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Cordis Angiographic Catheters with Marker Bands are designed to provide angiographic visualization and linear measurement of the vasculature when combined with the delivery of radiopaque contrast media to selected sites in the vascular system.

The SUPER TORQUE® MB Angiographic Catheter is a thin plastic tube which is inserted into an artery through a small incision in the skin. The catheter is guided to the area being examined, and contrast material is injected through the tube and images are captured using a small dose of ionizing radiation (x-rays). Each SUPER TORQUE® MB Angiographic Catheter consists of a braided Polyurethane body and a non-braided Polyurethane tip section having multiple, radiopaque marker bands.

This document is a 510(k) Premarket Notification for a medical device called the SUPER TORQUE® MB Angiographic Catheter. It is not an AI/ML device, and therefore the concepts of acceptance criteria and a study to prove the device meets those criteria (in the context of AI/ML performance metrics) do not apply in the traditional sense.

The document describes a submission seeking substantial equivalence to a legally marketed predicate device (K992347). For such devices, the "acceptance criteria" are generally that the new device is as safe and effective as the predicate device. This is typically demonstrated through a comparison of technological characteristics, and often, non-clinical (bench) testing. Clinical studies are not always required if substantial equivalence can be shown otherwise.

Here's why the requested information cannot be provided in the context of AI/ML device evaluation:

• No AI/ML Component: The SUPER TORQUE® MB Angiographic Catheter is a physical medical device (a thin plastic tube for angiography), not a software algorithm or an AI/ML system.
• No "Performance Metrics" in the AI Sense: The performance of this device is assessed by its physical characteristics, material properties, and functionality (e.g., ability to deliver contrast, radiopacity of marker bands), not by metrics like sensitivity, specificity, AUC, or reader performance improvement often used for AI.
• No "Training/Test Sets" for AI: The concept of training sets and test sets with ground truth established by experts is irrelevant for a physical catheter.

However, I can extract and present the available information in a slightly adapted format, focusing on how substantial equivalence was demonstrated, which is the closest analog to "meeting acceptance criteria" for this type of device.

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

For this physical angiographic catheter, "acceptance criteria" relate to demonstrating substantial equivalence to a predicate device. The performance is assessed through bench testing and comparison of fundamental technological characteristics.

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

Not applicable in the context of AI/ML. For a physical device, testing is typically done on manufactured samples. The document states "No new testing was required to be conducted due to addition of contraindication in the IFU." It also mentions "minor manufacturing updates were made, additional biocompatibility testing was performed, and additional sterilization facilities were qualified." This implies some level of physical testing (bench testing) on device samples, but specific sample sizes for these tests are not detailed in this submission. Data provenance would be from laboratory test reports.

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

Not applicable. This is not an AI/ML device requiring expert adjudication for ground truth.

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

Not applicable. This is not an AI/ML device requiring expert 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 not an AI/ML device. No MRMC study was performed. The document explicitly states: "No clinical data was required in support of the proposed change to the predicate device cleared under K992347."

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

Not applicable. This is not an AI/ML device, so there is no algorithm to evaluate in standalone mode.

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

Not applicable. For a physical device, "ground truth" would be engineering specifications and validated test methods for material properties, dimensions, and mechanical performance.

8. The sample size for the training set

Not applicable. This is not an AI/ML device.

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

Not applicable. This is not an AI/ML device.

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