Search Results

The product (Finecross™ MG) is intended to be percutaneously introduced into blood vessels and support a guide wire while performing PCI (percutaneous coronary intervention). The product is also intended for injection of radiopaque contrast media for the purpose of angiography.

FINECROSS MG consists of a catheter shaft, a hub and an anti-kink protector. The catheter shaft has reinforcing braided mesh, thus achieving the high shaft strength and anti-kink characteristics. The shaft has gradual hardness change from the proximal to the distal portion. This is achieved by joining outer layers of material with different hardness. By using polytetrafluoroethylene (PTFE) as the inner layer, high inner face mobility has been achieved. The outer surface of the catheter is coated with a hydrophilic polymer, therefore, it demonstrates a high lubricity upon moistening.

The provided text describes a 510(k) premarket notification for the FINECROSS™ MG Coronary Micro-Guide catheter. This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than presenting new clinical study data with specific acceptance criteria and performance metrics typically associated with AI/software as a medical device (SaMD) clearances.

Therefore, many of the requested elements for an AI/SaMD study, such as sample size for test and training sets, expert qualifications, and adjudication methods, are not applicable or explicitly mentioned in this document. The device is a physical medical instrument, not an AI algorithm.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a 510(k) submission for a physical medical device, specific "acceptance criteria" and "device performance" in the context of an AI algorithm's metrics (e.g., sensitivity, specificity) are not present. Instead, the document focuses on demonstrating substantial equivalence to predicate devices through various specifications and bench testing.

• Outer diameter (distal end): 1.8Fr (0.60mm)
• Outer diameter (proximal end): 2.6Fr (0.870mm)
• Inner diameter: 0.018" (0.45mm) to 0.0221" (0.55mm)
• Radiopaque markers: 1 |
  | Expiration Dating | 2 years. |

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

Not applicable for this type of device. The "test set" in this context would refer to physical prototypes undergoing bench testing, not a dataset for an AI algorithm. The document states "bench testing" was performed, but does not specify sample sizes or data provenance for these physical tests.

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 the context of AI refers to expert-labeled data. For a physical device, testing is typically against engineering specifications and predicate device performance, not expert-established ground truth in the AI sense.

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

Not applicable. This is a method for resolving discrepancies in expert labeling for AI ground truth.

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 device is a physical catheter, not an AI or software assistant for human readers. Therefore, an MRMC study related to AI assistance would not be performed for this product.

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

Not applicable. This is not an AI algorithm.

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

For this physical device, the "ground truth" would be established by engineering specifications, validated test methods, and direct comparison to the performance characteristics of the legally marketed predicate devices, rather than expert consensus on medical images or pathology.

8. The sample size for the training set

Not applicable. This device is not an AI algorithm that requires a training set.

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

Not applicable. There is no training set for this physical device.

Ask a specific question about this device