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The HILZO Esophageal Stents are indicated for use in esophageal strictures caused by intrinsic malignant tumors.

The HILZO Esophageal Stents are partially covered and fully covered, self-expanding tubular prosthesis designed to maintain patency of esophageal strictures. The HILZO Esophageal stents are available loaded on two styles of delivery devices, Over the Wire (OTW) and Through the Scope (TTS). The OTW delivery devices are 14Fr and the TTS is 10.5Fr to enable delivery through the working channel of an endoscope. The stents are made of Nitinol wire and are designed to prevent stent migration due to peristaltic motion and tumor in-growth. The stents are available in a variety models, diameters and lengths.

The document provided is a 510(k) Premarket Notification from the FDA for a medical device: the Hilzo Esophageal Stents. This type of submission is for demonstrating "substantial equivalence" to a legally marketed predicate device, not for establishing novel safety and effectiveness through clinical trials or performance studies involving complex metrics like those for AI/ML devices (e.g., sensitivity, specificity, clinical workflow improvement).

Therefore, the vast majority of the requested information regarding acceptance criteria, study design, ground truth establishment, expert adjudication, MRMC studies, and training set details are not applicable to this particular document. This document focuses on demonstrating that the new device is as safe and effective as a previously cleared device, primarily through bench testing comparing physical and mechanical properties, and biocompatibility.

Here's what can be extracted and what cannot:

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

The document provides a comparative table where "acceptance criteria" are implicitly defined by similarity to the predicate device's performance, often with an explicit acceptance range (e.g., "fell within the +/- 5% difference acceptance criteria").

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

The document mentions "extensive biocompatibility data" and various "Non-Clinical Performance Testing" types (shelf-life, expansion force, compression force, etc.). However, it does not specify sample sizes for these tests. The data provenance would be that of the manufacturer's internal testing. It's retrospective in the sense that the tests were completed before the submission. No country of origin for specific test data is provided, but the manufacturer is Thoracent, Inc. in Huntington, NY, USA.

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

This is not applicable. For this type of device (a physical medical implant), "ground truth" is established through engineering and biological performance standards, not expert medical opinion on a data set. The device is evaluated on its physical and mechanical properties and biocompatibility.

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

Not applicable. There is no expert adjudication process for bench testing results in the way there would be for image interpretation in an AI/ML study.

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 medical device (stent), not an AI/ML diagnostic or assistive software. MRMC studies are used for evaluating the impact of AI on human reader performance for diagnostic tasks.

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

Not applicable. This is a physical medical device, not an algorithm.

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

For this device, "ground truth" is established through:

• Engineering specifications and standards: For mechanical properties like expansion and compression force, dimensions, tensile strength, kink resistance.
• Biocompatibility standards (e.S. ISO 10993): For biological safety, ensuring the materials are not toxic or harmful to the body.
• Sterilization validation: Ensuring the device can be terminally sterilized.
• MR safety standards: To determine if the device is safe for patients undergoing MRI.

8. The sample size for the training set

Not applicable. This is a physical medical device, not an AI/ML model that requires a training set.

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

Not applicable. As above, no training set for an AI/ML model exists for this device.

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