K Number
K122772
Manufacturer
Date Cleared
2012-11-20

(71 days)

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

The DDC™ Catheters are indicated for the introduction of interventional devices into the peripheral and neurovasculature.

Device Description

The DDC™ Catheters are variable stiffness catheter with various diameters, a catheter shaft reinforced with a stainless steel or Nitinol coil, and have a radiopaque markerband on the distal end. They are available in various lengths. The DDC™ Catheters have a PTFE-lined lumen, which is coil re-enforced, flexible, and hydrophilically coated. The DDC™ Catheters are inserted through a guide catheter or vascular sheath, provide access to the target site and once in place, provides a reinforcing conduit for other intravascular devices. The devices are provided sterile and include a rotating hemostasis valve and tip shaping mandrel. The DDC™ Catheters will be available in various configurations to allow physician ease of device tracking to the target site

AI/ML Overview

Here's an analysis of the provided text regarding the acceptance criteria and the study proving the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

AttributeAcceptance CriteriaReported Device Performance
DDC™ must be compatible with 6F sheath100% Pass100% Pass
DDC™ tracking over 0.038" guidewire100% Pass100% Pass
0.038" Guidewire Compatible100% Pass100% Pass
Hub Transition100% Pass100% Pass
Microcatheter compatibility100% Pass100% Pass
Microcatheter friction100% Pass100% Pass
Microcatheter support100% Pass100% Pass
0.038in guidewire compatibility (Friction Force) (DDC 5MAX only)100% Pass100% Pass
Torsion (DDC 4MAX only)100% Pass100% Pass

2. Sample Size Used for the Test Set and Data Provenance

The document does not explicitly state the sample size used for the performance tests. It also does not mention the data provenance (e.g., country of origin, retrospective or prospective data) for these tests. The tests appear to be "Non-clinical testing," suggesting they were conducted in a lab setting rather than with patient data.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of those Experts

This information is not provided in the document. Given that the testing is described as "Non-clinical testing" and focuses on physical and mechanical attributes, it's unlikely that clinical experts were used to establish a ground truth in the traditional sense. The "ground truth" here would be the physical measurement and functional assessment against predefined engineering specifications.

4. Adjudication Method for the Test Set

The document does not describe an adjudication method. For non-clinical, objective performance tests, formal adjudication by multiple experts is typically not relevant. The pass/fail criteria are usually based on objective measurements and engineering standards.

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

There is no mention of an MRMC comparative effectiveness study involving human readers or AI in this document. The device is a physical medical device (catheter), not an AI-powered diagnostic tool.

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

This is not applicable as the device is a physical medical catheter, not an algorithm.

7. The Type of Ground Truth Used

The ground truth for the non-clinical performance testing appears to be based on pre-defined engineering specifications and objective measurements of the catheter's physical and mechanical properties. The "Acceptance Criteria" table implicitly defines these desired performance characteristics.

8. The Sample Size for the Training Set

This information is not applicable. The DDC™ Catheters are physical medical devices, and the provided document describes non-clinical performance testing for regulatory submission, not a machine learning model that would require a training set.

9. How the Ground Truth for the Training Set was Established

This information is not applicable, as there is no training set for a machine learning model.

§ 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).