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The device is indicated for use as a receptacle for the collection of tissue, organs and calculi during general and laparoscopic procedures.

The EzCatch Tissue Retrieval Bag consists of a long cylindrical tube (Deployer Handpiece) and a polyurethane bag (Tissue Retrieval Bag) that minimizes spillage and intraoperative contamination by isolating and containing specimens. This device is designed for introduction and use through all appropriately sized trocar sleeve (of generally 10mm size). The EzCatch Tissue Retrieval Bag has application for safe, convenient removal of tissue specimens such as the appendix, an ectopic pregnancy, gallbladder, gallstones, lymph nodes, ovaries, small sections of bowel and other tissue structures.

The medical device in question is the Ez Catch Auto, Ez Catch YR, and Ez Catch TR, which are tissue retrieval bags indicated for use as a receptacle for the collection of tissue, organs, and calculi during general and laparoscopic procedures.

Acceptance Criteria and Device Performance:

The document does not explicitly state acceptance criteria in a table format with corresponding reported device performance metrics for the tested parameters. However, it lists several non-clinical tests performed, implying that the device successfully met the internal criteria for these tests to support a claim of substantial equivalence.

Based on the information provided, here's a table summarizing the tests performed, which indirectly represent areas where the device needed to perform acceptably:

Study Information:

The document describes a series of non-clinical tests conducted on the subject device to demonstrate its performance and safety, and to support its substantial equivalence to a predicate device (K201243 - Disposable Specimen Retrieval Bag).

1. Sample sizes used for the test set and the data provenance:
   The document does not explicitly state the specific sample sizes used for each of the non-clinical tests (e.g., number of bags tested for the leak test). It only states that "non-clinical tests were performed in the subject device." The data provenance is implied to be from internal testing conducted by the manufacturer, Veol Medical Technologies Pvt Ltd, given the submission is for their device. The tests are "retrospective" in the sense that they were conducted for regulatory submission, not as a prospective clinical trial.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
   This information is not applicable to the non-clinical tests described. Ground truth and expert consensus are typically associated with clinical studies involving human interpretation or pathology, which are not outlined here. The "ground truth" for non-clinical tests would be the established engineering specifications and regulatory standards (e.g., ISO 10993-1).

3. Adjudication method for the test set:
   Not applicable. Adjudication methods like 2+1 or 3+1 refer to independent review of cases, typically in clinical studies, to establish ground truth or resolve discrepancies in interpretations. For non-clinical tests, performance is measured against predefined, objective specifications.

4. 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. The document describes a medical device (tissue retrieval bag), not an AI-powered diagnostic or assistive tool. Therefore, an MRMC study related to AI assistance is irrelevant to this submission.

5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
   Not applicable, as this is not an AI/algorithm-based device.

6. The type of ground truth used:
   For the non-clinical tests, the "ground truth" is defined by established engineering specifications, performance standards, and regulatory requirements (e.g., ISO 10993-1 for biocompatibility). The success of the tests indicates that the device met these objective criteria.

7. The sample size for the training set:
   Not applicable. This is a medical device, not a machine learning model, so there is no concept of a "training set."

8. How the ground truth for the training set was established:
   Not applicable, as there is no training set for this device.

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