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The ForceTriad is a full-featured electrosurgical generator intended for open and laparoscopic surgical procedures where the surgeon requires electrosurgical cutting (resecting, dividing, or separating), coagulation (hemostasis, coagulating, or desiccating), or vessel sealing or fusing.). The generator is intended for use in general, laparoscopic, and gynecologic surgical procedures where ligation of vessels, pulmonary vasculature, or lymph vessels, is desired. The system creates a vessel ligation (seal) by the application of bipolar electrosurgical RF energy (coagulation) to vessels interposed between the jaws of the device. The generator can also be used with standard bipolar devices where bipolar cutting or coagulation is desired or with compatible resectoscopes for endoscopically controlled removal (resection) or coagulation of tissue using 0.9% NaCl solution (saline) as the irrigation medium.

The indications for use include general (including urologic, thoracic, plastic, and reconstructive), laparoscopic, and gynecological procedures where electrosurgical cutting and coagulation of tissue, and sealing (fusion) of vessels, including pulmonary vessels, and tissue bundles is performed, including such procedures as bowel resections, hysterectomies (both vaginal and abdominal), laparoscopic cholesystectomies, laparoscopically assisted vaginal hysterectomies, gall bladder procedures, Nissen fundoplication, adhesiolysis, oophorectorny, etc. The devices can be used on vessels (arteries, veins. pulmonary arteries, pulmonary veins, lymph) up to 7mm and bundles as large as will fit in the jaws of the instruments.

The LigaSure tissue fusion function has not been shown to be effective for tubal sterilization or tubal coagulation for sterilization procedures. Do not use this function for these procedures.

The ForceTriad™ Electrosurgical Generator is a full-featured electrosurgical generator with monopolar, bipolar, and LigaSure™ vessel sealing output modes. TThe generator is an electrically isolated, microcontroller-based device, incorporating closed-loop control for all output modes implemented in the microcontroller firmware. The generator incorporates Instant Response™ technology to constantly measure the electrical impedance of the tissue and instantaneously adjust the generator output to maintain the desired power.

The generator is used with a selection of electrosurgical instruments designed for use with the ForceTriad and the LigaSure Vessel Sealing generator. All of the LigaSure instruments are capable of sealing vessels up to, and including, 7mm, and tissue bundles as large as can fit in the jaws of each instrument. When a LigaSure instrument is applied to a vessel or tissue bundle and RF energy is applied, the collagen and elastin in the tissues are reformed by heat and pressure to fuse vessel walls, thereby forming a permanent seal. The microprocessor in the generator monitors the tissue properties, stops the application of energy, and allows a brief period of cooling before indicating that the seal cycle is complete.

No changes are being made to the design, operation, or intended use of any of the current system except the software modifications to create the Bipolar Resection modes and to allow the ForceTriad to output system data to a computer. The subject of this 510(k) notification is in regards to the addition of specific definitions for "cut" and "coagulating" and the addition to the indications statement of a bipolar resection function for use with resectoscopes "for endoscopically controlled removal of tissue using 0.9% NaCl solution (saline) as the irrigation medium" and the hardware and software associated with the activation of this feature.

Here's an analysis of the provided text regarding the ForceTriad™ Electrosurgical Generator, focusing on acceptance criteria and supporting studies:

It's important to note that the provided document is a 510(k) premarket notification, which concerns substantial equivalence to predicate devices, rather than a detailed report of a new device's efficacy studies in the same way one might find for novel drug or medical device. Therefore, the information regarding specific acceptance criteria and detailed study outcomes for meeting those criteria is presented at a high level.

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not explicitly state the sample sizes (i.e., number of pork models or live porcine models) used for the bench and live animal testing. It also doesn't specify the country of origin for the data or whether the studies were retrospective or prospective, though animal model testing is inherently prospective.

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

This information is not provided in the document. The document refers to "bench testing" and "live porcine model" studies, but it doesn't detail how the "ground truth" or "acceptable results" were determined, nor does it mention the involvement or qualifications of experts in assessing the outcomes of these tests. For electrosurgical devices, ground truth might relate to tissue effects, seal integrity, or lack of collateral damage, which would traditionally be assessed by veterinary pathologists or surgeons.

4. Adjudication Method for the Test Set

This information is not provided in the document. Given the nature of bench and animal testing for an electrosurgical device, it's less likely to involve the same type of "adjudication" seen in image-based diagnostic studies. Performance would likely be assessed against predefined engineering specifications (e.g., power output, tissue cut/coagulation characteristics).

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• No MRMC study was done. The document explicitly states: "This premarket notification report does not rely on the assessment of clinical performance data to demonstrate substantial equivalence." This means there was no human reader study comparing effectiveness with and without AI assistance (as AI is not the primary focus here, rather software updates for device functionality).

6. Standalone (Algorithm Only) Performance Study

• No standalone algorithm performance study in the typical sense was performed or reported. This submission focuses on software updates to an existing electrosurgical generator to enable a bipolar resection feature. The "algorithm" here refers to the closed-loop control and Instant Response™ technology within the electrosurgical generator, which is designed to adjust output based on tissue impedance. The testing confirmed the device's functionality with these software updates, not an independent algorithm's diagnostic or predictive performance.

7. Type of Ground Truth Used

Based on the description of "bench testing using a pork model (to simulate prostate) and live porcine model using kidney (for hemostasis)," the ground truth for these tests would likely involve direct observation and measurement of tissue effects. This could include:

• Pathology/Histology: Microscopic examination of treated tissue to assess cut quality, depth of coagulation, cell viability, and collateral damage.
• Physiological Measurements: For hemostasis, this might involve quantitative measures of blood loss or time to achieve cessation of bleeding.
• Engineering Specifications: Measurement of power output, impedance feedback, and response times against predefined technical specifications.

The document states "Results were acceptable," implying that these assessments met predetermined performance standards.

8. Sample Size for the Training Set

The document does not mention a "training set" in the context of machine learning or AI algorithm development. The software updates relate to activating a specific electrosurgical mode and recognizing accessories, not to a learning algorithm requiring a distinct training phase. The "software validation" and "testing" refer to verification and validation of the software's functionality and safety, not training an AI model.

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

As there is no mention of a "training set" for an AI algorithm, this question is not applicable to the provided document. The ground truth for the testing that was performed (bench and live animal) would have been established as described in point 7.

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