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The IntraStent® Mega™ LD (Large Diameter) Stent - Biliary Indication and the IntraStent® Max™ LD (Large Diameter) Stent - Biliary Indication are intended as a palliative treatment of malignant neoplasms in the biliary tree.

The IntraStent Mega and Max LD Stents are balloon expandable stainless steel stents with an open lattice design. The device is provided unmounted, to be manually crimped onto a noncompliant PTA balloon catheter for biliary stent expansion of choice by the physician. Upon balloon inflation the crimped stent expands to conform to the duct inner luminal surface and retains the expanded state upon balloon deflation.

Medical Device: IntraStent Mega LD and IntraStent Max LD Stents

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not specify any sample sizes for a human-based test set or any clinical data provenance. The study described is entirely based on bench testing of the devices.

3. Number of Experts Used to Establish Ground Truth and Qualifications

Not applicable. This was a bench test study, not a clinical study involving experts establishing ground truth from patient data.

4. Adjudication Method for the Test Set

Not applicable. There was no clinical test set requiring adjudication.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. The submission focuses on device modifications and bench testing for substantial equivalence, not clinical effectiveness studies comparing human readers with and without AI assistance.

6. Standalone (Algorithm Only) Performance Study

Not applicable. This device is a physical medical implant (biliary stent), not a software algorithm or AI. The performance reviewed is mechanical/physical, not algorithmic.

7. Type of Ground Truth Used

The "ground truth" for this submission was the performance characteristics, materials, indication for use, and technological characteristics of the predicate devices (IntraStent™ Stent, K991929, and IntraStent DoubleStrut LD, K993904). The modified devices were compared against these established characteristics of the legally marketed predicate devices to demonstrate substantial equivalence.

8. Sample Size for the Training Set

Not applicable. This submission concerns physical medical devices, not an AI or algorithm that would require a training set.

9. How the Ground Truth for the Training Set Was Established

Not applicable. There was no training set in the context of an AI or algorithm.

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The IntraStent™ DoubleStrut™ LD Biliary Stent is indicated as a palliative treatment for malignant neoplasms in the biliary tree.

The IntraStent™ DoubleStrut™ LD is a balloon expandable stainless steel stent with an open cell design. The stent is provided unmounted, to be manually crimped onto an open lumen PTA balloon catheter for biliary stent expansion of choice by the physician. Upon balloon inflation the crimped stent expands to conform to the duct inner luminal surface and retains the expanded state upon balloon deflation.

The provided text describes a 510(k) submission for the IntraStent™ DoubleStrut™ LD Biliary Stent, focusing on demonstrating substantial equivalence to predicate devices, rather than a study proving the device meets acceptance criteria from a clinical outcome perspective.

Here's an analysis based on the information provided, specifically addressing the requested points:

1. Table of Acceptance Criteria and Reported Device Performance

The submission does not define specific clinical acceptance criteria in terms of performance metrics (e.g., patency rates, complication rates). Instead, the "acceptance criteria" are implied as demonstrating substantial equivalence through bench tests to established predicate devices.

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

The submission describes bench tests and pyrogenicity testing, not clinical trials with patient data.

• Test Set Sample Size: Not explicitly stated for bench tests (e.g., number of stents tested). For pyrogenicity, it's mentioned as "lot to lot basis," implying samples from manufacturing lots.
• Data Provenance: Not applicable in the context of clinical data (no country of origin or retrospective/prospective clinical data mentioned). The data provenance is from internal bench testing conducted by the manufacturer.

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

Not applicable. The ground truth for bench tests is the engineering specification and performance of the predicate device. There is no mention of experts establishing a "ground truth" for the test set in the sense of clinical diagnoses or interpretations.

4. Adjudication Method for the Test Set

Not applicable. This concept primarily applies to human reader studies or clinical trials where expert consensus is needed to resolve discrepancies. Bench tests rely on objective physical measurements and compliance with engineering specifications.

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 medical device (stent), not an AI-powered diagnostic or decision-support system. Therefore, MRMC studies comparing human readers with and without AI assistance are not relevant to this submission.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Not applicable. This is a medical device (stent), not an algorithm or AI system.

7. The Type of Ground Truth Used

The "ground truth" for this 510(k) submission is the performance and characteristics of the legally marketed predicate devices (IntraStent™ DoubleStrut™ K991929 and Cordis Corporation PALMAZ™ and PALMAZ-SCHATZ™ stents). The testing (bench tests, pyrogenicity) aimed to demonstrate that the new device's performance aligns with these established predicates.

8. The Sample Size for the Training Set

Not applicable. This is not an AI or machine learning device requiring a training set.

9. How the Ground Truth for the Training Set Was Established

Not applicable. As above, this is not an AI or machine learning device.

Summary of the Study Proving Acceptance Criteria:

The study proving the device meets the "acceptance criteria" (understood as demonstrating substantial equivalence to predicate devices) primarily involved:

• Bench Tests: These were conducted to verify that the IntraStent™ DoubleStrut™ LD met the "same performance characteristics" as the predicate IntraStent™ DoubleStrut™ (K991929). The submission states "Performance testing (bench) further supports a substantial equivalence claim." No specific details about the types of bench tests (e.g., radial force, fatigue, crimp retention) or their results are provided in this summary.
• Pyrogenicity Testing: This was performed on a "lot to lot basis" to support the claim that the device is non-pyrogenic.

The conclusion is that "The collective evidence therefore provides assurance that the IntraStent™ meets the requirements that are considered acceptable for the intended use" by demonstrating its "identical" nature in materials, indication for use, and technological characteristics, and by showing similar performance in bench tests, to its predicate devices.

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The IntraStent™ Biliary Stent is indicated as a palliative treatment for malignant neoplasms in the biliary tree.

The IntraStent™ is a balloon expandable stainless steel stent with an open attisce design. The device is provided unmounted, to be manually crimped onto a noncompliant PTA I he device is provided uninounced, to be manadis computer luminal surface and inflation the crimped stent expands to conform to the duct inner luminal surface and retains the expanded state upon balloon deflation.

Here's a breakdown of the acceptance criteria and the study information for the IntraStent™ Biliary Catheter based on the provided 510(k) summary:

This device is not a typical AI/ML-enabled medical device, so many of the questions asked (like MRMC study, ground truth for training set, effect size of AI, etc.) are not applicable in this context. This is a physical medical device (a stent) and its submission focuses on demonstrating substantial equivalence to already marketed devices through bench testing and material comparisons.

Acceptance Criteria and Reported Device Performance

Study Information

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

   • Test Set Sample Size: Not explicitly stated as a numerical sample size for a "test set" in the context of clinical trials or AI/ML validation. The "test" mentioned refers to bench tests.
   • Data Provenance: Bench testing data would be generated in a laboratory setting, likely in the US (where the company is based). It's a prospective generation of data specifically for this submission.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth as typically understood for AI/ML or clinical imaging studies (expert consensus) is not relevant here. The "ground truth" for bench testing is defined by engineering specifications and predicate device performance.

3. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable. This concept is for clinical or imaging review, not bench testing.

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. This is a physical medical device (a stent), not an AI-enabled diagnostic or assistive system.

5. 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.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): The "ground truth" for this submission is based on the established performance characteristics and design of predicate devices, combined with engineering specifications and bench testing results. The goal is substantial equivalence, meaning the new device performs as well as, or comparably to, already approved devices.

7. The sample size for the training set: Not applicable. This is not an AI/ML device where a "training set" in that sense would exist.

8. How the ground truth for the training set was established: Not applicable. See point 7.

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