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The Flexible Intubation Video Endoscope - Sterile (FIVE-S) are intended for use by physicians for endotracheal intubation and diagnostic and therapeutic procedures in nasal, sinus and nasopharyngeal endoscopy, tracheoscopy and esophagoscopy and laryngoscopy. The Karl Storz Video Bronchoscope is intended to provide visualization via a video monitor.

E-Box: the product serves as an adaptor for operating the flexible single-use videoscope on the compatible CCU.

The Flexible Intubation Video Endoscope - Sterile (FIVE-S) is a sterile single-use, flexible video-endoscopes. The distal tip houses the CMOS (Complementary Metal Oxide Semiconductor) imaging sensor and the LED light source. The raw data captured at the distal tip CMOS imaging sensor is transferred to the E-Box adaptor, where it is converted to a standard NTSC (National Television System Committee) video signal by the PCB (Printed Circuit Board), which is then driven into one of the CCUs (C-MAC, C-HUB II) for further processing and video formatting for output to a display monitor. The videoscopes and E-Box are powered by the CCUs through the connecting cords.

This document describes the premarket notification (510(k)) for the KARL STORZ Flexible Intubation Video Endoscope - Sterile (FIVE-S). It's important to note that this is a medical device clearance document, not a typical AI/ML medical device submission. Therefore, it focuses on demonstrating substantial equivalence to a predicate device through non-clinical performance data, primarily bench testing, rather than extensive clinical studies or AI model performance metrics.

Based on the provided text, here's an analysis of the acceptance criteria and the study proving the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

For traditional medical devices like the FIVE-S, "acceptance criteria" are generally tied to technical specifications and performance characteristics demonstrating equivalence to a predicate device, rather than diagnostic accuracy metrics seen in AI/ML products. The document highlights various technical specifications and non-clinical performance tests.

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

The document explicitly states: "Clinical testing was not required to demonstrate the substantial equivalence to the predicate devices. Non-clinical bench testing was sufficient to establish the substantial equivalence of the modifications."

Therefore, there isn't a "test set" in the traditional sense of patient data used to evaluate AI/ML performance. The "testing" involved bench tests on the physical device itself. The provenance would be the manufacturer's testing labs (KARL STORZ SE & Co. KG, Tuttlingen, Germany). The data from these bench tests are inherently prospective as they are conducted specifically to validate the new device.

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

Not applicable. Since no clinical testing or human-in-the-loop performance evaluation was conducted for this 510(k) (as it's a hardware device clearance, not an AI/ML product), there were no experts establishing ground truth for a clinical test set. The "ground truth" for the device's technical specifications was established through standard engineering and laboratory measurements.

4. Adjudication Method for the Test Set

Not applicable. No clinical test set requiring expert adjudication was used.

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

No. An MRMC study was not performed. The device is a bronchoscope, and the clearance is based on substantial equivalence of its physical and imaging characteristics to a predicate device, not on improved diagnostic reader performance with AI assistance.

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

Not applicable. This is a medical endoscope, which is a hardware device. It does not have a standalone algorithm in the sense of an AI/ML product. Its "performance" is evaluated based on its physical characteristics and image capturing capabilities.

7. The Type of Ground Truth Used

The ground truth used for this device clearance is engineering specifications and established metrics for imaging performance and physical characteristics of endoscopes. This is validated through:

• Physical measurements (e.g., diameters, lengths, tip deflection).
• Optical testing using standardized targets and methods (e.g., resolution charts for Lp/mm, field of view measurements).
• Electrical safety and biocompatibility testing according to recognized consensus standards.

8. The Sample Size for the Training Set

Not applicable. This is not an AI/ML device, so there is no training set in the context of machine learning. The device design and manufacturing processes are refined through engineering and iterative development, not through data-driven training.

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

Not applicable. As there is no AI/ML training set, there is no ground truth established for one. The "ground truth" for the device's design and performance goals is rooted in established medical device standards, clinical needs for intubation and endoscopy, and the characteristics of the predicate device.

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