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The Venclose System (Venclose digiRF Generator with EVSRF Catheter) is intended for endovascular coagulation of blood vessels in patients with superficial vein reflux.

The Venclose™ digiRF Generator is a multi-voltage energy delivery system with touchscreen control that automatically sets the non-adjustable treatment parameters for the catheter to be used with the generator (time, temperature, etc.), which is connected via a triaxial catheter connector port. The Venclose™ digiRF Generator is intended to be used with Venclose™ RF Catheter(s) (either the Venclose™ EVSRF Catheter or the Venclose™ Maven Catheter) as a system. The Venclose™ RF System uses resistive radiofrequency ablation via energy delivery to heat the wall of an incompetent vein with temperature-controlled RF energy to cause irreversible luminal occlusion, followed by fibrosis and ultimately resorption of the vein.

The scope of this 510(k) is only the Venclose™ digiRF Generator as the generator software has been modified. The Venclose™ Maven Catheter is not in the scope of this submission as the changes discussed within this submission are only applicable to the Venclose™ digiRF Generator as used with the Venclose™ EVSRF Catheter. There is no change to the Venclose™ EVSRF Catheter, as previously cleared via K160754.

Based on the provided 510(k) Clearance Letter, the device in question is the "Venclose digiRF Generator" and the modifications are related to its software when used with the "Venclose EVSRF Catheter." The clearance letter states that the scope of this 510(k) is only the Venclose digiRF Generator as the generator software has been modified, and there is no change to the Venclose EVSRF Catheter.

The document explicitly states that the device is an "Electrosurgical Cutting And Coagulation Device And Accessories" and the testing performed was "Software Verification and Validation." There is no mention of a study involving human subjects, interpretation of medical images by experts, or any kind of diagnostic performance evaluation typically seen with AI/ML-based diagnostic devices.

Therefore, many of the requested criteria regarding acceptance criteria for diagnostic performance, ground truth establishment, expert adjudication, MRMC studies, and training/test set details for AI/ML models are not applicable to this submission. This is a clearance for a software modification to an electrosurgical generator, not a medical imaging AI/ML diagnostic aid.

Here's the breakdown of what can be gathered from the provided text, addressing the points where information is available and indicating where it is not applicable or not provided.

Device: Venclose digiRF Generator (VCRFG1) with Venclose EVSRF Catheter (VC10A256F60, VC10A256F100)
Type of Modification: Software Modification to the Venclose digiRF Generator.

1. Table of Acceptance Criteria and Reported Device Performance

Given that this is a software modification to an electrosurgical generator, the acceptance criteria are not related to diagnostic performance metrics like sensitivity, specificity, or AUC, but rather to software functionality, safety, and effectiveness. The document states that internal risk assessments procedures were used.

Note: Specific numerical acceptance values are not detailed in this public 510(k) summary, as they are typically proprietary and part of detailed engineering and software validation reports submitted to the FDA.

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

This is not applicable in the context of an AI/ML diagnostic performance test set. The "test set" here refers to the software verification and validation activities. The document does not specify exact "sample sizes" (e.g., number of test cases or iterations) for the software testing. Data provenance is also not applicable in the context of clinical data for AI/ML, as the testing relates to engineering and software validation.

• Software Verification and Validation: This typically involves rigorous testing against defined requirements, including unit testing, integration testing, system testing, and perhaps regression testing. The "sample size" would relate to the number of test cases executed, input parameters varied, and error conditions simulated. Specific numbers are not provided in this summary.
• Data Provenance: Not applicable as no clinical data for diagnostic performance was used in this clearance for a software modification to an electrosurgical device.

3. Number of Experts Used to Establish Ground Truth and Qualifications

Not applicable. Ground truth, in the sense of expert annotation of medical data, is not established for an electrosurgical generator's software modification. The "ground truth" for this device's performance would be its adherence to engineering specifications and its ability to safely and effectively deliver RF energy for its intended purpose, as measured by calibrated equipment and functional tests.

4. Adjudication Method for the Test Set

Not applicable. Adjudication methods (e.g., 2+1, 3+1) are for consensus building among human experts for ground truth label generation in diagnostic studies. This process is not part of software verification and validation for an electrosurgical device.

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

No. An MRMC study is relevant for evaluating the impact of an AI/ML diagnostic device on human reader performance. This 510(k) is for a software modification to an electrosurgical generator, not a diagnostic AI/ML device. Therefore, no MRMC study was performed or reported.

