Search Results

The Apyx One Console is indicated for delivery of radiofrequency energy and/or helium plasma to cut, coagulate and ablate soft tissue during open and laparoscopic surgical procedures. The helium plasma portion of the generator can be used only with dedicated Renuvion/J-Plasma handpieces.

The Apyx One Console is an electrosurgical generator that delivers radiofrequency (RF) energy to cut and coagulate soft tissue. It can also deliver Helium plasma energy for cutting, coagulation, and ablation of soft tissue. Like the predicate, the Apyx One Console provides standard electrosurgical energy and Helium Plasma energy, with no changes to the intended use, electrosurgical modes, output power waveforms, or maximum power settings. The Apyx One Console is a modified version of the primary predicate device that was cleared under K192867 (Apyx Helium Plasma Generator), with a no change to the intended use.

The Apyx One Console has a Graphical User Interface (GUI). Remote Services will be available using an attached cellular module to assist in troubleshooting the generator in the field, a helium Gas Pressure Transmitter, and two monopolar ports.

The Remote Service module will also provide non-HIPPA data to a cloud data system which will log the various settings of the generator throughout its use.

The Apyx One Console is an electrosurgical generator intended for the delivery of radiofrequency energy and/or helium plasma to cut, coagulate, and ablate soft tissue during open and laparoscopic surgical procedures. The helium plasma portion of the generator can only be used with dedicated Renuvion/J-Plasma handpieces.

Here's a breakdown of the acceptance criteria and the study proving the device meets them:

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

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

The document does not specify a separate "test set" in the context of clinical data for performance evaluation. Instead, the performance testing described focuses on engineering verification and validation. Therefore, information regarding sample size and data provenance for a test set (e.g., patient data) is not applicable here as it is not a clinical study in that sense.

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

Not applicable. This evaluation focuses on engineering performance rather than clinical endpoints requiring expert ground truth establishment.

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

Not applicable. This was not a study requiring adjudication of interpretations.

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. The device is an electrosurgical generator, not an AI-powered diagnostic tool, so an MRMC study comparing human readers with and without AI assistance is not relevant.

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

Not applicable. The device is a physical medical instrument, not an algorithm, so the concept of "standalone algorithm performance" is not relevant. The performance evaluation focuses on the engineering safety and effectiveness of the hardware and software in its intended operational context.

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

The "ground truth" for this device's acceptance criteria primarily involved:

• Compliance with established international electrical safety, electromagnetic compatibility, and usability standards.
• Verification against product and performance specifications for electrical functionality, software/firmware operation, and mechanical design.

8. The sample size for the training set

Not applicable. This device, being an electrosurgical generator, does not utilize a "training set" in the context of machine learning.

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

Not applicable, as there is no training set for this type of medical device evaluation.

Ask a specific question about this device

The J-Plasma Precise® FLEX is used for the delivery of radiofrequency energy and/or helium gas plasma (J-Plasma energy) for electrosurgical cutting, coagulation of soft tissue. It is intended for use with a grasper during minimally invasive surgical procedures.

The J-Plasma Precise® FLEX is compatible with Apyx Medical electrosurgical generators.

The J-Plasma Precise® Flex Handpiece is a sterile, single use electrosurgical (monopolar) device intended to be used in conjunction with compatible generators for the delivery of radiofrequency ("RF") energy and/or helium gas plasma for electrosurgical cutting, coaqulation, and ablation of soft tissue. It is intended for use with a grasper during minimally invasive surgical procedures. The handpiece has one configuration, model # APYX-500BF. The compatible Generators operate at an adjustable power of up to 40 W (expressed as 0-100% where 100% is 40 W) and provide an adjustable helium gas flow of 1-5 LPM. Radiofrequency energy is delivered to the handpiece by the generator and used to energize the electrode. When helium gas is passed over the energized electrode, a helium plasma is generated for soft tissue cutting, coagulation or ablation.

The J-Plasma Precise® Flex Handpiece has an extendable electrode (blade) in the tip to generate helium plasma. The tip is controlled by the user via graspers to actuate (extend and retract) the blade. The handpiece comes with an Introducer that allows for more control of the tip when introducing and removing the distal end to and from the cannula. The handpiece has a flexible, seamless cable that can be advanced with graspers through the cannula during minimally invasive surgical procedures. The handpiece is activated by the footswitch.

The provided text describes a 510(k) premarket notification for a medical device, the J-Plasma Precise® FLEX Handpiece. The core of the submission is to demonstrate that the modified device is substantially equivalent to a legally marketed predicate device.

Here's an analysis of the acceptance criteria and study proving the device meets them, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are not explicitly stated in a quantitative manner (e.g., a specific percentage or value to be met). Instead, the studies aim to demonstrate equivalence to the predicate device. The performance is reported qualitatively as "equivalent" or that requirements were "met."

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

• Sample Size for Test Set: The document states that an "ex-vivo study was conducted on several tissue types (i.e., muscle, liver, kidney)" for the tissue thermal effect equivalency testing. However, the specific number of samples or replicates for each tissue type is not provided.
• Data Provenance: The study was "ex-vivo," meaning performed on tissue outside of a living organism. The country of origin for the tissue or the testing location is not specified, but the applicant is Apyx Medical Corporation, located in Clearwater, Florida, USA. The study design appears to be retrospective in the sense that it's comparing a modified device to an existing predicate, rather than a prospective clinical trial.

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

This document describes bench testing and ex-vivo studies. There is no mention of human experts establishing ground truth for a test set in the context of diagnostic performance or interpretation. The "ground truth" for the performance tests (e.g., tissue effect, electrical safety) would be established by the physical measurements and compliance with engineering standards by qualified technical personnel.

4. Adjudication Method for the Test Set

As there's no mention of a human expert-based assessment or diagnostic interpretation requiring adjudication, there is no adjudication method described. The tests are directly measuring physical and electrical properties.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study was not done. This device is an electrosurgical handpiece, not an AI diagnostic tool. The performance evaluation focuses on the safety and effectiveness of the device itself and its equivalence to a predicate, not on how it assists human readers in making diagnoses.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

This question is not applicable in the context of this device. The J-Plasma Precise® FLEX Handpiece is a physical surgical tool, not an algorithm. Its "performance" is its ability to cut, coagulate, and ablate tissue, and to meet safety standards. The ex-vivo tissue effect studies are "standalone" in the sense that they assess the device's direct effect on tissue, independent of a human operator's skill, but it's not an algorithm's performance.

7. The Type of Ground Truth Used

The ground truth for the performance studies is based on:

• Physical Measurements and Engineering Standards: For electrical safety and mechanical functionality, the ground truth is defined by compliance with established international standards (e.g., IEC 60601 series, ISO 14971) and meeting predefined operational requirements.
• Quantitative Tissue Effect Data: For tissue thermal effect, the ground truth is derived from measurements of depth and lateral spread of thermal effects in the ex-vivo tissue samples. The "truth" is established by direct scientific measurement and comparison to the predicate device's measured effects.
• ISO Standards for Biocompatibility: For biocompatibility, the ground truth is established by demonstrating compliance with ISO 10993 guidelines.

8. The Sample Size for the Training Set

This document describes a medical device, not an AI/ML algorithm. Therefore, there is no concept of a "training set" as would be used for machine learning. The device's design, manufacturing, and testing follow established engineering and quality system procedures.

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

As there is no training set for an AI/ML algorithm, this question is not applicable. The "ground truth" for the device's development and verification relies on engineering specifications, risk assessments (ISO 14971), and established laboratory testing protocols in compliance with design and development procedures (21 CFR 820.30).

Ask a specific question about this device