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510(k) Data Aggregation
(60 days)
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.
The da Vinci E-200 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 is intended to be used with the IS4000/IS4200 da Vinci surgical systems and also operate as a standalone electrosurgical generator. When connected to the da Vinci surgical system, 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 output to cut, seal, or coagulate human 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.
This document is a 510(k) premarket notification for the da Vinci E-200 Electrosurgical Generator, indicating that it is a medical device approval document and not a study on AI-assisted human reading, or a diagnostic AI device. Therefore, many of the requested criteria related to AI studies (e.g., sample size for test/training sets, ground truth establishment, expert adjudication, MRMC studies, standalone performance) are not applicable to this submission.
The document primarily focuses on demonstrating the substantial equivalence of the da Vinci E-200 Electrosurgical Generator to existing predicate devices through bench testing, in-vivo/ex-vivo models, and human factors evaluation, rather than evaluating an AI algorithm's performance in a diagnostic context.
However, I can extract and present the available information regarding the device's performance and acceptance criteria based on the provided text.
1. Table of Acceptance Criteria and Reported Device Performance
Since this is an electrosurgical generator rather than a diagnostic AI device, the "acceptance criteria" are related to its functional performance, safety, and equivalence to predicate devices, rather than typical diagnostic performance metrics (e.g., sensitivity, specificity, AUC). The document outlines various tests conducted to demonstrate the device meets its design requirements and is safe and effective.
| Category of Testing | Acceptance Criteria (Implied by Test Name) | Reported Device Performance (Summary from Document) |
|---|---|---|
| Design Verification | Device meets hardware, EMC, electrical safety, software (including cybersecurity), system interface, instrument compatibility, packaging, and labeling requirements. | "The subject device, E-200 Electrosurgical Generator, was subjected to series of tests to evaluate performance and to demonstrate that the design outputs meet the design input requirements." |
| Design Validation (In-vivo porcine model) | Safety and efficacy of the E-200 generator, its accessories, and its interaction with intended robotic and third-party instruments/accessories in a simulated surgical setting. Device fulfills user needs and intended use is met. | "Design validation demonstrated that the design outputs fulfill the user needs and that the intended use have been met." |
| Thermal Effects Testing | Comparable thermal effects on tissue to the predicate ForceTRIAD generator (K110268). | "The E-200 generator was found to have acceptable thermal effects when compared to the ForceTRIAD generator." |
| Neutral Electrode Contact Quality Monitor (CQM) Study | Conformance to IEC standards for the CQM system. Validation of the use of Covidien E7507 neutral electrode. | "The study validated the use of the Covidien E7507 neutral electrode (commercially available product) with the E-200 generator for CQM functionality." |
| Vessel Sealing Bench Testing (E-200 vs. E-100) | HF output characteristics are substantially equivalent to the predicate E-100 device (K191280) with no differences expected to change vessel sealing performance. | "The test demonstrated that the HF output characteristics of the two generators are substantially equivalent and that there are no differences which would be expected to result in a change in the vessel sealing performance." |
| Capacitive Coupling Evaluation | No significant increase in unintended capacitively coupled energy delivery compared to the predicate Covidien ForceTriad generator. | "This validation demonstrated that the E-200 generator had no significant increase in unintended capacitively coupled energy delivery when compared to the predicate Covidien ForceTriad generator." |
| Human Factors Evaluation (Usability Validation Study) | Safe and effective use of the E-200 generator and associated accessories by intended users in the intended use environment. | "The usability validation study demonstrated that the E-200 electrosurgical generator could be used safely and effectively by the intended users in the intended use environment." |
2. Sample Size Used for the Test Set and Data Provenance
- Test Set Sample Size: The document does not specify a numerical sample size for individual tests like "Design Verification" (bench testing), "Thermal Effects Testing," or "CQM Study." For the in-vivo validation, it mentions a "porcine model," but no specific number of animals or cases. Similarly, "vessel sealing bench testing" and "capacitive coupling evaluation" do not specify sample sizes.
