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The Lumendi DiLumen is an accessory to an endoscope. The DiLumen dual balloon accessory is intended for use with any standard endoscope that has a distal tip outer diameter of 12.5 – 14.3 mm. The device is indicated to ensure complete positioning of an endoscope during navigation in the large intestine, while assisting with optical visualization, diagnosis, tissue manipulation, and endoscopic treatment.

The DiLumen Endolumenal Interventional Platform is a non-sterile, single-use, close-fitting sleeve that fits securely over a standard endoscope. The DiLumen utilizes two balloons to position and stabilize the endoscope within a patient's large intestine. After the DiLumen is installed over the endoscope and DiLumen are navigated to the target zone with the balloons deflated. At the area of interest, the Aft Balloon, which is attached to the DiLumen sleeve, is inflated until it contacts the tissue near the proximal end of the articulating section of an endoscope. The second balloon, the Fore Balloon, is also attached to the sleeve via two flexible extension push rods and is deployed at the distal end of the endoscope at a variable distance. Once extended and inflated, the Fore Balloon contacts the intestine tissue, and in combination with the Aft Balloon, creates an isolated diagnostic / therapeutic zone. Both balloons are controlled using an Inflation Handle with a squeeze bulb to manually inflate and deflate them (independently) with ambient air as they assist in stabilizing the endoscope and the therapeutic area. The Suture Loops attached to the Fore Balloon of the DiLumen allow clinicians to manipulate tissue when used with an endoscopic clip. The endoscope flexibility, maneuverability and functionalities (such as visualization, suction, insufflation, etc.) are unaffected by the presence of the DiLumen is designed to permit the usage of any standard tool through the endoscope working channel.

The provided text is a 510(k) summary for the DiLumen Endolumenal Interventional Platform, detailing modifications to a previously cleared device. It primarily focuses on demonstrating substantial equivalence to the predicate device rather than presenting a full de novo clearance study with extensive clinical performance data against specific acceptance criteria.

Therefore, many of the requested elements for a study proving a device meets acceptance criteria (like a large human reader study, detailed ground truth establishment for a test set, etc.) are not present in this document. The document states that the changes "do not raise different questions of safety or effectiveness," and therefore, "the bench testing to support this 510(k) notice is limited."

However, I can extract the information that is present and indicate where the requested information is not available.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not present a formal table of quantitative acceptance criteria for clinical performance (e.g., sensitivity, specificity, accuracy) typical for a new AI/diagnostic device. Instead, the "acceptance criteria" are implied by the nature of a 510(k) for a modified device – demonstrating that the modifications do not negatively impact the device's original performance and that it remains substantially equivalent to its predicate. The "performance" is largely demonstrated through bench testing and verification studies.

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

This document primarily describes bench and user validation testing for design changes, not a clinical trial with a "test set" in the sense of patient images or data for an AI algorithm. Therefore:

• Sample size for test set: Not applicable in the context of an AI/diagnostic algorithm testing on patient data. The "test set" would be the modified device itself, subjected to various physical and functional tests. Specific sample sizes for bench tests (e.g., number of devices tested for pull force) are not detailed.
• Data Provenance: Not applicable in terms of patient data. The "data" comes from engineering bench tests and potentially user feedback on the device.

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

• Number of experts: Not applicable. Ground truth for an AI/diagnostic algorithm using expert reads is not relevant here. The "experts" would likely be the engineers, quality assurance personnel, and potentially clinical users (e.g., endoscopists) involved in the design verification, validation, and user testing. Their specific number and qualifications are not detailed.

4. Adjudication Method for the Test Set

• Adjudication method: Not applicable. This concept applies to consensus reading for ground truth in diagnostic studies, which is not the nature of the tests described here.

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

• MRMC study: No, an MRMC comparative effectiveness study was not done. The document states that the changes "do not raise different questions of safety or effectiveness," implying that extensive clinical re-evaluation of diagnostic accuracy or comparative effectiveness was not deemed necessary for this 510(k) Special submission. The study is focused on the device's technical and physical performance after minor modifications.

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

• Standalone performance: Not applicable. This device is a mechanical accessory to an endoscope, not a software algorithm, so the concept of standalone performance does not apply.

7. The Type of Ground Truth Used

• Type of ground truth: For mechanical and functional performance, the "ground truth" would be established engineering specifications, design parameters, and relevant ISO/USP standards (e.g., ISO 10993 for biocompatibility, predetermined values for pull/push force). For user validation, the "ground truth" would be the subjective and objective feedback from clinical users regarding the ease of use and functionality of the modified device compared to the predicate.

8. The Sample Size for the Training Set

• Training set sample size: Not applicable. This is not an AI/machine learning device that requires a training set.

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

• Ground truth for training set: Not applicable.

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