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Endoscopic Distal Attachment is intended to be used in combination with compatible endoscopes to maintain the field of view during endoscopic procedures such as mucosal resection.

The Endoscopic Distal Attachment is an additional device, made of TPU designed to attach to the distal end of the endoscope. The device is composed of three main portions: an attaching portion, a distal portion, and a drain portion. The attaching portion is a wider diameter opening which is used to connect the attachment to a compatible endoscope; the distal portion is the ending portion of the attachment which tapers into narrower diameter opening. The hole, which is only available for some models, forms drain portion which prevent the fluids lodging on the surface of the endoscope.

The Endoscopic Distal Attachment can be used in combination with compatible endoscopes to maintain an appropriate endoscopic field of view.

The Endoscopic Distal Attachment has six models, depending on different surface design (flat or incline), with or without hole and with scale or without scale. The models include models of flat face without hole, flat face with hole, inclined face without hole, inclined face with hole, flat face without hole with scale and flat face.

This document is a 510(k) clearance letter for a medical device called "Endoscopic Distal Attachment (AF-D series)". Based on the provided text, the device is not an AI/Software as a Medical Device (SaMD). It is a physical accessory made of TPU that attaches to endoscopes.

Therefore, many of the requested bullet points, such as "MRMC comparative effectiveness study," "standalone (i.e. algorithm only) performance," "sample size for training set," and "how ground truth for training set was established," are not applicable to this type of device and are not discussed in the clearance letter.

The clearance relies heavily on bench testing and biocompatibility data to demonstrate substantial equivalence to a predicate device, rather than clinical study data or AI performance metrics.

Here's an analysis of the provided text in relation to your questions:

1. A table of acceptance criteria and the reported device performance

The document does not present a formal table of acceptance criteria with quantified reported device performance in the precise way you've requested for an AI/SaMD. Instead, it lists the types of performance tests conducted and states that the device "met all design specifications" and "demonstrated safety and essential performance."

The acceptance criteria are implicitly defined by the standards and the comparison to the predicate device. The performance is summarized as meeting these criteria.

2. Sample sizes used for the test set and the data provenance

• Sample Size for Test Set: Not explicitly stated in terms of number of devices or number of tests conducted for each category. The document indicates "performance tests were implemented on both the subject device and the predicate device," implying sufficient samples were used to conduct the various bench tests. This is a physical device, so "test set" would refer to the number of physical devices and components tested.
• Data Provenance: The testing was conducted by Alton (Shanghai) Medical Instruments Co. Ltd. (China). The data origin is from their internal testing. The document implies these are prospective tests conducted specifically for this submission.

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

• N/A. This is a physical non-AI medical device. The "ground truth" for its performance is established through adherence to engineering specifications, material properties, and standardized testing protocols (e.g., ISO, ASTM standards), not through expert consensus on images or clinical outcomes.

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

• N/A. Adjudication methods like 2+1 or 3+1 are typically used for establishing ground truth in clinical imaging studies or pathology where human annotators are involved. For this physical device, performance is evaluated against objective, measurable criteria defined by engineering standards and specifications.

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. This is a physical device, not an AI/SaMD. MRMC studies are not applicable.

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

• N/A. This is a physical device, not an algorithm.

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

• For this physical device, the "ground truth" (or basis for verification) comes from engineering specifications, material science principles, and international consensus standards (e.g., ISO for biocompatibility and sterilization, ASTM for packaging and mechanical properties). The device's performance is compared against the established limits or requirements of these standards and against the performance of the predicate device.

8. The sample size for the training set

• N/A. This is a physical device, not an AI/SaMD. There is no "training set."

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

• N/A. This is a physical device, not an AI/SaMD. There is no "training set" or corresponding ground truth establishment process in the AI sense.

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