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The Prestige Coil System is indicated for arterial and venous embolizations in the peripheral vasculature.

The Prestige Coil System is intended for use in the peripheral vasculature to endovascularly obstruct or occlude blood flow in vascular abnormalities of the peripheral vessels.

The Prestige Coil System is a product family of embolic coils with associated delivery system components. These devices are angiographically delivered through the vasculature to embolize peripheral vascular abnormalities. The devices are to be permanently placed in the peripheral vessels to create blood stasis, reducing flow into the anomaly, and thrombosing the target site.

The provided FDA 510(k) Clearance Letter for the Prestige Coil System (Prestige Packing Coil Line Extension) does not describe a study involving an AI/Machine Learning device, human readers, or image interpretation. Instead, it describes a vascular embolization device and its mechanical and physical performance testing.

Therefore, many of the requested points in your prompt are not applicable to this document, as they relate to studies of AI performance or human reader studies in diagnostic imaging, which is not the subject of this 510(k) clearance.

However, I can extract the relevant information from the provided text regarding the device's acceptance criteria and the performance testing conducted.

Here's the breakdown based on the provided document:

Device: Prestige Coil System (Prestige Packing Coil Line Extension)

Type: Vascular Embolization Device (mechanical medical device)
Purpose: Arterial and venous embolizations in the peripheral vasculature.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: The document repeatedly mentions "test samples" but does not specify the exact number of samples used for each test (Visual Inspection, Dimensional Inspection, Resistance Check, and Simulated Use).
• Data Provenance: Not applicable in the context of clinical data. This refers to bench testing involving physical device samples. No specific country of origin or retrospective/prospective data collection is mentioned as this relates to device manufacturing and testing, not patient data.

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

• Not Applicable. "Ground truth" in this context refers to the defined engineering specifications and performance characteristics of the device. These are established through design controls, manufacturing standards, and engineering principles, not through expert consensus on medical image interpretation. The "experts" would be engineers and quality control personnel involved in the device's design and testing.

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

• Not Applicable. This is a concept related to consensus building among human readers (e.g., radiologists) for establishing ground truth in image-based studies. For physical device bench testing, the "adjudication" is based on objective measurements against pre-defined engineering specifications and Pass/Fail criteria. No multi-reader adjudication method applies here.

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 document describes a vascular embolization device, not an AI/Machine Learning diagnostic device. Therefore, no MRMC study or AI assistance was involved.

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

• Not Applicable. This is a mechanical device, not an algorithm. Standalone performance refers to the device's inherent functional capabilities as demonstrated in the bench tests, which are independent of a human operator's actions beyond following the instructions for use during the test.

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

• The "ground truth" for this device's performance testing is based on pre-established engineering specifications, design requirements, and manufacturing tolerances for the physical device. The device passes if its measured physical and functional characteristics meet these objective, pre-defined criteria. There is no biological "ground truth" (like pathology or outcomes data) in this specific submission, as it focuses on demonstrating the substantial equivalence of a modified mechanical device through bench testing.

8. The sample size for the training set

• Not Applicable. This applies to AI/Machine Learning models, not physical medical devices undergoing bench testing. The device itself is not "trained."

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

• Not Applicable. As above, this applies to AI/Machine Learning models.

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The Prestige Coil System is indicated for arterial and venous embolizations in the peripheral vasculature.

The Prestige Coil System is a series of specialized coils that are inserted into the vasculature under angiographic visualization to embolize peripheral vascular anomalies. The system consists of an embolization coil implant comprised of platinum/tungsten, affixed to a delivery pusher to facilitate insertion into the hub of a microcatheter. The system is available in various shapes, lengths, and sizes. The devices are to be placed into anomalies to create blood stasis, reducing flow in the target vasculature, and inducing thrombosis. Upon positioning coils into the vasculature, the coils are thermally detached from the delivery pusher in serial manner until the target vasculature is occluded.

The provided text is a 510(k) summary for the Prestige Coil System, a vascular embolization device, which explicitly states that it is not an AI/ML powered device. Therefore, it does not involve any of the AI/ML related concepts you asked about, such as training sets, test sets, ground truth establishment, MRMC comparative effectiveness studies, or AI performance metrics.

However, I can still extract the acceptance criteria and information about the studies performed for this non-AI medical device.

1. Table of Acceptance Criteria and Reported Device Performance

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

As this is a non-AI/ML device, the concept of a "test set" in the context of AI does not directly apply. The studies mentioned are bench tests and non-clinical device assessments. Specific sample sizes for each test are not provided in this summary. The data provenance is from non-clinical bench testing performed by the manufacturer (Balt USA, LLC) to demonstrate substantial equivalence to a predicate device.

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

Not applicable, as this is not an AI/ML device and does not involve establishing ground truth through expert review for a test set.

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

Not applicable, as this is not an AI/ML device and does not involve adjudication of expert assessments for a test set.

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, as this is not an AI/ML device and does not involve human readers or AI assistance.

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

Not applicable, as this is not an AI/ML device and does not have an algorithm to be evaluated in standalone mode.

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

Not applicable, as this is not an AI/ML device. The "ground truth" for the device's performance in these non-clinical tests is based on pre-defined acceptance criteria derived from device specifications and recognized standards (e.g., ISO 10993-1).

8. The sample size for the training set

Not applicable, as this is not an AI/ML device and therefore no training set was used.

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

Not applicable, as this is not an AI/ML device and therefore no training set was used or ground truth established for it.

Ask a specific question about this device