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To be attached to the distal end of the endoscope to facilitate endoscopic therapy, to be used for the following:

• Keeping the suitable depth of endoscope's view field
• Helping the endoscope with being inserted into the gastrointestinal tract

The Arc EndoCuff and Arc Endocuff Vision have short tube like shape with flexible hairs and is attached to the distal end of the endoscope to facilitate endoscopic therapy.

The Arc EndoCuff and Arc Endocuff Vision are designed to fit specific endoscopes (as designated on the packaging), and is supplied sterile following radiation sterilization and is single use only.

The Arc EndoCuff and Arc Endocuff Vision are cylindrical shaped all polymer products. They utilise the combined properties of two polymer materials to self-retain to the designated endoscope(s). The products feature a number of flexible "hairs" that fold within the structure of the product during intubation and forward movement when in use, and open out when drawn backward to control field of view.

Both the Arc EndoCuff and Arc Endocuff Vision devices are manually pushed onto the tip of the endoscope. It is designed to grip the endoscope sufficiently so as to prevent dislodgment during the procedure but without causing damage to the endoscope. At the end of the procedure, the device is removed either manually or with a purpose designed disposable tool before the endoscope is reprocessed.

The endoscope fitted with the Arc EndoCuff or Arc Endocuff Vision is inserted into the intestine either through the anus or a stoma and is used in the standard manner. The EndoCuff stabilizes the tip of the instrument in the bowel lumen enabling the shaft of the Arc endoscope to be more easily straightened on pulling back so avoiding excessive looping. This is because the cuff maintains the position of the tip without having to angle it acutely against the bowel wall to gain purchase. The device does not hinder forward motion or cause trauma.

During extubation, the device enables tip withdrawal in a more controlled fashion and provides improved visualisation by opening up the intestinal lumen for careful examination. Mucosal folds are everted and flattened enabling a more complete view of the areas of the bowel wall that were hidden behind mucosal folds.

This document is a 510(k) Summary for the Arc EndoCuff and Arc Endocuff Vision devices, which are accessories for endoscopes. It describes the device, its indications for use, and technological characteristics. The main purpose of this submission is to add additional marketing claims, which are supported by non-clinical performance testing, clinical data, or device design.

The document does NOT describe the acceptance criteria or a study that proves the device meets the acceptance criteria for an AI/ML medical device.

Instead, it pertains to a physical medical device (an endoscope accessory) and focuses on demonstrating substantial equivalence to previously cleared predicate devices and supporting additional marketing claims for these physical devices.

Therefore, many of the requested elements for describing the acceptance criteria and a study for an AI/ML device (e.g., sample size for test/training sets, data provenance, expert ground truth, MRMC studies, standalone performance) are not applicable to the content of this 510(k) summary.

However, I can extract information relevant to the device's claims and their supporting documentation as provided in the document.

Based on the provided document, here's what can be inferred about the device's claims and supporting evidence, noting that the context is a physical medical device, not an AI/ML system:

The document describes marketing claims for the Arc EndoCuff and Arc Endocuff Vision, and the supporting documentation for each claim. This is the closest equivalent to "acceptance criteria" and "proof" in the context of this 510(k) submission, even though it's not a formal set of quantitative acceptance criteria for an AI/ML model's performance.

1. Table of Acceptance Criteria and Reported Device Performance:

Since this is not an AI/ML device, there are no specific quantitative acceptance metrics like sensitivity or specificity. Instead, the "acceptance criteria" are the marketing claims, and the "reported device performance" is the type of documentation (clinical data, device design, in-vitro testing) that supports these claims.

Regarding the other requested information, these are largely not applicable as the document describes a physical medical device, not an AI/ML system:

2. Sample sized used for the test set and the data provenance:

• The document mentions "Clinical Data" and "Meta-Analysis of the Clinical literature supports the improvement of Adenoma Detection Rate claims." It does not specify the sample sizes of the individual studies included in the meta-analysis, nor details about data provenance (e.g., country of origin, retrospective/prospective nature of the meta-analyzed studies). This information would typically be in the full clinical study reports, not a 510(k) summary.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not applicable as this is a physical device; no "ground truth" establishment in the context of an AI/ML model's output for analysis by experts is described. Clinical studies would involve physician assessments, but this document does not detail the number or qualifications of clinicians involved in the meta-analysis.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

• Not applicable. This concept pertains to establishing ground truth for AI model performance evaluation, which is not what this document is about.

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:

• Not applicable. MRMC studies are for evaluating diagnostic performance of systems (often AI) with human readers. The clinical data cited is likely related to the device's impact on Adenoma Detection Rate during colonoscopy, which is a clinical outcome, not a reader study of diagnostic interpretation. The document states the device results in a "statistically significant and clinically relevant improvement in adenoma detection rate," but does not provide specific effect sizes.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

• Not applicable. This is a physical device that assists human clinicians, not a standalone AI algorithm. It's used with an endoscope, not independently.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

• For the clinical claim (ADR improvement), the "ground truth" would be the pathology results of detected polyps/adenomas and the patient outcome of Adenoma Detection Rate as determined in the clinical studies included in the meta-analysis.

8. The sample size for the training set:

• Not applicable. This is not an AI/ML device.

9. How the ground truth for the training set was established:

• Not applicable. This is not an AI/ML device.

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