K Number
K102439
Date Cleared
2012-01-12

(504 days)

Product Code
Regulation Number
870.1250
Reference & Predicate Devices
N/A
Predicate For
N/A
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

The Funnel Guide Catheter" is indicated for use in the peripheral and coronary vasculature for the introduction of interventional and/or diagnostic devices.

Device Description

The Lazarus Effect Funnel Guide Catheter" (Funnel Guide Catheter") is a single-lumen, variable-stiffness catheter with an atraumatic nitinol wire braided funnel distal tip to facilitate the passage of other interventional and/or diagnostic devices. Device dimensions and configuration are shown on the product label. The Funnel Guide Catheter" is compatible with introducer sheaths and guide catheters having an inner diameter of 6F or greater. A rotating hemostasis valve with side-arm adapter and a compatible guidewire may be used, but are not provided with the Funnel Guide Catheter™.

AI/ML Overview

The provided text describes a medical device, the "Funnel Guide Catheter™," and its regulatory submission (510(k) summary). This is a physical medical device, not an AI/ML-driven diagnostic tool. Therefore, the questions related to AI/ML specific criteria (such as AI assistance effect size, standalone algorithm performance, ground truth for training/test sets, sample size for training/test sets, and expert qualifications for ground truth establishment) are not applicable to this submission.

The "acceptance criteria" for this device are implicitly tied to demonstrating substantial equivalence to predicate devices through various performance tests.

Here's an interpretation of the requested information based on the provided text, while noting the non-applicability of certain AI/ML specific points:

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

The document does not explicitly state quantitative "acceptance criteria" with specific pass/fail thresholds for each test, as would be common for AI/ML performance metrics (e.g., sensitivity > X%, specificity > Y%). Instead, the "acceptance criteria" are implied by the successful completion of a battery of tests demonstrating the device's safety and effectiveness and its substantial equivalence to predicate devices. The "reported device performance" is a general statement that the device met these criteria.

Acceptance Criteria Category (Implied)Reported Device Performance
Bench Testing:Verified as designed
- Dimensional measurementVerified as designed
- Visual examinationVerified as designed
- Fluoroscopic evaluationVerified as designed
- Kink resistanceVerified as designed
- Simulated useVerified as designed
- Torque transmissionVerified as designed
- Repeated useVerified as designed
- Navigation and insertion forceVerified as designed
- Air and fluid leakVerified as designed
- Corrosion resistanceVerified as designed
- Tensile testing (force at break)Verified as designed
- Fluid flow rateVerified as designed
- Burst pressureVerified as designed
- Product and packaging stabilityVerified as designed
- Packaging integrityVerified as designed
Biocompatibility Testing:Verified as designed
- CytotoxicityVerified as designed
- Sensitization assayVerified as designed
- Intracutaneous reactivityVerified as designed
- PyrogenVerified as designed
- Systemic toxicityVerified as designed
- HemolysisVerified as designed
- ThromboresistanceVerified as designed
- Complement ActivationVerified as designed
- SterilizationVerified as designed
In-vivo Testing:Verified as designed
- Simulated use (porcine model)Verified as designed
Overall Conclusion:Substantially equivalent to predicate devices, performs as designed and is suitable for its intended use.

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

The text mentions "in vivo testing in the animal model" using a "simulated use porcine model." The exact sample size (number of pigs) is not specified. This would be a prospective animal study. Data provenance (country of origin) is not stated for the animal model. Bench testing and biocompatibility testing were also performed, but these do not typically involve "test sets" in the same way an AI/ML model would, and specific sample sizes for these tests are generally detailed in the full test reports, not typically summarized in a 510(k) summary.

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)

This is not applicable. For a physical medical device like a catheter, "ground truth" is established through engineering specifications, validated test methods (bench, biocompatibility), and animal studies, not through expert consensus on diagnostic images. The performance of the device itself (e.g., its navigated path, ability to deliver other devices, material integrity) is the "ground truth" being assessed.

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

This is not applicable. Adjudication methods are relevant for subjective interpretations of data, particularly in clinical trials or AI/ML evaluations. For performance testing of a physical device, results are typically objectively measured against specifications or observed in controlled environments (e.g., kink resistance, burst pressure). Any observations during the porcine model would likely be recorded by researchers/veterinarians involved in the study.

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

This is not applicable. This device is a physical catheter, not an AI-assisted diagnostic tool. Therefore, MRMC studies and "human readers improving with AI" are irrelevant.

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

This is not applicable. This device is a physical medical instrument and does not involve an algorithm.

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

For this physical device, the "ground truth" is primarily established through:

  • Engineering Specifications: For benchmark and dimensional measurements.
  • Validated Test Methods: For biocompatibility, mechanical properties (e.g., tensile strength, burst pressure), and functional performance (e.g., simulated use, torque transmission).
  • Biological Response in Animal Models: For in-vivo assessment of tissue reaction (histology) and visibility (fluoroscopic visibility) in a porcine model.

8. The sample size for the training set

This is not applicable. There is no "training set" for a physical medical device. This term applies to machine learning models.

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

This is not applicable. There is no "training set."

§ 870.1250 Percutaneous catheter.

(a)
Identification. A percutaneous catheter is a device that is introduced into a vein or artery through the skin using a dilator and a sheath (introducer) or guide wire.(b)
Classification. Class II (performance standards).