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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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The Canady Flex RoboWrist is intended for grasping, mobilization, transection, suturing, and/or electrocautery of tissue under direct and endoscopic visualization.

The Canady Flex RoboWrist is a motorized, hand-held laparoscopic surgery instrument available with hook, scissors, or needle holder end-effectors. The device includes a connector for an electrosurgical generator, which allows the option of using the mono scissors or hook for electrosurgery. The Canady Flex RoboWrist primarily intended for dissection, and/or suturing of tissue under direct and endoscopic visualization in minimally invasive surgical procedures for interventions such as laparoscopic (urologic, gynecologic) or thoracic surgeries.

The Canady Flex RoboWrist is composed of an instrument (with end-effectors) and a control unit, which provides power to the instrument. Three models of instruments are available: needle-holder, monopolar hook and monopolar scissors. An electrical cable is provided to connect the instrument to the control unit. It is also provided with a sterilization tray.

The provided text is a 510(k) summary for the Canady Flex RoboWrist, an endoscopic instrument. This document describes the device, its intended use, and how it demonstrates substantial equivalence to a predicate device. However, it does not include detailed acceptance criteria or a study that evaluates the device's performance against specific clinical or diagnostic metrics, as would be expected for an AI/ML-driven device with performance claims.

Instead, the document focuses on non-clinical performance data to demonstrate safety and effectiveness for a surgical instrument. The key takeaway is that this is not an AI/ML device and therefore the questions about AI-specific performance criteria, ground truth, expert adjudication, and MRMC studies are not applicable.

Here's an analysis based on the provided text, highlighting what is present and what is not:

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

The document does not specify quantitative acceptance criteria in the typical sense for a medical device with performance metrics (e.g., sensitivity, specificity, accuracy). Instead, it lists various non-clinical tests that were performed to evaluate conformance to product specifications.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

Not applicable. The "test set" here refers to physical components of the device and its performance in a lab setting, not a dataset of patient images or clinical outcomes.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Not applicable. This device is an endoscopic surgical instrument, not an AI/ML diagnostic or prognostic tool. "Ground truth" for this device would relate to engineering specifications, material properties, and functionality demonstrations performed by engineers and technicians, not clinical experts establishing diagnostic accuracy.

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

Not applicable. There is no clinical test set requiring adjudication in the context of an AI/ML device.

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/ML-assisted device.

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

No. This is a surgical instrument operated by a human.

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

For the non-clinical tests, the "ground truth" is defined by the requirements and specifications of the referenced ISO and IEC standards (e.g., a material is cytotoxic or not based on ISO 10993-5 criteria; electrical safety is met if measurements are within IEC 60601-1 limits). For functionality, it's whether the device can successfully manipulate, cut, and suture tissue as intended.

8. The sample size for the training set

Not applicable. This device does not involve a training set as it is not an AI/ML device.

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

Not applicable. No training set is involved.

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The Canady Plasma® SMART XL-1000™ Electrosurgical Generator with Accessories is intended to provide gas-enhanced coagulation during general surgery procedures. The Canady Plasma® SMART XL-1000™ Electrosurgical Generator with Accessories is designed for gas enhanced coagulation when used only with the Canady Plasma Electrosurgery Unit and compatible monopolar and/or bipolar handpieces.

The Canady Electrosurgery Unit Generators are intended to cut and/or coagulate tissue when used with compatible monopolar and/or bipolar RF handpieces. The Canady Electrosurgery Unit Generators are capable of monopolar argon gas enhanced coagulation when used with Canady Plasma Coagulator and probes.

The Canady Plasma® SMART XL-1000™ Electrosurgical Generator (CPSXEG) with Accessories is a High Frequency (HF) Electrosurgery Unit (ESU) used in combination with electrosurgical probes. The CPSXEG combines (HF) voltage to electrically enhanced plasma gas (i.e. Argon) to produce a plasma gas stream. Current density upon arrival at the tissue surface from Canady Plasma Probes causes coagulation of the tissue. The CPSXEG is also a monopolar and bipolar RF surgical device for cutting and coagulation. It is used for tissue removal and coagulation in accordance with the operative procedure performed by the physician. The unit provides various cutting, coagulation, hybrid plasma, and argon plasma modes to meet the physician's flexibility performing the specific procedure with the device.

The modified Canady Plasma Smart XL-1000™ ESU has the same intended use as the predicate SS-601/Argon 4 Canady Plasma® Electrosurgical Unit as well as the same performance specifications. The modified device has the same protective circuits as the predicate ESU which displays the equipment output error on the monitor screen with a graphic symbol so that the user can determine the cause of the error. The packaging, labeling (i.e. user manual) are the same.

The Canady Plasma® SMART XL-1000™ Electrosurgical Generator has a touch screen color monitor that provides the user with quick start, on screen tutorial and user manual as well as operational and settings. Various cutting, coagulation, bipolar, and plasma modes are the predicate unit, but the modified device has improved programmable software. When turned on, an APPS screen is displayed on the monitor screen. The user can decide which medical application is started by touching the particular application (i.e Pediatrics, orthopedics, endoscopy, gynecology). Upon activation of the device audio and visual error system malfunctions or user errors can be observed by the user. Once the device is activated, power in watts, gas flow rate, gas volume, PPM, and energy mode are displayed on the monitor screen.

The provided text describes a 510(k) premarket notification for the Canady Plasma® SMART XL-1000™ Electrosurgical Generator with Accessories. This is a submission to demonstrate substantial equivalence to a predicate device, rather than a study proving the device meets specific acceptance criteria in a clinical context.

Therefore, many of the requested details, such as sample sizes for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, and training set information, are not applicable or available in this type of regulatory document.

The document focuses on non-clinical performance data and a comparison to a predicate device to establish substantial equivalence.

Here's the information that can be extracted relevant to acceptance criteria and performance:

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

The document does not present "acceptance criteria" in the typical sense of a clinical performance study with specific endpoints and thresholds. Instead, it demonstrates performance through the comparison of technological characteristics with a predicate device and extensive non-clinical testing.

The acceptance criteria for this submission are implicitly that the modified device should perform as specified, in accordance with the predicate device's specifications, and not raise new questions of safety or effectiveness. The reported "performance" is that it meets these expectations.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not provided in the document. The testing described is non-clinical laboratory testing performed by the manufacturer, not a clinical trial or study with human subjects.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This information is not applicable/provided. The testing performed is non-clinical performance and safety testing of an electrosurgical generator, not a diagnostic device requiring expert interpretation for ground truth establishment.

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

This information is not applicable/provided. Adjudication methods are typically used in clinical studies involving interpretation of data/images, which is not the nature of this submission.

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

This information is not applicable/provided. The device is an electrosurgical generator, not an AI-assisted diagnostic or image interpretation tool. Therefore, MRMC studies and AI-related effect sizes are irrelevant to this submission.

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

This information is not applicable/provided. The device is a medical instrument (electrosurgical generator), not an algorithm that operates in a standalone capacity without human interaction in a clinical setting.

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

This information is not applicable/provided in the context of clinical ground truth. For the non-clinical performance testing, the "ground truth" would be the established engineering specifications and compliance standards (e.g., maximum power output, frequency deviation, electrical insulation integrity) which were measured and validated.

8. The sample size for the training set

This information is not applicable/provided. This is a hardware device with "improved programmable software," but the document does not describe it as an AI/ML device that undergoes a "training" process in the sense of predictive modeling.

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

This information is not applicable/provided for the reasons stated in point 8.

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