K Number
K121773
Manufacturer
Date Cleared
2012-09-21

(95 days)

Product Code
Regulation Number
882.4725
Panel
NE
Reference & Predicate Devices
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

The Nimbus Electrosurgical Radiofrequency Multitined Expandable Electrode, in combination with an RF generator and probe, are intended for use in radiofrequency (RF) heat lesion procedures for relief of pain.

Device Description

The NIMBUS Electrosurgical Radiofrequency Mutitined Expandable Electrode consists of an insulated cannula with an active tip that directs RF energy into target tissues, and a pair of deployable tines which expand the volume of the ablation. It is intended, in combination with an RF generator and probe, for use in radiofrequency (RF) heat lesion procedures for relief of pain.

AI/ML Overview

The provided 510(k) summary for the NIMBUS Electrosurgical Radiofrequency Multitined Expandable Electrode describes a regulatory submission establishing substantial equivalence to a predicate device, rather than a clinical study with detailed acceptance criteria and performance metrics for an AI device. Therefore, a direct response to your request, which presumes a study showing an AI device meeting specific acceptance criteria, cannot be fully provided from the given document.

However, I can extract the information that is present and indicate what is not available based on the nature of this submission.

The document discusses performance tests conducted to demonstrate substantial equivalence to a predicate device (BMC RF Cannula, K972846). The objective of these tests was to show that the Nimbus device performs similarly and is as safe and effective as the predicate, not to meet pre-defined acceptance criteria in the context of an AI device's performance.

Here's the information synthesized from the document, acknowledging its limitations regarding typical AI device study data:


1. Table of Acceptance Criteria and Reported Device Performance

As this is a 510(k) submission for a medical device and not an AI algorithm, there are no specific "acceptance criteria" presented in the form of diagnostic performance metrics (e.g., sensitivity, specificity, AUC) for an AI device. Instead, the document lists performance tests (implicitly with internal pass/fail criteria) performed to demonstrate substantial equivalence.

Acceptance Criteria Type (Implied for Device Performance)Reported Device Performance (Summary)
Comparative Performance vs. PredicatePassed all comparative tests; found substantially equivalent to the predicate device.
Thermal PropertiesNot explicitly stated, but implies performance met expectations for substantial equivalence.
Lesion Formation Volume and ShapeNot explicitly stated, but implies performance met expectations for substantial equivalence.
High frequency dielectric strengthPassed (implied as "passed all tests").
High frequency leakage currentPassed (implied as "passed all tests").
Mains frequency dielectric strengthPassed (implied as "passed all tests").
Connection cord bend testPassed (implied as "passed all tests").
Conformance to SpecificationPassed all tests.
Dimensional conformance to specificationPassed.
Active tip characterizationPassed.
Luer/injection performancePassed.
Needle durability and Tine IntegrityPassed.
Tine deploymentPassed.
Biocompatibility and DurabilityPassed.
Label verification; packagingPassed.
Sterilization ValidationPassed.
Shelf-life TestingPassed.

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

  • Sample Size: Not specified for any of the performance tests. The testing appears to be bench testing and not a clinical study involving human subjects or data sets in the way an AI study would.
  • Data Provenance: Not applicable in the context of an AI study. The tests were likely conducted in a controlled laboratory environment by the manufacturer (Biomerics, LLC) in Salt Lake City, Utah, USA.

3. Number of Experts Used to Establish Ground Truth and Qualifications

  • Not Applicable. This is not an AI device, and the ground truth for its performance tests (e.g., electrical measurements, physical dimensions, lesion formation) is based on engineering specifications and measurement standards, not expert interpretations of medical images or patient outcomes.

4. Adjudication Method for the Test Set

  • Not Applicable. As there are no expert interpretations or consensus required for typical engineering and performance bench tests.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

  • No. This type of study is specifically for evaluating the effectiveness of a diagnostic aid (like AI) on human reader performance. This device is a surgical tool, not a diagnostic aid.

6. Standalone (Algorithm Only) Performance

  • Not Applicable. The device itself is the "algorithm" in a sense (its design and function), and its performance is evaluated directly through physical and electrical tests, not as a standalone software algorithm separate from human interaction for diagnostic purposes.

7. Type of Ground Truth Used

  • Engineering Specifications and Standardized Test Methods: The "ground truth" for the performance tests would be established by validated measurement equipment and adherence to relevant industry standards (e.g., for electrical safety, material properties, biocompatibility) and the device's own design specifications. For example, a dielectric strength test has a pass/fail threshold defined by an electrical standard. Lesion formation is likely compared to a predefined expectation or to the predicate device's measured lesion formation under identical conditions.

8. Sample Size for the Training Set

  • Not Applicable. This is not an AI device trained on data. There is no concept of a "training set" for the NIMBUS Electrosurgical Radiofrequency Multitined Expandable Electrode.

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

  • Not Applicable. (See point 8).

Summary Regarding AI-Specific Information:

The provided document is a 510(k) summary for a physical medical device (an electrosurgical electrode), not an Artificial Intelligence (AI) enabled device. Therefore, the questions related to AI acceptance criteria, sample sizes for test/training sets, expert ground truth establishment, MRMC studies, and standalone algorithm performance are not applicable to the content of this document. The document describes traditional device verification and validation activities aimed at demonstrating substantial equivalence to a predicate device.

§ 882.4725 Radiofrequency lesion probe.

(a)
Identification. A radiofrequency lesion probe is a device connected to a radiofrequency (RF) lesion generator to deliver the RF energy to the site within the nervous system where a lesion is desired.(b)
Classification. Class II (performance standards).