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

No. "Standalone performance" refers to the diagnostic accuracy of an AI/ML algorithm by itself. This device is an electrosurgical generator. Its performance is measured by its ability to generate and deliver RF energy according to specifications, not by its diagnostic capabilities. The software's "performance" was evaluated through verification and validation activities.

7. The Type of Ground Truth Used

Not applicable in the AI/ML diagnostic sense. For this device, the "ground truth" for software validation would be derived from:

• Design Specifications: The documented requirements and expected behavior of the software and the device.
• Predicate Device Performance: The existing performance characteristics of the previously cleared predicate devices, to which the modified device is being compared for substantial equivalence.
• Engineering Standards and Measurements: Data from calibrated test equipment, electrical measurements, temperature readings, and time controls.

8. The Sample Size for the Training Set

Not applicable. This device is not an AI/ML algorithm that requires a training set. The software was likely developed using traditional software engineering methodologies.

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

Not applicable. As there is no AI/ML training set, there is no ground truth to establish for such a set.

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The XERF is intended for use in dermatologic and general surgical procedures for electrocoagulation and hemostasis.

XERF is an electrosurgical unit which uses high frequency electrical currents for treatment. When high frequency is irradiated on the skin, the treated skin tissue is heated, resulting in coagulation. This equipment generates high frequency of 2 MHz and 6.78 MHz and is delivered non-invasively into skin through the tip of the handpiece. There are a total of 12 types of active electrode tips compatible with the handpiece; the different tips are intended for various applications and treatment zones. The system also includes a return pad corresponding to the neutral electrode which is intended to be attached to the patient's back to disperse the generated energy. For adjustment of treatment parameter, data can be used by adjusting the operator interface through LCD touch screen. Treatment is conducted using foot switch or finger switch after ready when applied treatment parameter is output to the tissue.

The provided FDA 510(k) Clearance Letter for the XERF device does not contain the kind of detailed information about acceptance criteria and a study proving the device meets them that your request outlines. This document is a clearance letter, which means the FDA has already assessed the sufficiency of the submitted information, including performance data, and found the device substantially equivalent to a predicate.

Specifically, the document states:

• "No clinical tests were included as part of this submission." This immediately tells us there was no study involving human subjects to demonstrate the device meets acceptance criteria in a clinical setting.
• The "Performance" section describes ex-vivo thermal studies. While these are performance tests, they are not clinical studies with acceptance criteria based on human outcomes or expert assessment of clinical images, as typically implied by your request.

Therefore, for aspects like "Table of acceptance criteria and reported device performance," "Sample size used for the test set," "Number of experts," "Adjudication method," "MRMC comparative effectiveness study," "Standalone performance," "Type of ground truth," "Sample size for training set," and "How ground truth for training set was established," the provided text does not contain this information. These details would typically be found in the more comprehensive 510(k) submission itself, rather than in the final clearance letter summary.

However, I can extract the available information from the "Performance" section regarding the ex-vivo studies.

Summary of Device Performance and Related Information from the Provided Text:

1. Table of Acceptance Criteria and Reported Device Performance

• Acceptance Criteria (Implicit from study goal): Achieving coagulation, uniform coagulation, and thermal performance equivalent to predicate device.
• Reported Device Performance:
  • Study 1 (Ex-vivo thermal study - tissue effects): "Coagulation was observed when treatment was performed with five stacked pulses with the interval of 200ms (within the same treatment spot without moving the tip). Coagulation surface correlated to the perimeter of the RF tip treatment surface. Uniform coagulation at entire perimeter and depth was observed in tested tissues."
  • Study 2 (Ex-vivo thermal study - temperature-time curves): "The ex-vivo dermal temperature testing confirmed that the XERF device's thermal performance is equivalent to that of the Thermage FLX device in terms of time-dependent heating and cooling behavior."

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

• Sample Size: Not explicitly stated for the ex-vivo studies.
• Data Provenance: Ex-vivo (not human/clinical) tissues: kidney, liver, and skin. No country of origin mentioned for the tissues.

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

• Not applicable as no clinical ground truth was established. The tissue analysis involved standard H&E histology performed on biopsy samples. The expertise of those analyzing the histology (e.g., pathologist) is not specified.

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

• Not applicable as no clinical ground truth was established by experts.

