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510(k) Data Aggregation
(270 days)
The MAGIC Flow-Dependent Microcatheter is intended to access the peripheral and neuro vasculature for the controlled selective infusion of physician-specified embolization materials and diagnostic materials such as contrast media.
The MAGIC Flow-Dependent Microcatheter is designed with progressive suppleness and a rigid proximal shaft to allow control and navigability in the vascular system. By their diameter and progressive suppleness features, these catheters are specifically designed for catheterization of small diameter, sinuous distal vessels.
The catheter body and its distal tip (ring) are radiopaque to provide visibility under fluoroscopy. The MAGIC Flow-Dependent Microcatheter has an external hydrophilic coating which provides a lubricious surface during use.
A coated mandrel is included inside the MAGIC Flow-Dependent Microcatheter to provide support during product preparation and insertion through the guide catheter.
The MAGIC Flow-Dependent Microcatheter and accompanying support mandrel are provided sterile, nonpyrogenic, and intended for single use only.
The provided document is a 510(k) Pre-market Notification for the MAGIC Flow-Dependent Microcatheter (K213435). This document does NOT contain information about a study proving the device meets acceptance criteria in the context of an AI/ML medical device. Instead, it details a comparison between the subject device and predicate/reference devices to establish substantial equivalence.
The "acceptance criteria" and "device performance" mentioned in the document relate to bench testing done to demonstrate the subject device's ability to deliver embolic materials. This is not for software performance but for the physical device's function. No AI/ML component is mentioned in the device description or testing.
Therefore, I cannot provide the requested information for an AI/ML device study.
However, based on the provided document, here is the information related to the physical device's performance:
1. Table of Acceptance Criteria and Reported Device Performance (Non-AI/ML Device)
| Acceptance Criteria (related to bench testing) | Reported Device Performance |
|---|---|
| Ability to successfully deliver an array of embolic materials in a tortuous anatomical model. | Pass |
2. Sample size used for the test set and the data provenance:
- Sample Size: Not specified in the document. The description only states "The subject device was evaluated..."
- Data Provenance: The test was non-clinical bench testing, meaning it was conducted in a laboratory setting, not with patient data.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
This information is not applicable. For physical device bench testing, "ground truth" is typically established by engineering specifications and direct physical measurement/observation against those specifications, not by expert consensus in diagnostic interpretation.
4. Adjudication method for the test set:
Not applicable. The testing was a direct performance evaluation against predefined criteria, not an interpretive task requiring adjudication.
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 physical medical device (microcatheter), not an AI/ML algorithm that assists human readers.
6. 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 AI/ML algorithm.
7. The type of ground truth used:
For the bench testing, the "ground truth" would be the successful delivery of embolic materials as defined by engineering and performance specifications in the tortuous anatomical model.
8. The sample size for the training set:
Not applicable. This is a physical medical device, not an AI/ML algorithm that requires a training set.
9. How the ground truth for the training set was established:
Not applicable. This is a physical medical device, not an AI/ML algorithm.
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(28 days)
The Rebar™ Micro Catheter is intended for the delivery of interventional devices or contrast media into the vasculature of the peripheral and neuro anatomy.
The Rebar" Micro Catheter is an endhole, single-lumen catheter designed to be introduced over a steerable guidewire into the vasculature. The proximal end of the catheter incorporates a standard luer adapter to facilitate the attachment of accessories. The catheter has a semi-rigid proximal shaft which transitions into the flexible distal shaft to facilitate the advancement of the catheter in the anatomy. Single or dual radiopaque markers at the distal end facilitate fluoroscopic visualization. The outer surface of the catheter is coated to increase lubricity.
The provided text does not describe a study involving a device that uses AI or machine learning. Instead, it describes a 510(k) premarket notification for a medical device called the "Rebar™ Micro Catheter." This submission is focused on demonstrating substantial equivalence to an existing predicate device based on material changes (e.g., to the hub material and adhesive) and associated non-clinical bench testing.
Therefore, I cannot provide the information requested in your prompt regarding acceptance criteria and a study proving an AI/ML device meets them, as the provided document pertains to a traditional, non-AI medical device clearance.
The document discusses:
- Device: Rebar™ Micro Catheter (a vascular microcatheter)
- Purpose: Delivery of interventional devices or contrast media into the vasculature.
- Regulatory Pathway: 510(k) premarket notification, aiming for substantial equivalence to a previously cleared Rebar™ Micro Catheter (K093750).
- Changes: Primarily changes to the material of the catheter hub (from Polypropylene to Trogamid) and the adhesive used.
- Proof of Equivalence: Non-clinical bench testing and biocompatibility data, rather than clinical trials or AI/ML performance studies.
The acceptance criteria listed are for physical and functional properties of the catheter (e.g., hub integrity, pressurization, tensile strength) and not related to AI/ML performance metrics like accuracy, sensitivity, or specificity. There is no mention of a test set, ground truth acquisition involving experts, MRMC studies, or training sets, as these concepts are not applicable to the type of device and study described.
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