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510(k) Data Aggregation
(163 days)
The GYNECARE VERSAPOINT™ II Bipolar Electrosurgery System is intended for use in tissue cutting, removal and desiccation as required or encountered in gynecologic hysteroscopic electrosurgical procedures for the treatment of intrauterine myomas, polyps, adhesions, and septa, and benign conditions requiring endometrial ablation. Procedures include:
- . Excision of intrauterine myomas
- ◆ Excision of intrauterine polyps
- . Lysis of intrauterine adhesions
- Incision of uterine septa
- . Endometrial ablation
The GYNECARE VERSAPOINT™ II Bipolar Electrosurgery System (VERSAPOINT II System) is the next generation of the currently-marketed GYNECARE VERSAPOINT™ Bipolar Electrosurgery System (VERSAPOINT System). This electrosurgical system utilizes bipolar technology specifically designed to provide a range of gynecological surgical treatments, including vaporization to ablate and excise tissue, thermal coagulation of tissue and hemostasis of blood vessels. The VERSAPOINT II System is comprised of four main elements: the VERSAPOINT II Generator, the VERSAPOINT II 4mm Angled Loop Electrode, the VERSAPOINT II Footswitch, and the VERSAPOINT II Connector Cable. The VERSAPOINT II System offers five bipolar output modes: Ablation (VC [VaporCut]) – for tissue removal and cutting Enhanced Ablation (VP [VersaPulse]) - an enhanced version of the Ablation (VC) output mode attained by use of short-duration high power pulses Blended Ablation (BL) – simultaneous ablation and coagulation (the generator rapidly switches between ablation and coagulation output modes) Enhanced Blended Ablation (VBL) – a variant of the VP output mode that rapidly switches the output ON and OFF to deliver blended ablation/coagulation Coagulation (DES [Desiccate]) - for thermal coagulation and hemostasis
Here's an analysis of the provided text regarding the acceptance criteria and supporting studies for the GYNECARE VERSAPOINT™ II Bipolar Electrosurgery System:
1. Table of Acceptance Criteria and Reported Device Performance
The submission states that performance was evaluated against the predicate device to demonstrate "substantial equivalence." The acceptance criteria were based on similar performance to the legally marketed predicate. Specific numerical targets or ranges for the acceptance criteria are not explicitly detailed in the provided text, but the study aimed to show that the new device's performance was comparable.
Performance Metric | Acceptance Criteria (Implied) | Reported Device Performance |
---|---|---|
Maximum thermal margin and depth of tissue necrosis | Comparable to predicate device | Demonstrated substantial equivalence |
Mean volume of gas generated | Comparable to predicate device | Demonstrated substantial equivalence |
Mean tissue removal rate | Comparable to predicate device | Demonstrated substantial equivalence |
Hemostasis performance | Comparable to predicate device | Demonstrated substantial equivalence |
2. Sample Size Used for the Test Set and Data Provenance
- Test Set Sample Size: Not explicitly stated for each study. The text mentions "Two bench studies and one animal study." While these studies form the "test set" for demonstrating substantial equivalence, the specific number of samples or animals used in each is not provided.
- Data Provenance: The animal study was conducted "in compliance with the Good Laboratory Practices regulation, 21 CFR Part 58," indicating a prospective, controlled study design typically involving animal subjects. The location (country of origin) of these studies is not specified. Bench studies are inherently controlled laboratory evaluations.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Those Experts
Not applicable. The studies described are performance-based evaluations of the electrosurgical system's physical effects (tissue necrosis, gas generation, tissue removal, hemostasis) rather than diagnostic or interpretative tasks requiring human expert ground truth.
4. Adjudication Method for the Test Set
Not applicable, as expert adjudication is not relevant for this type of performance testing.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No, an MRMC comparative effectiveness study was not done. This type of study would be relevant for diagnostic devices where human readers interpret images or data, and the AI's assistance to these readers is being evaluated. The GYNECARE VERSAPOINT™ II is an electrosurgical system, not a diagnostic imaging or interpretive aid.
6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study
Yes, the studies conducted can be considered "standalone" in the sense that they evaluated the device's inherent performance characteristics (like thermal effects, gas generation, tissue removal) independently of human cognitive interpretation or decision-making. The device is a surgical tool, and its performance is assessed by its direct effects on tissue.
7. Type of Ground Truth Used
The "ground truth" for these studies was based on direct measurement and observation of the physical effects of the electrosurgical system.
- Bench Studies: Involved direct measurements of thermal margin, depth of tissue necrosis, volume of gas generated, and tissue removal rate in controlled laboratory settings.
- Animal Study: Involved direct observation and measurement of tissue effects and hemostasis performance in a living model. This would likely include histological analysis and quantitative measurements of tissue damage or desired surgical outcomes.
8. Sample Size for the Training Set
Not applicable. The GYNECARE VERSAPOINT™ II is an electrosurgical device, not an AI/machine learning algorithm that requires a "training set" in the conventional sense. The "hardware and software updates" mentioned likely refer to engineering and control system logic modifications, not a data-driven learning model.
9. How the Ground Truth for the Training Set Was Established
Not applicable, as there is no "training set" for an AI algorithm in this context. The "updates" were likely developed based on engineering principles, predicate device performance data, and design specifications, rather than a data-driven training process.
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