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 MRMC study was done. This device is an electrosurgical unit, not an AI diagnostic/imaging device.

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

• Not applicable. This is a medical device, not an algorithm, and its performance was assessed ex-vivo.

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

• For the ex-vivo tissue study: Histology (H&E staining and analysis under light microscope) was used to assess coagulation.
• For the ex-vivo thermal curve study: Direct temperature measurements using fiber optic sensors.

8. The sample size for the training set:

• Not applicable. The device is not an AI/ML algorithm that requires a training set in the conventional sense. The studies described are performance validation tests for the device itself.

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

• Not applicable.

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The Duoblade Plus SE (Models: DB1EP, DB1EP-T, DB1EP-H, DB1EP-TH), and Duoblade Prime (Models: DB1P, DB1P-T, DB1P-H, DB1P-TH) are intended for general electrosurgical applications, including cutting and coagulation. These models are designed without shaft extension functionalities. The Model: DB1EP, DB1EP -T, DB1EP-H, DB1EP-TH are compatible with the smoke evacuation system, removing smoke generated by electrosurgery when used in conjunction with an effective smoke evacuation system.

The Electrosurgical Cutting and Coagulation Device and Accessories (Model: Duoblade Plus SE, Duoblade Prime) is a single-use, monopolar RF device designed to be used with a qualified Generator as part of the Surgery System. It uses high-frequency energy (RF Monopolar Energy) to generate heat for tissue cutting and coagulation. It can be operated using the integrated hand switch or a qualified Footswitch. The device's design simplifies functionality by excluding shaft extension features. The models of Duoblade Plus SE and Duoblade Prime are identified according to with/without a suction function (removing smoke), and a swivel function.

• Suction & swivel function (Duoblade Plus SE): DB1EP, DB1EP-T, DB1EP-H, DB1EP-TH
• No Suction & swivel function (Duoblade Prime): DB1P, DB1P-T, DB1P-H, DB1P-TH
  The scope of the submission only includes the addition of model without functions, such as swivel function, shaft extension function and appearance change for marketing purpose.

The provided FDA 510(k) clearance letter and summary are for an electrosurgical device (Duoblade Plus SE, Duoblade Prime), not an AI/software device that would involve a test set, ground truth experts, or MRMC studies. The document primarily focuses on demonstrating substantial equivalence to a predicate device through comparison of features, materials, and established non-clinical tests relevant to electrosurgical devices (e.g., biocompatibility, sterility, electrical safety, thermal effects on tissue).

Therefore, I cannot extract the information required by your prompt regarding acceptance criteria, test set details, ground truth establishment, or human reader effectiveness studies, as these concepts are not applicable to the type of device described in this 510(k) submission.

The document states:

• "No clinical studies were considered for this submission." This directly indicates that there was no human-in-the-loop performance study, nor any evaluation of "how human readers improve with AI vs without AI assistance" because there's no AI component.
• "The thermal effects of a subject device are the same as the predicate device." This highlights that the performance demonstration relies on equivalence to a previously cleared device, not on new independent performance metrics against a defined acceptance criterion of the type you've outlined. The non-clinical test mentioned ("Thermal effects on tissue") is a comparative study against a positive control device, not a test with a specific quantitative acceptance criterion for the new device on its own.

In summary, because this 510(k) submission is for a physical electrosurgical device and not an AI/software product, the requested information about acceptance criteria for AI performance, test sets, ground truth experts, and MRMC studies is not present in the provided text.

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The Swift™ System is a surface-based device intended for the coagulation of soft tissue during non-invasive procedures.

The Swift™ System is not indicated for use in genital warts or cardiac procedures.

Specific Indication: Treatment of Common and Plantar Warts.

The swiftPro™ System is a surface-based device intended for the coagulation of soft tissue during non-invasive procedures.

The swiftPro™ System is not indicated for use in genital warts or cardiac procedures.

Specific Indication: Treatment of Common and Plantar Warts.

The Swift™ System is a microwave-based system intended to delivery energy through a surface contact applicator into targeted soft tissue for the purpose of coagulating (ablation) a pre-defined volume of tissue. The Swift™ System serves as a predicate device to the swiftPro™ System, which was originally cleared under 510(k) K222388. The swiftPro™ System is a handheld microwave generator designed to provide the same functionality as the Swift™ System in a more compact package.

