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510(k) Data Aggregation
(108 days)
The Plasma MD or Plasma + is intended for the removal and destruction of skin lesions and coagulation of tissue.
The Plasma Pen utilizes a treatment method called plasma sublimation, which causes controlled skin damage through the generation of an electrical arc. The arc between the disposable tip and the skin is created by a radio frequency generator housed in an electrosurqical unit (handpiece) that ionizes the gas particles in the air. A straight disposable tip is available with the system. The handheld device is cordless and is charged in a docking/charging station prior to use.
The system components include the following:
- Plasma Pen (Plasma MD (with 2 level switch) and Plasma+ (without switch)
- Docking station for Plasma Pen
- Cable for Plasma Pen
- Power bank battery
- Cable for power bank battery
- Charging Block
The provided text describes a 510(k) premarket notification for the Plasma Pen (Plasma MD and Plasma +) device. It details the device's characteristics, its intended use, and a comparison to a predicate device to establish substantial equivalence. However, the document does not contain the specific information requested regarding acceptance criteria, a study that proves the device meets those criteria, or details about test sets, ground truth establishment, or expert involvement.
The document focuses on demonstrating substantial equivalence to an existing predicate device (SubNovii Advanced Plasma Technology, K201738) based on similar indications for use, mode of operation, and performance characteristics. The "performance data" mentioned refers to non-clinical bench testing, not a clinical study involving human patients or complex AI-driven analysis.
Therefore, many of the requested fields cannot be filled from the provided text.
Here's a breakdown of what can and cannot be extracted from the provided text:
1. A table of acceptance criteria and the reported device performance:
The document doesn't explicitly state "acceptance criteria" in the format of a clinical study with metrics like sensitivity, specificity, or AUC. Instead, it compares characteristics and performance benchmarks against a predicate device to claim substantial equivalence. The closest to "acceptance criteria" are the "SAME" or "DIFFERENT" conclusions for various characteristics and the damage depth for thermal effects.
| Characteristic | Acceptance Criteria (from Predicate) | Reported Device Performance (Plasma Pen) | Met Criteria? (Substantial Equivalence) |
|---|---|---|---|
| Indications for Use | Intended for the removal and destruction of skin lesions and coagulation of tissue. | Intended for the removal and destruction of skin lesions and coagulation of tissue. | SAME |
| Prescription or OTC | Prescription | Prescription | SAME |
| Mode of Operation | Plasma; Radiofrequency energy ionizes the air creating a plasma stream | Plasma; Radiofrequency energy ionizes the air creating a plasma stream | SAME |
| Output | Monopolar | Monopolar | SAME |
| Power Supply | 110-250 VAC 50/60 Hz | 110-250 VAC 50/60 Hz | SAME |
| Frequency | 40 kHz | 40 kHz | SAME |
| Max Power Output | 5W | 2W | DIFFERENT (Lower max power output, with intended effect still achievable) |
| System Components | Handpiece, electrosurgical generator unit, docking station, active electrode. | Handpiece, electrosurgical generator unit, docking station, active electrode. | SAME |
| Thermal Effects on 4 porcine tissues (liver, kidney, muscle and skin) per FDA Guidance "Premarket Notification (510(K)) Submission for Electrosurgical Devices for General Surgery" (Damage Depth) | Damage depth of <0.25mm | Damage depth of <0.25mm | SAME |
| Electrical Safety (IEC 60601-1, IEC 60601-1-2, IEC 60601-2-2) | Compliance with standards demonstrating basic safety, essential performance, emissions, and immunity. | Demonstrated appropriate electrical safety and electromagnetic compatibility profile. | Met (Passed) |
| Electrical system performance | Not explicitly quantified, but expected to meet functional requirements. | Performance was met. | Met |
| Output waveform at the rated load | Not explicitly quantified, but expected to be appropriate for intended function. | Performance was met. | Met |
2. Sample size used for the test set and the data provenance:
- Sample size for bench testing: Not specified. The thermal effects testing mentions "4 porcine tissues," but not the number of samples or repetitions.
- Data provenance: Not applicable in the context of clinical data for AI performance. The performance testing is "bench/performance testing" and involves "porcine tissues" for thermal effects, not human data.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Not applicable. This device is an electrosurgical tool, not an AI-driven diagnostic device requiring expert interpretation for ground truth. The "ground truth" for its performance is derived from physical measurements (e.g., damage depth, electrical safety compliance) and comparison to a predicate device's established performance.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
- Not applicable. No expert adjudication process for image interpretation or diagnosis.
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:
- No. This is not an AI-assisted diagnostic device. The study described is non-clinical bench testing.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- No. This is a hardware device.
7. The type of ground truth used:
- Bench test measurements and compliance with electrical safety standards. For thermal effects, the ground truth is the measured damage depth in porcine tissues. For electrical safety, the ground truth is compliance with the specified IEC standards. Substantial equivalence relies on comparing these performance characteristics to the predicate device.
8. The sample size for the training set:
- Not applicable. This device does not involve machine learning or AI that requires a training set.
9. How the ground truth for the training set was established:
- Not applicable. No training set for AI.
In summary, the provided document describes a 510(k) submission for an electrosurgical device, focused on demonstrating substantial equivalence based on physical characteristics and non-clinical bench testing. It does not involve an AI component or complex clinical study with human patients, which are the typical contexts for the detailed acceptance criteria and study designs outlined in your request.
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