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The Ultravision™ Visual Field Clearing System is indicated for the clearance of smoke and other particulate matter that is created during laparoscopic surgery.

The Ultravision™ Visual Field Clearing System is a device that precipitates surgical smoke generated during laparoscopic procedures to clear the visual field. The device components are summarized briefly in Table 1, below.

Acceptance Criteria and Device Performance for ULTRAVISION™ Visual Field Clearing System

The ULTRAVISION™ Visual Field Clearing System is indicated for the clearance of smoke and other particulate matter created during laparoscopic surgery. The acceptance criteria address various aspects of the device's safety, performance, and usability.

1. Table of Acceptance Criteria and Reported Device Performance

Given the nature of the device as a "surgical smoke precipitator," the acceptance criteria were primarily qualitative and focused on safety, usability, and the ability to maintain a clear visual field.

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

• Test Set (Clinical Study): 30 patients were enrolled. Follow-up data was available for 25/30 enrolled patients.
• Data Provenance: The clinical study was a randomized, double-blinded, controlled, prospective trial conducted at a "single site." The location of this single site (e.g., country of origin) is not explicitly stated in the provided text.

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

• Number of Experts: The text refers to "The surgeons and reviewing panel" rating the treatment group's visibility. The specific number of surgeons or members of the reviewing panel is not provided.
• Qualifications of Experts: The qualifications of the "surgeons" are implied by their role in performing and assessing laparoscopic cholecystectomy. The qualifications of the "reviewing panel" are not specified beyond their role in judging visual field effectiveness.

4. Adjudication Method

The text indicates that "The surgeons and reviewing panel rated the treatment group to have a higher mean proportion of procedures with effective visibility than the control group." This suggests some form of consensus or independent rating was used, but a specific adjudication method (e.g., 2+1, 3+1) is not explicitly detailed. The blinding of the surgeon to the device's activation status suggests an effort to reduce bias in assessment.

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

A formal MRMC comparative effectiveness study, as typically described in imaging, was not conducted. However, a controlled clinical trial was performed where surgeons served as "readers" of the visual field.

• Effect size of human readers with AI vs. without AI assistance: The device is not an AI-assisted diagnostic tool but a physical device that clears the visual field. Therefore, the "effect size" isn't about human reader improvement with AI, but rather the improvement in the surgical environment (visual field clarity) provided by the device.
  • Visual Field Clarity: The treatment group (with device active) had a "higher mean proportion of procedures with effective visibility" compared to the control group (device deactivated).
  • Procedure Interruptions: In the treatment group, 8 procedures had no interruptions, while in the control group, no cases were completed without interruptions due to visual field impairment.
  • Camera Cleaning: 85% of procedures with the active device required no camera cleaning, compared to only 35% in the control group.

These results indicate a substantial positive impact of the device on the surgeon's ability to maintain a clear visual field and proceed without interruptions.

6. Standalone Performance Study

Yes, a standalone performance (algorithm only without human-in-the-loop performance) was implicitly done for several aspects, though not for visual field assessment.

• Biocompatibility Testing (Table 2): These are laboratory tests evaluating material properties directly, independent of human interaction.
• Chemical Characterization: This study assessed the effect of the device on surgical smoke chemistry, independent of human observers.
• Sterilization and Shelf Life Validation: These studies verify the effectiveness of the sterilization process and integrity of the packaging over time, independent of human application.
• Electrical Safety and EMC Testing: These are objective engineering tests demonstrating compliance with safety standards, not requiring human interpretation of the device's primary function.
• Software Verification and Validation: These analyze the software's functionality independently.
• Animal Simulated-Use Testing: While involving an animal subject, the assessment of functionality, visual field clearance, and non-damaging effects were objectively observed and recorded, serving as a standalone performance validation in a controlled environment prior to human clinical use.

7. Type of Ground Truth Used

• Clinical Study: The primary endpoint, "maintenance of a clear visual field," was established by the subjective assessment and consensus of the surgeons performing the procedures and a "reviewing panel." Secondary endpoints like adverse events and physiological measurements (CO, MetHb) were objective data (lab results) but visual field was assessed by human observation.
• Animal Study: The "acceptance criteria for the study were qualitative verification of performance and usability, through observed clearance of the visual field and an absence of observed clinical chemistry or histology concerns." This indicates a combination of expert observation/assessment (for visual field and usability) and objective laboratory results (clinical chemistry and histology).
• Other Studies (Biocompatibility, Chemical Characterization, Electrical Safety, etc.): These rely on objective test results against established standards and scientific methodologies (e.g., ISO standards, spectrographic analysis, electrical measurements).

8. Sample Size for the Training Set

The provided document describes a medical device, not an AI/ML algorithm that requires a "training set" in the conventional sense for model development. Therefore, there is no explicit training set sample size mentioned for an AI/ML model for this device. The clinical trial and animal studies serve as validation, not training.

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

As stated above, this device is not an AI/ML algorithm that uses a "training set." Therefore, this question is not applicable in the context of the provided information.

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