- Data Provenance: The studies appear to be prospective bench tests and animal model studies conducted by the manufacturer, Intuitive Surgical, Inc. The document does not mention the country of origin for the data beyond implying it was conducted as part of the FDA submission process.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of those Experts
This concept is not applicable to this type of device submission. Ground truth in this context refers to the physical and electrical performance of an electrosurgical unit, verified through established engineering and medical device testing standards, rather than expert interpretation of medical images or data. Performance is measured against physical specifications and validated against in-vivo/ex-vivo results.
4. Adjudication Method for the Test Set
This concept is not applicable. Adjudication typically refers to resolving disagreements among human readers or labelers in diagnostic AI studies. The performance validation of an electrosurgical generator involves objective measurements and functional tests, not human interpretation that requires adjudication.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done
No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This type of study is relevant for evaluating the impact of AI assistance on human reader performance in diagnostic tasks, which is not the purpose of this submission for an electrosurgical generator.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done
Not applicable in the context of AI algorithm performance. The "standalone" operation mentioned in the document refers to the E-200 Electrosurgical Generator operating independently of the da Vinci robotic system, as a traditional ESU. It's a device operating standalone, not an AI algorithm.
7. The Type of Ground Truth Used
The "ground truth" for this device's performance is established by:
- Design Input Requirements/Specifications: The device's performance is validated against its pre-defined engineering and functional requirements.
- Industry and IEC Standards: Conformance to relevant electrical safety and performance standards.
- Predicate Device Performance: Demonstrating comparable performance to legally marketed predicate devices (Covidien ForceTRIAD and Intuitive E-100) through direct comparative testing (e.g., thermal effects, HF output characteristics, capacitive coupling).
- In-vivo/Ex-vivo Models: Actual physiological effects in tissue (e.g., cutting, coagulation, vessel sealing effectiveness) observed in animal (porcine) models and ex-vivo settings.
- User Needs/Safe and Effective Use: Confirmed through human factors evaluation with intended users.
8. The Sample Size for the Training Set
Not applicable. This submission is for an electrosurgical generator, not an AI model, so there is no "training set."
9. How the Ground Truth for the Training Set was Established
Not applicable. As there is no AI model or training set, the concept of establishing ground truth for it does not apply.
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(61 days)
The Epix Electrosurgical Probe with Smoke Evacuation is intended to deliver energy from an independent monopolar electrosurgical generator to cut and coagulate tissue during laparoscopic surgical procedures where the device is introduced into the body through a cannula. The device may be used for the evacuation of smoke created by electrosurgery at the surgical site.
The Epix Electrosurgical Probe with Smoke Evacuation is a sterile, single-use monopolar instrument equipped with a smoke evacuation feature. The proposed device uses RF energy provided by a generator to electrosurgically cut and/or coagulate tissue during general laparoscopic procedures. The electrosurgical probes are available in three different tip geometries with probe lengths ranging between 20cm - 45cm. All models are constructed of the same materials and by similar manufacturing assembly processes.
This document from the FDA describes the substantial equivalence determination for the "Epix Electrosurgical Probe with Smoke Evacuation" (K171684) compared to a predicate device, the "Epix Electrosurgical Probes" (K132300).
The provided text does not contain the detailed acceptance criteria or the specific study results in the format requested. It states that certain performance tests were conducted and that the device "Met Acceptance Criteria" or was "Substantially Equivalent," but it does not specify what those criteria were (e.g., a numerical threshold or a specific characteristic being achieved) or the quantitative results of the tests.
Therefore, I cannot fulfill all parts of your request with the given information. However, I can extract the available information regarding performance data.
Here's what can be extracted based on the provided text:
1. A table of acceptance criteria and the reported device performance
| Test | Reported Device Performance |
|---|---|
| Electrosurgical Performance | Substantially Equivalent |
| Smoke Evacuation Performance | Substantially Equivalent |
| Biocompatibility | Met Acceptance Criteria |
| Mechanical Testing | Met Acceptance Criteria |
| Electrical Safety Testing | Met Acceptance Criteria |
| Electromagnetic Compatibility (EMC) Testing | Met Acceptance Criteria |
Missing Information: The document does not specify the actual acceptance criteria (e.g., "electrical impedance within X ohms," "smoke evacuation rate of Y L/min") for each test, only that they were met or that the device was substantially equivalent.
