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The GLOW800 is a Leica Surgical Microscope accessory used in viewing intra-operative blood flow and related tissue perfusion in the cerebral vascular region as well as blood flow following plastic and reconstructive surgery and coronary artery bypass grafting (CABG).

Similar to the predicate device (Leica FL800 most recently cleared under K141136 and previously in K061871 and K080612), the GLOW800 is an accessory to the Leica Microsystems (LMS) Class I 510(k) exempt surgical operating microscope (SOM).

The GLOW800, a non-contact, non-invasive device similar to its predicate, allows the surgical microscope to produce excitation light and resolve fluorescent emission from the fluorescent agent Indocyanine green (ICG). The generated fluorescence signal depicts the distribution of the infra-red dye in the patient's blood vessels during the surgical procedure (fluorescence video angiography). The ICG fluorescence peak is captured for display on the SOM screen. Using an additional camera to capture the visible light (VL) video stream and digitally combining with the Near Infra-red (NIR) video stream presents a high definition display of the surgical site as a pseudocoloured combined image of the same field of view (FOV), which includes anatomical information.

The GLOW800 utilizes the illumination light source, supplied as standard with the SOM to produce excitation light which is filtered using an illumination filter (also referred to as the excitation filter) within the 750 and 800 spectral wavelength range.

The provided text describes the regulatory clearance for the GLOW800 device, comparing it to a predicate device (Leica FL800 ULT). The crucial information regarding acceptance criteria and study results comes primarily from the "Substantial Equivalence Summary Table: Comparison to Predicate Device" and the "Non-Clinical, Bench, and Clinical Performance Testing" sections.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

Key Takeaway: The GLOW800 device did not undergo a study with pre-defined quantitative acceptance criteria for its performance in the way one might expect for an AI/algorithm-driven device. Instead, the "acceptance criteria" were based on demonstrating functional equivalence to a predicate device through various non-clinical (bench) and preclinical (animal model) studies, and human factors testing. The primary "performance" metric was qualitative assessment (visualization ability) by experts.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Bench Testing: Described as "one-arm study using only the subject device GLOW800 on microscope platform M530 OH6 and assessed vs. historical experience with predicate FL800 (historical control)." No specific sample size for the "test set" in terms of number of devices tested is explicitly stated, but it implies a single GLOW800 unit was extensively tested against pre-established criteria and historical data.
• Preclinical Study:
  • Sample Size: 8 pigs.
  • Data Provenance: Conducted at the University of Mainz, Germany Institute of Neurosurgical Pathology. This was a direct comparative test, not a retrospective assessment.
• Human Factors Testing:
  • Sample Size: 21 surgeons and 15 nurses/other allied health professionals.
  • Data Provenance: Conducted at the Mt. Sinai Medical Center Neurosurgery Simulation Core, Annenberg Building, New York. This was a prospective study in a simulated operating room environment.

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

• Preclinical Study (Porcine Model):
  • Ground truth was based on "independent scoring assessments predefined within the protocol."
  • Experts involved in the assessment were "cardiovascular surgeon, neurosurgeons and veterinarians." The number of each type of expert is not specified, nor is their specific experience level (e.g., "10 years of experience").
  • The results state "n=18 comparative reviews," implying 18 assessments of the image sets. It's unclear if this means 18 different experts, or 18 reviews conducted by a smaller group of experts. Given the "independent scoring assessments" and the stated types of experts, it suggests multiple experts.
• Human Factors Testing: The "ground truth" for human factors was based on the ability of users (surgeons, nurses/techs) to perform tasks correctly and intuitively, assessed via "observational analysis." The primary "experts" here were the observers assessing performance against the predefined tasks and acceptance criteria, but their specific qualifications are not detailed beyond "observers."

4. Adjudication Method for the Test Set

• Preclinical Study: "Independent scoring assessments predefined within the protocol." This suggests that multiple experts made assessments, but the specific adjudication method (e.g., majority vote, consensus meeting, 2+1, 3+1) is not specified beyond being "independent."
• Human Factors Testing: "Observational analysis" with "pre-defined test cases and objective pass/fail criteria." No specific adjudication method among observers is mentioned, but the outcomes (e.g., "100% of users... perform key functions") suggest clear-cut observations rather than needing complex 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

• No MRMC study was done in the context of AI assistance.
• The GLOW800 is a hardware accessory (optical system, camera, and basic software for combining images), not an AI/algorithm. Its purpose is to visualize blood flow, not to interpret or provide diagnostic insights based on that visualization. Therefore, the concept of "human readers improve with AI vs without AI assistance" does not apply to this device submission.
• The "comparative effectiveness" was primarily demonstrated by showing functional equivalence between the new device and a predicate optical device, meaning the new device provides similar or better visual information.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• This question is largely irrelevant as the GLOW800 is a hardware device (an accessory to a surgical microscope) designed for human use, not a standalone algorithm. Its "performance" is inherently tied to its ability to present visual information to a human operator.
• The "bench testing" does cover aspects of the device's technical performance (e.g., optical specifications, software functionality) in a "standalone" or de-coupled manner, ensuring it correctly processes and displays information.

7. The Type of Ground Truth Used

• Bench Testing: Internal design specifications, historical performance data of the predicate device, and "experiential basis" from prior device marketing history.
• Preclinical Study: The "actual" blood flow and vessel architecture in the porcine model (as visualized by the predicate device and assessed by expert observation of both devices' outputs) served as the de facto ground truth. The goal was functional equivalence in visualization, not an independent "pathology" ground truth of true blood flow given the real-time nature of the imaging.
• Human Factors Testing: Pre-defined "objective pass/fail criteria" for task performance and qualitative assessment of usability.

8. The Sample Size for the Training Set

No "training set" (in the context of machine learning) is mentioned or implied, as this device does not appear to employ machine learning or AI algorithms requiring a training phase.

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

Not applicable, as there is no mention of a training set for an AI/ML algorithm.

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