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The Flexible Bronchoscopes have been designed to be used with the video processor, endotherapy accessories and other ancillary equipment for endoscopy within the airways and tracheobronchial tree.

The Flexible Bronchoscope is for use in a hospital environment. The Flexible Bronchoscope is a single-use device designed for use in adults.

The Flexible Bronchoscope (Model: BS27U-12EU, BS27U-12US, BS38U-20EU, BS38U-20US) is intended to be used with the Portable Video Processor (cleared via K243497). The Flexible Bronchoscope is inserted through the airways and tracheobronchial tree during bronchoscopy, and when used with the compatible video processor and monitor, the endoscope system can be operated as intended and indicated. The Flexible Bronchoscope is a single-use endoscope, which consists of a Handle, an Insertion Section, and an Endoscope Connector. The handle includes a deflection lever, a lever lock, a push button for picture taking/video recording, a push button for suction, a connector for suction tubing, a Luer port for insertion of accessory devices and irrigation to the working channel and a LED for illumination. The insertion section contains one working channel, wiring to transmit the image signals to the video processor, and two optical fibers to transmit illumination from the handle to the distal tip. The distal bending section of the insertion section is controlled by the user via the deflection lever on the handle. The distal end of the insertion section contains a CMOS sensor for capturing image and transmitting it to the video processor, optical fibers for transmitting illumination from the LED inside the handle, and the distal opening of the working channel. The Endoscope Connector connects the endoscope handle to the video processor, which provides power and processes video signals from the endoscope. Same as the predicate, the subject device is also provided in 2 deflection versions (US/EU deflection).

This document is an FDA 510(k) clearance letter for a Flexible Bronchoscope, indicating substantial equivalence to a predicate device. However, it does not contain the level of detail requested regarding acceptance criteria and a specific study proving the device meets those criteria, particularly in the context of an AI/algorithm-driven device.

The provided text focuses on the physical and performance characteristics of the bronchoscope itself, its intended use, technological comparison to a predicate device, and various non-clinical tests (electrical safety, photobiological safety, mechanical/optical performance, biocompatibility, sterilization, shelf life, and package validation).

There is no mention of an AI component, an algorithm, or any study involving human readers, ground truth establishment, or performance metrics like sensitivity, specificity, or AUC. The "device performance" in this context refers to the bronchoscope's mechanical and optical functionality, not the diagnostic accuracy of an AI algorithm.

Therefore, most of the requested information cannot be extracted from this document.

Here's an attempt to answer based on the provided text, highlighting what is missing:

1. Table of acceptance criteria and reported device performance

The document does not present a formal table of "acceptance criteria" for a diagnostic algorithm with corresponding "reported device performance" in terms of clinical accuracy metrics (like sensitivity, specificity, AUC). Instead, it states that various non-clinical tests were performed to demonstrate compliance with recognized standards and that the device is "as safe, as effective, and performs as well as the legally marketed device identified above."

Below is a table summarizing the types of tests and the general conclusion, but without specific quantitative acceptance criteria or performance metrics related to diagnostic accuracy.

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

• Sample Size for Test Set: Not applicable/Not mentioned. This document describes a medical device (bronchoscope) itself, not an AI algorithm performing a diagnostic task on a dataset. The "tests" mentioned are non-clinical engineering and biological safety tests, not tests on a dataset.
• Data Provenance (e.g. country of origin of the data, retrospective or prospective): Not applicable/Not mentioned.

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

• Not applicable. There is no mention of "ground truth" in the context of an AI algorithm's diagnostic performance for which experts would be needed. The "ground truth" for the non-clinical tests would be the established performance specifications and standards for a bronchoscope.

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

• Not applicable. As no expert ground truth establishment for a diagnostic AI is mentioned, no adjudication method would be relevant.

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

• No. This document describes the clearance of a flexible bronchoscope, a physical medical device. It does not mention any AI component or a MRMC study.

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

• Not applicable. There is no mention of an algorithm in this document that would perform as a standalone device.

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

• Not applicable. Ground truth in the context of diagnostic AI is not mentioned. For the non-clinical tests, the "ground truth" is compliance with established engineering and safety standards.

8. The sample size for the training set

• Not applicable. There is no mention of an AI model or a training set.

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

• Not applicable. There is no mention of an AI model or a training set.

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