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The HydroFrame HydroCoil Embolic System (HES) is intended for the endovascular embolization of intracranial aneurysms and other neurovascular abnormalities such as arteriovenous malformations and artiovenous fistula. The HES is also intended for vascular occlusion of blood vessels within the neurovascular system to permanently obstruct blood flow to an aneurysm or other vascular malformation and for arterial and venous embolization in the peripheral vasculature.

The HydroFrame coils consist of implant coil made of platinum alloy with inner hydrogel core. The coils are designed in 3D spherical structure in various loop with miller hydroget core. he a V-Trak™ MCS delivery pusher via a polymer fillament. The delivery pusher contains radiopaque positioning markers at the distal end. The proximal end is inserted into a hand held battery powered V-Grip™ Detachment Controller. The proximal end is niscreed into nell onecry powered. Costroller Controller.

This document describes the HydroFrame - HydroCoil Embolic System (HES), a neurovascular embolization device. The information provided is from a 510(k) summary (K090357) for FDA clearance. The "acceptance criteria" and "study that proves the device meets the acceptance criteria" in this context refer to the performance tests conducted to demonstrate substantial equivalence to previously cleared predicate devices, not a clinical trial with specific performance metrics like sensitivity/specificity.

Here's a breakdown of the requested information based on the provided text:

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

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

The document describes bench testing, which typically does not involve human subjects or clinical data. The "test set" in this case would refer to the physical units of the HydroFrame coils subjected to the various bench tests. The specific sample sizes for each test are not provided in this summary.

The data provenance is MicroVention, Inc., Aliso Viejo, California, U.S.A. The data is from prospective bench tests performed by the manufacturer to demonstrate the device's physical and functional properties.

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

This question is not applicable to the type of testing described. Bench testing is a physical verification process against established engineering and design specifications. It does not involve medical experts establishing "ground truth" in the way clinical studies do (e.g., diagnosing a condition). The "ground truth" for these tests would be the pre-defined engineering specifications and performance targets for each test, which are determined by the manufacturer based on their design requirements and comparison to predicate devices.

4. Adjudication method for the test set

This is not applicable to bench testing as described. Adjudication methods (like 2+1, 3+1) are typically used in clinical studies or image review where multiple human readers are involved in making subjective assessments or diagnoses, and their disagreements need to be resolved. Bench tests involve objective measurements and comparisons against defined criteria.

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, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. This device is a physical medical implant (an embolic coil), not an AI-powered diagnostic or assistive tool. Therefore, the concept of human readers improving with or without AI assistance does not apply.

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

No, a standalone algorithm performance study was not done. This device is a physical medical device, not an algorithm or AI system.

7. The type of ground truth used

The "ground truth" for the bench tests would be the established engineering specifications, design parameters, and performance criteria for each test (e.g., specific dimensions, tensile strengths, detachment forces, gel expansion rates). These criteria are derived from the device's design, manufacturing standards, and the performance characteristics of its predicate devices.

8. The sample size for the training set

This question is not applicable. There is no "training set" in the context of this device's testing, as it is a physical product and not an AI/machine learning model.

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

This question is not applicable for the same reason as point 8.

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