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The Orbus LifeStent LP SDS Biliary Endoprosthesis is indicated for use for the palliation of malignant neoplasms in the biliary tree.

The LifeStent LP SDS Biliary Endoprosthesis consists of a balloon expandable stent which is provided mounted onto a percutaneous transluminal angioplasty (PTA) balloon catheter which acts as the delivery system. The stent is a permanently implanted device used to maintain patency of a major bile duct obstructed by tissue of an impinging tumor. This flexible, balloon expandable stent is made by laser cutting an open lattice design into a 316L stainless steel tube. The stent is supplied mounted onto a PTA balloon catheter, inserted percutaneously to the diseased site, and expanded by balloon inflation. The systems are available with expanded diameters of 4.0, 5.0, 6.0 mm at stent lengths of 18, 36, and 56 mm.

The provided text describes the 510(k) summary for the LifeStent LP SDS Biliary Endoprosthesis, outlining its characteristics, intended use, and substantial equivalence to predicate devices. However, it does not contain information about acceptance criteria, device performance metrics, or any specific study results as would be typically found in clinical trials or performance testing reports for AI/ML devices.

The document is a regulatory submission demonstrating substantial equivalence of a medical device (a biliary stent) to previously approved predicate devices, not an AI/ML product. Therefore, many of the requested categories for AI/ML device studies (such as sample sizes for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, and training set information) are not applicable or present in this context.

Here's an attempt to answer the questions based on the available information, noting where the information is not present or not applicable:

1. Table of Acceptance Criteria and Reported Device Performance

The submission focuses on demonstrating substantial equivalence based on in vitro tests and comparison to predicate devices, rather than predefined acceptance criteria for clinical efficacy or AI performance metrics.

2. Sample Sizes Used for the Test Set and Data Provenance

This information is not provided in the document. The submission references "in vitro tests" but does not specify the sample sizes (e.g., number of stents tested), the specific test protocols, or the origin of any data (as it's in vitro, geographic provenance is less relevant than for patient data).

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of those Experts

This information is not applicable as the document describes a physical medical device and in vitro performance testing, not an AI/ML device requiring expert-established ground truth from medical images or patient data.

4. Adjudication Method Used for the Test Set

This information is not applicable as the document describes in vitro performance testing of a physical medical device, not an AI/ML device with an adjudicated test set.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Its Effect Size

This information is not applicable. An MRMC study is typically for evaluating the impact of an AI/ML device on human reader performance. This document concerns a physical device (stent) and its in vitro performance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

This information is not applicable. This document evaluates a physical medical device, not an algorithm.

7. The Type of Ground Truth Used

For the in vitro performance tests, the "ground truth" would be established by the measurement standards and specifications for the physical properties of the stent and its delivery system (e.g., precise dimensions, force measurements, materials analysis). This is inherent to engineering and material science testing, rather than medical ground truth like pathology or expert consensus.

8. The Sample Size for the Training Set

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

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