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510(k) Data Aggregation
(24 days)
COOK MREYE EMBOLIZATION COILS
The Cook MReye Embolization Coil is used for peripheral arterial and venous vessel embolization procedures.
The Cook MReye Embolization Coil is a device used for peripheral arterial and venous vessel embolization procedures. The coil is pre-loaded into a cartridge to facilitate delivery into a microcatheter, which then delivers the coil to the embolization site.
The provided document is a 510(k) summary for a medical device modification, specifically for the Cook MReye Embolization Coils. It focuses on demonstrating substantial equivalence to a predicate device rather than a clinical study evaluating a novel AI algorithm's performance.
Therefore, many of the requested categories (e.g., sample size for test set, number of experts, adjudication method, MRMC study, standalone performance, training set size) are not applicable to this type of regulatory submission in this specific document. The document describes engineering and performance testing of the device itself, not an AI component.
Here's an analysis based on the information available:
1. A table of acceptance criteria and the reported device performance
Acceptance Criteria (Inferred from types of tests) | Reported Device Performance (Summary) |
---|---|
Coil deformation testing | Met applicable design and performance requirements. |
Delivery friction testing | Met applicable design and performance requirements. |
Embolization fiber pull-out testing | Met applicable design and performance requirements. |
Cannula to catheter delivery testing | Met applicable design and performance requirements. |
Study Proving Device Meets Acceptance Criteria:
The study is described as "Test Data" presented to demonstrate that the Cook MReye Embolization Coils meet applicable design and performance requirements. The specific study details are not provided in this summary, but the types of tests performed are listed.
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample Size: Not specified in the provided document. This would typically be detailed in the full test reports, which are not included here.
- Data Provenance: Not specified. Given these are engineering and performance tests of a physical device, the "data provenance" would refer to the testing conditions and environments, which are not outlined. It is most likely laboratory-based testing conducted by the manufacturer.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
- Not Applicable. This document describes performance testing of a physical medical device (embolization coils), not an AI algorithm requiring expert ground truth for image interpretation or diagnosis. The "ground truth" here would be the physical properties and performance characteristics measured in a laboratory setting.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not Applicable. See point 3.
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
- No. This document does not describe an MRMC study. This type of study is relevant for AI-powered diagnostic or assistive tools, not for a physical device like an embolization coil.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not Applicable. There is no AI algorithm component described in this document. This is a physical medical device.
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)
- Physical/Engineering Measurement Standards: The "ground truth" for this device's performance would be established by industry standards, internal design specifications, and validated measurement techniques for physical properties (e.g., tensile strength, friction coefficients, dimensional tolerances). It is not based on expert consensus, pathology, or outcomes data in the clinical sense mentioned in the question.
8. The sample size for the training set
- Not Applicable. There is no AI algorithm being "trained" described in this document.
9. How the ground truth for the training set was established
- Not Applicable. See point 8.
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