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The aspiration and infusion cannulae and needles are indicated for aesthetic body contouring and general tissue aspiration.

INEX Cannulae and Needles are used to remove fluid, soft tissue, and exudates and infusion, utilizing a hollow stainless tube and multiple tips, handle and attachment connectors that are disposable in configuration. They are used during general, plastic, and reconstructive procedures.

This FDA 510(k) summary for the INEX Cannulae and Needles does not contain details about acceptance criteria or a study proving the device meets those criteria in the way typically expected for an AI/CADe device submission.

Instead, this document is for a Class II medical device, specifically surgical cannulae and needles used for lipoplasty, and the approval pathway is based on substantial equivalence to a predicate device. This means the device is being compared to an existing legally marketed device, and the focus is on demonstrating that the new device is as safe and effective as the predicate.

Therefore, many of the requested categories (like sample size for test set, number of experts for ground truth, MRMC studies, standalone performance, training set details) are not applicable to this type of submission.

Here's a breakdown based on the provided text, addressing the requested information where possible and indicating when it's not applicable:

1. Table of Acceptance Criteria and Reported Device Performance

As this is a substantial equivalence determination for a physical medical device (cannulae and needles), there are no direct performance metrics like sensitivity, specificity, or FROC scores typically found in AI/CADe submissions. Instead, "acceptance criteria" are related to demonstrating similarity to a predicate device and compliance with general safety and performance standards.

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

• Not Applicable. This is a substantial equivalence submission for a physical surgical instrument, not an AI/CADe device evaluated with a test set of data. The "test" involved comparing the design, materials, and intended use to a predicate device and performing biocompatibility testing. There is no "data set" in the context of an AI algorithm.

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

• Not Applicable. There is no "test set" of an AI algorithm or images requiring expert ground truth in this submission.

4. Adjudication method for the test set

• Not Applicable. No test set requiring adjudication in the context of AI was used.

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. This is a physical surgical device, not an AI/CADe system designed to assist human readers. Therefore, an MRMC study is irrelevant.

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

• Not Applicable. This is a physical surgical device, not an algorithm.

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

• Not Applicable. In an AI context, ground truth refers to the true label of a data point. For this physical device, the "truth" is established by demonstrating that its design, materials, manufacturing process, and intended use conform to established standards and are substantially equivalent to a legally marketed predicate device, as well as passing biocompatibility tests.

8. The sample size for the training set

• Not Applicable. This is a physical device, not an AI algorithm that requires a training set.

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

• Not Applicable. As there is no training set for an AI algorithm, there is no ground truth to establish for it.

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