion portion assist in delivering air/suction as well as endoscope accessories, such as forceps. The glass fiber bundles allow light to travel through the endoscope and emit light from the tip of the insertion to illuminate the body cavity. This provides enough light to the CCD image sensor to capture an image and display it on the monitor. The umbilicus consists of electronic components needed to operate the endoscope when plugged in to the video processor and the light source. The endoscope is used in combination with FUJIFILM's video processors, light sources and peripheral devices such as monitor, printer, foot switch, and cart.

The provided text describes a 510(k) summary for the FUJIFILM Video Bronchoscopes EB-530H, EB-530S, and EB-530T. The scope of this document is a substantial equivalence determination based on minor modifications to an already cleared predicate device.

Here's an analysis of the requested information based only on the provided text:

1. Table of acceptance criteria and reported device performance

The document states that the devices met pre-defined acceptance criteria, but it does not explicitly list the specific quantitative acceptance criteria for each performance test. It only states that the devices "met the pre-defined acceptance criteria for the test."

In addition, the following were evaluated for compliance, not performance:

2. Sample size used for the test set and the data provenance

The document does not provide information regarding sample sizes for the test set or data provenance (e.g., country of origin, retrospective/prospective). The performance testing described appears to be bench testing on the physical devices rather than clinical studies with patient data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

This information is not provided in the document. The performance tests mentioned (field of view, bending capability, etc.) are objective technical measurements of the device itself, not assessments requiring expert interpretation of clinical data to establish ground truth.

4. Adjudication method for the test set

This information is not provided in the document. As noted above, the tests described are objective technical measurements, not clinical assessments requiring adjudication.

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

An MRMC comparative effectiveness study was not performed because this submission is for minor modifications to a bronchoscope, not an AI-enabled device. The document does not mention any AI components.

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

A standalone algorithm performance test was not performed because this device is a bronchoscope, not an algorithm or AI system.

7. The type of ground truth used

For the performance tests conducted (field of view, bending capability, etc.), the "ground truth" would be established by objective engineering specifications and measurement standards. It's not a ground truth derived from expert consensus, pathology, or outcomes data, as these are technical performance measurements of the physical device.

8. The sample size for the training set

This information is not provided in the document. As this is not an AI/algorithm-based device, a "training set" in that context is not applicable.

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

This information is not provided in the document. As this is not an AI/algorithm-based device, there is no "training set" with associated ground truth to establish in this context.

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