Search Results

The Physician Industries' Radiofrequency Ablation Needle is a single use RF (radiofrequency) needle with injection capabilities. It can be used for either 1) (Fadiofrequency) in the lesioning, or 2) percutaneous nerve blocks with a local anesthetic solution. The nerve is localized by using electrical stimulation through the needle. The nerve may then be blocked either by the generating an RF lesion, or by the injecting of a local anesthetic. It is to be used only under the direction of a licensed clinician.

The Physician Industries Inc. needle shares major similarities with the predicate device(s), inasmuch as the configuration, material, use, labeling and safety issues remain basically unchanged. It consists of a plastic hub, insert molded over a PTFE-coated stainless steel cannula.

The provided text describes a 510(k) premarket notification for the Physician Industries' Radiofrequency Ablation Needle. This type of submission focuses on demonstrating "substantial equivalence" to a legally marketed predicate device, rather than proving safety and effectiveness through extensive, de novo clinical trials with detailed performance metrics and acceptance criteria. As such, the document does not contain the typical information for acceptance criteria and a study proving a device meets them in the way modern AI/software device submissions would.

However, I can extract the relevant information from the document that speaks to how the device's safety and effectiveness were supported for its 510(k) clearance.

Here's a breakdown based on the information available:

1. Table of Acceptance Criteria and Reported Device Performance

This document does not present a table of specific, quantifiable acceptance criteria or device performance metrics in the way a clinical trial for a novel device would. Instead, the "performance" is demonstrated by showing "substantial equivalence" to predicate devices. The implicit acceptance criteria are that the device performs as safely and effectively as the predicate devices.

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

• Test Set: No specific test set of patients or medical cases is described in the document. The "test" for substantial equivalence relies on comparison with the predicate devices and their established safety and performance records.
• Data Provenance: The document refers to "review of the FDA's MAUDE, Safety Alert..., and MDR databases" for adverse event data related to predicate devices. This would be retrospective data from the United States.

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

Not applicable. The ground truth for this 510(k) submission is not established by expert consensus on a test set of data. Instead, the "ground truth" for the device's acceptable performance is implicitly the established safety and effectiveness of the existing predicate devices on the market, as cleared by the FDA.

4. Adjudication method for the test set

Not applicable, as no human-adjudicated test set is described.

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 a medical device (a physical RF ablation needle), not an AI/software device. Therefore, no MRMC study, human reader improvement, or AI assistance is relevant.

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

Not applicable, as this is a physical medical device.

7. The type of ground truth used

The "ground truth" in the context of this 510(k) submission is the documented safety and effectiveness of the predicate devices (Radionics' Pole Needle, K021942 and K963577) as legally marketed and reviewed by the FDA. This is based on regulatory history and prior clearances rather than an independent gold standard for a new device.

8. The sample size for the training set

Not applicable. This is a physical medical device. There is no "training set" in the machine learning sense. The design and manufacturing processes are informed by general engineering principles and quality systems compliant with 21 CFR Part 820.

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

Not applicable. There is no training set as understood in AI/ML contexts. The device design and manufacturing are based on established engineering practices, material science, and regulatory requirements for medical devices, aiming to replicate the established performance and safety profile of equivalent predicate devices.

Ask a specific question about this device