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The Well Lead Extraction Bag is intended for use by qualified surgeons in tissue extraction procedures during laparoscopic surgery.

The Well Lead Extraction Bag is used for removal of tissue specimens during a suitable laparoscopic surgery.The device consists of a cylindrical sheath, a pusher and a polyurethane bag that minimizes spillage and intraoperative contamination by isolating and containing specimens. The bag is made of biocompatible high strength PU material, it is transparent and soft. which makes a qood visuality.

The device is composed of biologically safe materials. It is supplied sterile and intended for single use only. It's easy to enter, open, close and exit, higher efficiency, and different type and size available. It is offerd in 4 types: Type B, Type C, Type D and range in bag volume from 200ml for different surgery needs. The well thought-out rang of types and sizes are suitable for all laparoscopic procedures. The main differences between all types are the deployment system and operation method.

The provided text describes a 510(k) submission for the "Well Lead Extraction Bag" and focuses on demonstrating substantial equivalence to predicate devices rather than providing a detailed study proving the device meets specific acceptance criteria in a clinical setting. Therefore, many of the requested elements (like sample size for test sets, expert ground truth, MRMC studies, standalone performance, training set details) are not explicitly present in the provided document, as they are not typically required for a 510(k) for this type of device.

However, I can extract information related to non-clinical performance testing and what constitutes the acceptance criteria as described in the document.

1. Table of Acceptance Criteria and Reported Device Performance

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

The document mentions "Testing datas and results are included in this submission" but does not specify the sample size for the non-clinical performance tests (e.g., how many bags were tested for leakage, tensile strength, etc.).
The data provenance is implied to be from the manufacturer's internal testing as part of their 510(k) submission, likely conducted in China where the manufacturer (WELL LEAD MEDICAL CO., LTD.) is located. The tests are non-clinical, so terms like "retrospective or prospective" do not directly apply in the same way they would to human subject studies.

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)

Not applicable/Not provided. For non-clinical performance testing of a medical device like an extraction bag, ground truth is established through standardized engineering and laboratory testing protocols, not by expert human graders. The "experts" involved would be technicians or engineers conducting the tests and interpreting the results according to the specified standards (e.g., ISO standards for biocompatibility).

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

Not applicable/Not provided. Adjudication methods like 2+1 or 3+1 are used in clinical trials or studies involving human assessment where there might be disagreements in interpretation. For objective, non-clinical performance tests, results are typically quantitative and assessed against a pre-defined pass/fail threshold, not through an adjudication process.

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 device is an extraction bag, a physical surgical tool, not an AI-powered diagnostic or assistive tool for human readers. Therefore, an MRMC study comparing human reader performance with and without AI assistance is entirely irrelevant and was not conducted.

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

No. This question applies to AI algorithms. As mentioned above, the device is a physical surgical tool, not an AI algorithm.

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

For the non-clinical performance tests:

• Engineering specifications and recognized standards (e.g., criteria for what constitutes a "leak," a specified "rated volume," or a minimum "tensile strength").
• Biocompatibility standards (ISO 10993 series) define the ground truth for assessing non-toxic, non-irritating, and non-sensitizing properties of materials.

8. The sample size for the training set

Not applicable/Not provided. This question pertains to machine learning models. The Well Lead Extraction Bag is a physical device, so there is no "training set" in this context.

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

Not applicable/Not provided. As there is no training set for this device, this question is irrelevant.

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