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The Express SD Biliary Monorail Premounted Stent System is indicated for palliation of malignant neoplasms in the biliary tree.

The Express® SD Biliary Monorail® Premounted Stent System (Express SD Biliary) is a traditional Monorail catheter with a balloon near the distal tip. Express SD Biliary consists of a delivery system and a stent that is balloon expandable intended to maintain patency of biliary strictures produced by malignant neoplasms.

This document is a 510(k) summary for the Express® SD Biliary Monorail® Premounted Stent System. It's a premarket notification to the FDA to demonstrate substantial equivalence to an already marketed device, not a study proving the device meets acceptance criteria for a new clinical claim or an AI algorithm.

Therefore, the requested information regarding acceptance criteria, study details, sample sizes, expert involvement, adjudication methods, MRMC studies, standalone performance, ground truth, and training sets is not applicable to this type of document.

This 510(k) pertains to a medical device (a stent system), not an AI/ML powered device. The "study" mentioned here refers to non-clinical tests (first article, shaft, and bond burst testing) to ensure the physical properties of the device (specifically a modified corewire) are equivalent to the predicate device, not clinical performance studies against specific acceptance criteria for a diagnostic or prognostic claim.

Here's why some of the requested information cannot be found:

• Acceptance Criteria & Device Performance Table: This document discusses substantial equivalence to a predicate device based on similar design, materials, and non-clinical testing. It does not provide specific performance metrics or acceptance criteria in the way an AI/ML device submission would (e.g., sensitivity, specificity thresholds).
• Sample Size (Test Set) & Data Provenance: Non-clinical testing of physical components doesn't typically involve "test sets" of patient data or data provenance in the context of clinical AI/ML studies.
• Number of Experts & Qualifications / Adjudication: This is relevant for establishing ground truth in clinical studies, particularly for imaging or diagnostic AI. It's not part of a non-clinical device equivalence assessment.
• MRMC Study / Standalone Performance: These are specific to AI/ML powered diagnostic or screening devices to assess their impact on human readers or their performance without human intervention. This device is a physical stent system.
• Type of Ground Truth: Ground truth (e.g., pathology, clinical outcomes) is established in clinical studies for diagnostic or prognostic purposes. The "ground truth" for this device is its physical integrity and performance as determined by engineering tests (e.g., burst pressure, stiffness).
• Sample Size (Training Set) & Ground Truth for Training Set: These concepts are specific to the development and validation of AI/ML models. This document describes a physical medical device.

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The Express SD Biliary Monorail Premounted Stent System is indicated for palliation of malignant neoplasms in the biliary tree.

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The provided text describes the 510(k) premarket notification for the Express® SD Biliary Monorail® Premounted Stent System. This document does not describe an AI/ML-driven medical device, but rather a traditional medical device (biliary stent). Therefore, much of the information typically requested for AI/ML device evaluations (such as acceptance criteria, sample sizes for test/training sets, expert qualifications, adjudication methods, MRMC studies, standalone performance, and ground truth establishment for AI models) is not applicable or present in this document.

However, I can extract the relevant information regarding the device's acceptance, testing, and comparison to a predicate device.

Device Name: Express® SD Biliary Monorail® Premounted Stent System
Intended Use/Indications for Use: Palliation of malignant neoplasms in the biliary tree.

Acceptance Criteria and Device Performance

The document functions as a 510(k) summary, which establishes substantial equivalence to a predicate device rather than setting specific performance acceptance criteria like sensitivity/specificity for an AI model.

The "acceptance criteria" here are implicitly related to demonstrating that the new device is as safe and effective as the predicate device, especially regarding its Magnetic Resonance (MR) compatibility, which was the focus of the non-clinical testing.

Study Details (as inferable from the document):

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

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

   • Sample Size: Not explicitly stated. The document mentions "Bench testing was performed" but does not detail the number of stents or test configurations used.
   • Data Provenance: The testing was "non-clinical bench testing" performed by Boston Scientific Corporation.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. This is a physical device, and the testing described is non-clinical (bench testing) for MR compatibility, not expert-adjudicated clinical performance.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable as it's not a clinical study requiring expert adjudication of results.

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 not an AI-assisted device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an AI device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable in the context of AI models. For MR compatibility, the "ground truth" would be established by validated test methods and standards for assessing electromagnetic compatibility and material safety in MR environments.

8. The sample size for the training set: Not applicable. This is not an AI/ML device that requires a training set.

9. How the ground truth for the training set was established: Not applicable.

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