The Swift™ System (SWF-SYS) consists of the following components:

• Swift™ Microwave Generator (SWF-GE01)
• Swift™ Applicator Handpiece (SWF-HP01)
• Swift™ Interconnect Cable (SWF-CA01)
• Swift™ Applicator Tip (SWF-AT01)

The Swift™ System was previously cleared under 510(k) K181941.

The swiftPro™ System (SWF-SPS) consists of the following components:

• swiftPro™ Handheld Microwave Generator (SWF-HAN01)
• swiftPro™ DC Power Cable (SWF-DCA01)
• swiftPro™ Cradle (SWF-CRA01)
• swiftPro™ Applicator Tips (SWF-AT02, SWF-AT03)

The swiftPro™ System was initially cleared under 510(k) K222388 and subsequently received updated clearance under K240518 to include the swiftPro™ Charging Dock (SWF-CHA01) and Battery Pack (SWF-BAT01) for cordless operation.

There have been no modifications to the design, principles of operation, or materials used in the Swift™ and swiftPro™ Systems. The clinical functionality of delivering treatment remains unchanged.

Here's an analysis of the provided information regarding the acceptance criteria and the study that proves the device meets those criteria:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document details a non-inferiority clinical study comparing the Swift™ System to cryotherapy for the treatment of common and plantar warts. The primary effectiveness endpoint was "Clearance of all treated warts, each of which is defined as "resolved" or "not resolved" based on the classification by the blinded site investigator assessing the treated warts at three months post final treatment (up to 5 warts in total per subject)."

The acceptance criteria for non-inferiority are not explicitly stated as a numerical threshold (e.g., "non-inferiority margin of X%"). Instead, the study's goal was to demonstrate that the Swift System was not worse than cryotherapy by a significant amount. However, the study failed to meet its primary endpoint for non-inferiority due to insufficient data. Despite this, the effectiveness results were very close, and safety data was favorable for the Swift System.

Given the information, we can construct the following table for effectiveness:

Safety Acceptance Criteria and Performance (Implicit - reasonable assurance of safety)

The document primarily highlights the safety profile of the Swift System compared to cryotherapy. The implicit acceptance criterion would be a reasonable assurance of safety, with no serious adverse events and a comparable or better safety profile than the predicate.

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

• Test Set Sample Size:
  • Randomized subjects: 119
  • Evaluable Per Protocol Population (for primary endpoint): 93 subjects (49 in Swift System group, 44 in cryotherapy group)
• Data Provenance:
  • Country of Origin: US
  • Retrospective or Prospective: Prospective (Randomized, multi-site, open, parallel-group, controlled, blind-assessed clinical study).

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

The document states "blinded site investigator assessing the treated warts." The number of investigators and their specific qualifications (e.g., dermatologists, years of experience) are not specified in this summary.

4. Adjudication Method for the Test Set

The primary endpoint involved assessment by a "blinded site investigator." There is no explicit mention of an adjudication method (e.g., 2+1, 3+1 consensus) if there were disagreements among investigators, or if multiple investigators were used per patient. The phrasing "blinded site investigator" suggests a single investigator making the assessment at each site, blind to the treatment arm.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This was a comparative clinical trial involving a device and a standard-of-care treatment, not an imaging-based "reader" study for diagnostic performance. Therefore, an effect size of human readers improving with AI vs. without AI assistance is not applicable here.

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

No, a standalone algorithm performance study was not done. The device itself is a microwave ablation system, not an AI/software algorithm for diagnosis or interpretation. The clinical study evaluated the device's therapeutic effect with human operators.

7. The Type of Ground Truth Used

The ground truth for the primary effectiveness endpoint was based on a clinical assessment by a blinded site investigator, using specific criteria:

• lesion no longer visible, and
• return of dermatoglyphics to the affected area, and
• no pain on lateral compression.

This is a form of expert clinical assessment/consensus based on predefined objective and subjective criteria.

8. The Sample Size for the Training Set

The document describes a single pivotal clinical study to support the expanded indication. This study is the dataset used to evaluate the device against the expanded indication. There is no mention of a separate training set for an algorithm, as this is a physical device, not an AI algorithm requiring a training phase in the context of this 510(k) summary.

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

As there is no explicit training set for an algorithm mentioned in this summary, the question of how its ground truth was established is not applicable in this context. The clinical study described served as the primary evidence for the device's safety and effectiveness for its intended use.

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