K Number
K241635
Manufacturer
Date Cleared
2024-08-05

(60 days)

Product Code
Regulation Number
878.4400
Panel
SU
Reference & Predicate Devices
Predicate For
N/A
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

The da Vinci E-200 Electrosurgical Generator is intended to deliver high-frequency energy for cutting, coagulation and vessel sealing of tissues in da Vinci robotic procedures, and non-robotic open and laparoscopic procedures.

Device Description

The da Vinci E-200 Electrosurgical Generator is an electrosurgical unit (ESU) designed to provide high-frequency (HF) traditional monopolar, bipolar, and advanced bipolar outputs intended for cutting, coagulation and/or vessel sealing of tissues. The da Vinci E-200 Electrosurgical Generator is intended to be used with the da Vinci Xi, and da Vinci 5 surgical systems, and also operate as a standalone electrosurgical generator. When connected to the E-200 provides HF output to da Vinci instruments. Control and status messages are passed between the E-200 and the da Vinci system through an Ethernet communication cable. The E-200 is also compatible with open and laparoscopic third-party handheld monopolar and bipolar instruments, fingerswitch equipped instruments (where applicable) and Intuitive provided auxiliary footswitches. The primary function of the E-200 Electrosurgical Generator is to allow a surgeon to deliver HF out, seal, or coagulate tissue during surgery. The user interface includes audible indicator tones, LED indicators on the front of the generator, and status messages provided on its LCD display.

AI/ML Overview

This document focuses on the da Vinci E-200 Electrosurgical Generator, which is an electrosurgical unit (ESU). The information provided is a 510(k) summary, which inherently focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed de novo study with strict acceptance criteria and performance metrics for a novel technology.

Therefore, the requested information elements related to standalone performance, MRMC studies, specific acceptance criteria values, sample sizes for test and training sets, and expert details for ground truth establishment are not explicitly described in the provided text in the manner typically found for AI/ML device studies. The document describes a traditional medical device (electrosurgical generator) and its safety and efficacy testing, not an AI/ML diagnostic or predictive system.

Here's an analysis based on the provided text, addressing the points where information is available or inferable:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not provide a table with specific numerical acceptance criteria and corresponding reported device performance values. Instead, it states that "Verfication and validation activities were successfully completed that the subject device performs as intended and is substantially equivalent to its predicate."

The "acceptance criteria" are implied by the successful completion of the following testing types:

Test TypeImplied Acceptance Criteria / Performance Demonstrated
Design Verification (Bench Testing)Functional design outputs were met. Specifically: Software requirements (including cybersecurity) were met.EMC (Electromagnetic Compatibility) and Electrical Safety requirements were met.System interface requirements were met.Instrument compatibility requirements were met.Packaging and Labeling requirements were met.
Design Validation (Simulated Clinical Use)Product specifications continued to meet the users' needs and intended use in a simulated clinical environment. (Performed with a porcine model, implying demonstration of cutting, coagulation, and vessel sealing efficacy and safety in tissue.)
Human Factor EvaluationThe device was determined to be safe and effective for its intended uses by the intended users in the intended use environment.

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

  • Sample Size for Test Set: Not explicitly stated. For bench testing, this would refer to the number of test cases or iterations. For simulated clinical use, it refers to the number of porcine models or procedures performed.
  • Data Provenance:
    • Bench Testing: Likely internal laboratory testing at Intuitive Surgical.
    • Simulated Clinical Use: Performed with a porcine model, indicating animal tissue (non-human, in vivo or ex vivo animal studies).
    • Retrospective or Prospective: These tests are inherently prospective, as they are conducted specifically for the submission.

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

This concept of "ground truth" established by experts, as typically applied to image-based AI diagnostics, is not directly applicable here. The device is an electrosurgical generator, and its performance (e.g., cutting efficacy, coagulation, vessel sealing) is assessed through objective measurements (bench testing) and direct observation/clinical evaluation (simulated clinical use).

For the Human Factor Evaluation, experts (likely human factors engineers and potentially medical professionals) would assess usability and safety, but they are evaluating the device's interaction with users, not establishing a "ground truth" for a diagnostic output.

4. Adjudication Method for the Test Set:

Not applicable in the context of electrosurgical generator testing as described. Adjudication methods (like 2+1 or 3+1) are typically used to resolve disagreements among multiple expert readers establishing ground truth for diagnostic decisions, which is not the primary output of this device.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done:

No, an MRMC comparative effectiveness study is not mentioned. Such studies are generally performed for diagnostic devices, especially those incorporating AI, to compare human performance with and without AI assistance. This device is a surgical tool, not a diagnostic one.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study was Done:

The "standalone" performance for this device refers to its ability to function as an electrosurgical generator without being integrated into a da Vinci robotic system. The device description explicitly states: "The da Vinci E-200 Electrosurgical Generator... also operate as a standalone electrosurgical generator." The testing described (bench testing, simulated clinical use, human factor evaluation) would have covered this standalone operation, ensuring its basic electrosurgical functions (cutting, coagulation, sealing) are performed as intended. However, "standalone" in the context of an algorithm's diagnostic performance (without human interpretation) is not relevant here.

7. The Type of Ground Truth Used:

  • Bench Testing: Engineering specifications, electrical safety standards, EMC standards, software requirements, measured physical parameters (e.g., power output, frequency).
  • Simulated Clinical Use (Porcine Model): Direct observation of tissue effects (e.g., cut quality, coagulation adequacy, seal strength) by qualified personnel, possibly confirmed by gross and/or histopathological examination. Performance against a "gold standard" of expected surgical outcomes for electrosurgery.
  • Human Factor Evaluation: Usability metrics, error rates, user feedback, adherence to human factors engineering principles.

8. The Sample Size for the Training Set:

Not applicable. This is not an AI/ML device that requires a training set of data. The "training set" concept is relevant for machine learning algorithms, which "learn" from data. This device is a traditional electrosurgical generator engineered to specific design parameters.

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

Not applicable for the same reason as point 8.

§ 878.4400 Electrosurgical cutting and coagulation device and accessories.

(a)
Identification. An electrosurgical cutting and coagulation device and accessories is a device intended to remove tissue and control bleeding by use of high-frequency electrical current.(b)
Classification. Class II.