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The Canady Helios Cold Plasma™ XL-1000CP™ Ablation System is indicated for the gas enhanced ablation of soft tissue using helium-based plasma.

The Canady Helios Cold Plasma™ XL-1000CP™ Ablation System produces a Helium-based cold plasma spray to deliver high frequency low energy current intended for the ablation of soft tissues.
The Canady Helios Cold Plasma™ XL-1000CP Ablation System includes the following items:

• Canady Helios Cold Plasma™ XL-1000CP SMART Electrosurgical Generator
• Canady Helios™ Cold Plasma Ablators
• Foot Pedal
• Trolley Cart
  The Canady Helios Cold Plasma™ XL-1000CP™ SMART Electrosurgical Generator is a transportable nonsterile electrical device compatible for use in the operating room environment. The Canady Helios Cold Plasma™ XL-1000CP SMART Electrosurgical Generator creates high frequency, short duration energy pulses with regulated Helium gas, which is delivered to the target tissue via the Canady Helios™ Cold Plasma Ablators. The Canady Helios™ Cold Plasma Ablators are sterile monopolar electrosurgical instruments intended for single use.

This document, K240297, is a 510(k) Premarket Notification for the Canady Helios Cold Plasma™ XL-1000CP™ Ablation System. It demonstrates substantial equivalence to a predicate device, not an AI/ML powered device. Therefore, the information requested about acceptance criteria, study details, ground truth establishment, sample sizes, and expert adjudication as pertains to AI/ML device performance is not applicable to this submission.

The document focuses on the safety and effectiveness of the electrosurgical ablation system itself, comparing it to an existing predicate device based on its intended use, technological characteristics, and performance testing against recognized standards.

Here's a breakdown of what is available in the document regarding the device's performance and acceptance, interpreted in a general sense rather than specifically for AI/ML:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't provide specific numerical acceptance criteria for performance; rather, it lists various tests conducted and generally states that the device "Met criteria." This is common for non-AI medical devices where performance is typically validated against engineering specifications and applicable standards, rather than statistical thresholds for diagnostic accuracy.

The document also notes in the Substantial Equivalence table:

• Performance: "Shown to ablate soft tissue at specified parameters." (For both subject and predicate device).

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

This information is not applicable as the document describes a traditional medical device (electrosurgical ablation system) and its performance validation, not an AI/ML-powered device requiring a test set for algorithmic performance evaluation. The "tests" mentioned are likely bench testing, in-vitro experiments, or potentially animal studies (though not specified), designed to verify physical and electrical properties, sterility, and basic function. Data provenance as typically understood for AI (e.g., country of origin of patient data, retrospective/prospective) is irrelevant here.

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

Not applicable. There is no "ground truth" in the AI/ML sense (e.g., clinical labels for images) established by experts for this type of device. Performance is assessed against engineering specifications, safety standards, and the ability to perform its stated function (ablation).

4. Adjudication Method for the Test Set:

Not applicable. No adjudication methods are described as there is no human interpretation of data for algorithmic ground truth establishment.

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

Not applicable. This type of study is relevant for AI/ML diagnostic or assistive technologies where human reader performance is a key metric. This is a therapeutic electrosurgical device.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:

Not applicable. As this is not an AI/ML device, the concept of a standalone algorithm performance test is not relevant.

7. Type of Ground Truth Used:

Not applicable in the AI/ML sense. For this device, "ground truth" refers to established engineering principles, safety standards (e.g., electrical safety, electromagnetic compatibility), and the physical outcome of the ablation process (e.g., tissue ablation effectiveness, thermal effect), verified through laboratory testing against specifications.

8. Sample Size for the Training Set:

Not applicable. There is no "training set" as this is not an AI/ML device that learns from data.

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

Not applicable. Similar to point 8, there is no training set or associated ground truth for this type of medical device submission.

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