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EverLift™ Submucosal Lifting Agent is indicated for use in gastrointestinal endoscopic procedures for submucosal lift of polyps, adenomas, early-stage cancers, or other gastrointestinal lesions prior to excision with a snare or other appropriate endoscopic device.

The GI Supply EverLift™ Submucosal Lifting Agent is a prefilled plastic syringe with attached plunger rod containing 5mL of lifting agent. The syringe has a luer lock connection capable of interfacing with a standard, commercially available, endoscopic injection needle.

The EverLift™ Submucosal Lifting Agent is an injectable liquid composition for use as a submucosal injection agent during endoscopic mucosal resection (EMR), endoscopic mucosal dissection (ESD) and polypectomy procedures in the gastrointestinal tract. The device is intended for use in endoscopic resection procedures in the upper and the lower gastrointestinal tract, including the esophagus, the stomach, the small intestine, the sigmoid colon, and the rectum, as a submucosal injectable agent during the removal of polyps, adenomas, early-stage cancers and other pathological lesions by EMR, ESD or polypectomy.

EverLift™ Submucosal Lifting Agent is injected into the submucosal layer by means of a standard, commercially available, endoscopic injection needle, which is inserted into the working channel of the endoscope. The composition, when injected, creates a cushion in situ by lifting the gastrointestinal mucosa from the submucosal laver, allowing the endoscopist to perform an easy and safe resection procedure (EMR, ESD or polypectomy).

The provided document is a 510(k) premarket notification for the EverLift Submucosal Lifting Agent, describing its substantial equivalence to a predicate device. It details non-clinical performance testing but does not include information about AI/ML device performance or clinical studies involving human readers or AI assistance. Therefore, I cannot fulfill all parts of your request related to AI/ML device acceptance criteria and studies.

Based on the provided text, here's what can be extracted and what cannot:

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

The document speaks to "functional and performance requirements" and various "functional performance tests" but does not explicitly list quantified acceptance criteria with corresponding performance metrics in a clear table format that would be typical for an AI/ML device. Instead, it states that tests were conducted to "demonstrate substantial equivalence."

Acceptance Criteria and Reported Device Performance (as inferred and specified in the document):

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

• Sample Size: The document mentions "a series of functional performance tests, animal studies, biocompatibility tests, and sterility tests" but does not provide specific sample sizes (e.g., number of devices tested, number of animals in the preclinical study).
• Data Provenance: The document does not specify the country of origin for the data or whether the studies were retrospective or prospective. Given it's a non-AI/ML device based on physical/chemical properties and animal studies, "retrospective/prospective" in the context of clinical data isn't directly applicable here.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)

This information is not applicable and not provided as this is a medical device for submucosal lifting, not an AI/ML diagnostic or image analysis device requiring expert ground truth for image interpretation. The ground truth for this device's performance is based on physical/chemical measurements and in-vivo effects in animal models.

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

This information is not applicable and not provided as this relates to expert review and consensus for imaging or diagnostic studies, which is not relevant to this device's testing.

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

This information is not applicable and not provided. The device is not an AI/ML algorithm that assists human readers. It is a physical agent used in endoscopic procedures.

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

This information is not applicable and not provided. The device is not an AI algorithm.

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

The "ground truth" for this device's performance is established through:

• Direct physical and chemical measurements (e.g., pH, viscosity, osmolality, density, flow rate).
• Direct observation of physical effects and safety in an in vitro (container integrity) and ex vivo / in vivo (porcine model for lift duration and performance) setting.
• Results from standardized biocompatibility, sterility, and aging tests.
  This is not based on expert consensus, pathology, or outcomes data in the typical sense of AI/ML diagnostic evaluation.

8. The sample size for the training set

This information is not applicable and not provided as this is not an AI/ML device that requires a training set.

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

This information is not applicable and not provided as this is not an AI/ML device that requires a training set.

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