Search Results

These products are used in combination with an applicable endoscope to perform the endoscopic treatments for the target site in the gastrointestinal tract, such as ablation, incision, cauterization, coagulation and avulsion of tissue and arrest of bleeding, and to inject saline or submucosal injection agent for endoscopic surgery into the submucosal layer in the gastrointestinal tract, which is exposed after dissection, under the management of physicians in medical facilities. Never use this product for any other purpose.

FUJIFILM Diathermic Slitter (FlushKnife) is an electrosurgical instrument that removes tissue and controls bleeding by use of high-frequency ("HF") electrical current. The device is available with either a needle or ball tip slitter and comes in a variety of sizes.

This document is a 510(k) Premarket Notification from the FDA regarding a medical device. It does not contain information about an AI/ML medical device or a clinical study with human subjects, therefore, most of the requested information cannot be extracted from the document. The document describes a Diathermic Slitter (FlushKnife) used for endoscopic treatments in the gastrointestinal tract. This is a physical, electrosurgical instrument, not an AI or software-based device.

Therefore, many of the requested fields related to AI/ML device performance, such as sample size for test sets, ground truth establishment, expert adjudication, MRMC studies, and training set details, are not applicable to this document.

However, I can provide information based on the "Performance Data" section regarding the device's technical validation.

Here's what can be extracted based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The document states that the device met pre-defined acceptance criteria for all tests. Specific numerical acceptance criteria or performance metrics are not detailed in this summary; rather, it refers to compliance with standards and successful completion of tests.

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

• Sample Size: Not specified for any of the performance tests. The document refers to "bench testing" and evaluations against standards, which typically involve a specified number of samples, but these numbers are not disclosed.
• Data Provenance: The testing appears to be conducted by the manufacturer as part of their submission for regulatory clearance. The document doesn't specify country of origin for data but states the manufacturer is FUJIFILM Corporation, located in Japan. The tests are described as "bench testing," implying a laboratory, likely prospective testing for the purpose of the submission.

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

• Not Applicable. This document describes a traditional electrosurgical device, not an AI/ML device that requires expert-established ground truth for image interpretation or diagnosis. Ground truth, in this context, refers to the physical properties and performance characteristics of the device being measured against engineering specifications and regulatory standards.

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

• Not Applicable. As this is not an AI/ML device relying on human interpretation, an adjudication method for test set ground truth is not relevant.

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 not an AI/ML device and therefore no MRMC study or assessment of human reader improvement with AI assistance was conducted or is relevant.

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

• No. This is not an algorithm or software device. Its performance is evaluated intrinsically as a physical piece of medical equipment.

7. The type of ground truth used

• Technical Specifications and Consensus Standards: The "ground truth" for this device's performance relies on its ability to meet engineering design specifications and comply with recognized consensus standards for electrical safety, biocompatibility, sterility, and device-specific functionalities (e.g., slitter length, conductivity). This is established through laboratory testing and verification against pre-defined performance metrics, rather than expert consensus on diagnostic interpretations or clinical outcomes data in a comparative study.

8. The sample size for the training set

• Not Applicable. This device uses traditional engineering principles, not machine learning, and therefore has no "training set."

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

• Not Applicable. There is no training set for this type of device.

Ask a specific question about this device

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.

Ask a specific question about this device