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The Galileo Hysteroscopes are endoscopes intended for direct visualization of the cervical canal and uterine cavity for diagnostic procedures during gynecological procedures. The Hysteroscope diagnostic include abnormal uterine bleeding, infertility and pregnancy wastage, evaluation of abnormal hysterosalpingogram, intrauterine foreign body, amenorrhea and pelvic pain.

The Galileo Disposable Hysteroscopes are a line of disposable endoscopes based on existing endoscope technology. The Galileo Disposable Hysteroscopes will be available in 2.8 mm OD X 270 mm length size. The Galileo Disposable Hysteroscopes are fiber optic design endoscopes that are offered in disposable configurations only. Fiberoptic design endoscopes function by light being transmitted from a standard external high intensity light source through optical fibers to the distal tip of the endoscope. The image of the target is then transmitted from the distal end via an objective lens and a fiberoptic imaging bundle to a proximal eyepiece. The image can be viewed directly or it may be transmitted through a video camera to a video monitor. The Disposable Hysteroscopes are offered with a coupler that includes a light source which is provided by Galileo Electro-Optics Corporation. The Galileo coupler is compatible only with the Galileo Disposable Hysteroscopes and the other cleared commercially available Galileo endoscopes.

The provided document, K974297, "Galileo Corporation Galileo Disposable Hysteroscopes," describes the acceptance criteria and the study conducted to demonstrate the substantial equivalence of the device.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: "Samples of each type of hysteroscope containing the lens, image fiber, and illumination fiber were used for this testing." The exact number of samples is not specified, but it implies at least one stainless steel sheathed hysteroscope and at least one polyimide sheathed hysteroscope.
• Data Provenance: The study was conducted by Galileo Corporation, a U.S.-based company, suggesting the data is domestic and likely prospective as it involves new product testing.

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

Not applicable. This was a physical performance test for optical and structural integrity, not a study requiring expert clinical or diagnostic ground truth. The "ground truth" was the objective optical measurements before and after stress.

4. Adjudication Method for the Test Set

Not applicable. This was a physical performance test using objective measurements, not a human reader study requiring adjudication.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The study focused on the physical and optical performance of the device itself under stress, rather than human readability or diagnostic accuracy with human interpretation.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

Yes, a standalone study was performed. The study evaluated the intrinsic optical and structural performance of the hysteroscopes in isolation, without human interaction playing a role in the performance metrics. The device's ability to transmit an image and maintain integrity was assessed directly.

7. Type of Ground Truth Used

The ground truth used was objective optical performance measurements and structural integrity of the device. This was assessed by measuring properties like field of view, angle of view, resolution on axis, and uniformity of illumination before and after a deflection test. The "truth" was whether these objective physical metrics remained within acceptable standards.

8. Sample Size for the Training Set

Not applicable. This device is a physical medical instrument, not an AI or algorithm-based device that requires a "training set" in the machine learning sense. The testing performed was validation testing, not model training.

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

Not applicable, as there was no training set for an AI/algorithm.

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