Search Results

This instrument has been designed to be used for viewing intra-operative blood flow in the cerebral vascular area and is intended for use in adults only.

The SURGICAL MICROSCOPE SYSTEM ORBEYE with IR is used for viewing intra-operative blood flow in the cerebral vascular area. When the INFRARED IMAGING UNIT MAJ-2304 and the INFRARED FILTER UNIT MAJ-2307 are mounted on the LED LIGHT SOURCE OME-L200 and the ORBEYE SURGICAL MICROSCOPE OME-V200 respectively, it allows the surgical microscope to produce excitation light and resolve florescence light from the fluorescent ICG. The subject device of this 510(k) submission, ORBEYE with IR system, enables the microscopic observation with IR (Infrared) Imaging. The ORBEYE with IR system will be marketed as a System and will also be sold as individual components.

This medical device submission for the SURGICAL MICROSCOPE SYSTEM ORBEYE with IR (K190772) does not contain a study that establishes acceptance criteria for diagnostic or performance metrics (e.g., sensitivity, specificity, accuracy) that are typically reported for AI/ML-based medical devices or devices that involve interpretation of images for diagnosis.

The submitted document focuses on demonstrating substantial equivalence to a predicate device (Leica FL800, K141136) through technical comparisons and non-clinical performance testing. It largely relates to the device's ability to produce excitation light and resolve fluorescence light from ICG for viewing intra-operative blood flow.

Therefore, many of the requested elements for describing acceptance criteria and a study proving their fulfillment are not applicable or cannot be extracted from the provided text.

Here's an analysis based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not provide a table of acceptance criteria related to diagnostic performance (e.g., sensitivity, specificity, or image quality metrics that would be directly comparable). The "performance data" section focuses on engineering and safety verifications.

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

• Animal Study: 5 male beagle dogs, 7-8 months old.
• Provenance: Not explicitly stated, but the study was conducted in accordance with 21 CFR Part 58 - Good Laboratory Practice for Nonclinical Laboratory Studies, suggesting a controlled laboratory environment. Retrospective or prospective is not specified, but typically animal studies supporting premarket submissions are prospective.

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

Not applicable. The animal study involved observing gross pathological abnormalities, likely by veterinarians or researchers, but the document does not specify the number or qualifications of experts for establishing a ground truth in a diagnostic sense.

4. Adjudication Method for the Test Set:

Not applicable. There's no mention of a diagnostic performance study requiring adjudication.

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

No, an MRMC comparative effectiveness study was not done. The document explicitly states: "No clinical study was performed to demonstrate substantial equivalence."

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

Not applicable. This device is a surgical microscope system for "viewing" intra-operative blood flow. It is an imaging device intended for human use and interpretation, not a standalone AI algorithm that would produce a diagnostic output without human intervention.

7. The Type of Ground Truth Used:

• Bench Testing: Engineering specifications and measurements for light wavelength, optical properties, and safety limits.
• Animal Study: Observation of "gross pathological abnormalities" in the cerebral tissue, cerebral surface arteries and veins. This would be considered observational ground truth based on biological outcomes.

8. The Sample Size for the Training Set:

Not applicable. The device described is a medical imaging system, not an AI/ML algorithm that requires a training set in the conventional sense. The "software verification and validation" tests relate to the proper functioning of the device's embedded software, not to training an AI model.

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

Not applicable (as above, no training set for an AI model).

Ask a specific question about this device