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample Size for Test Set: Not specified.
- Data Provenance: Not specified. It can be inferred that the testing was conducted by Applied Medical Resources Corporation for this FDA submission, likely within the US, but this is not explicitly stated.
- Retrospective or Prospective: Not specified. These were likely laboratory-based performance and safety tests rather than clinical studies.
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 and not provided. The performance tests described (Electrosurgical, Smoke Evacuation, Biocompatibility, Mechanical, Electrical Safety, EMC) are engineering and laboratory-based tests, not clinical evaluations requiring expert interpretation of results for ground truth establishment.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- This information is not applicable and not provided. Adjudication methods are typically used in clinical studies for interpretation of subjective findings. The tests performed are objective performance measurements.
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 comparative effectiveness study was done. The device is a physical electrosurgical probe, not an AI-assisted diagnostic tool.
- The document explicitly states: "No animal or clinical studies were required to demonstrate the safety and efficacy of the subject device in support of this application for premarket clearance."
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- This question is not applicable as the device is a physical electrosurgical probe, not an algorithm or AI system.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
- For the performance tests listed, the "ground truth" would be established by validated test methodologies and engineering specifications, rather than clinical ground truth types like pathology or expert consensus. For example, for electrical safety, the ground truth is adherence to IEC standards. For biocompatibility, it's compliance with ISO 10993 series.
8. The sample size for the training set
- This information is not applicable as the device is a physical electrosurgical probe, not a machine learning or AI device that requires a training set.
9. How the ground truth for the training set was established
- This information is not applicable for the same reason as above.
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(59 days)
The BiZact™ device is a bipolar instrument intended for use in open surgical procedures where ligation and division of vessels, tissue bundles, and lymphatics is desired.
The tissue fusion function of the device can be used on vessels (arteries and veins) and lymphatics up to and including 3 mm diameter. The BiZact device is indicated for use in open general surgical procedures.
It is also indicated for adult ENT procedures, including tonsillectomy for the ligation and division of vessels, tissue bundles and lymphatics 2-3 mm away from unintended thermally sensitive structures.
The BiZact™ device has not been shown to be effective for tubal sterilization or tubal coagulation for sterilization procedures. Do not use for these procedures.
The BiZact™ Tonsillectomy Device Advanced Bipolar Tissue Sealer/Divider is a sterile, single use, hand-held electrosurgical device that incorporates RF tissue fusion technology for a desired tissue effect when used with the ForceTriad Energy Platform (K051644, K070162, K102913, and K110268), the Valleylab™ LS10 LS Series Single Channel Vessel Sealing Generator (K143654), or the Valleylab FT10 Energy Platform (K151649, K170170) for ligation and division of vessels, tissue bundles, and lymphatics during open general surgical procedures.
The BiZact™ Tonsillectomy Device Advanced Bipolar Tissue Sealer/Divider attaches to a compatible electrosurgical generator with a 10 foot cord containing a proprietary connector. The generator is able to identify the BiZact™ device via the RFID tag embedded in the connector (Valleylab LS10 LS Series single Channel Vessel Sealing Generator and Valleylab FT10 Electrosurgical Platform) or with a barcode on the connector (ForceTriad). The generator delivers energy to the device using a defined algorithm that adjusts the generator output as a function of the electrical resistance of the combination of the BiZact instrument and the generator algorithm achieve complete and permanent tissue fusion.
The provided document is a 510(k) premarket notification for a medical device (BiZact Tonsillectomy Device) and does not contain information about an AI/ML-based device or its performance criteria related to AI/ML tasks.
Therefore, I cannot extract the requested information regarding acceptance criteria and study details for an AI/ML device's performance. The document focuses on the substantial equivalence of a physical electrosurgical device to a predicate device, based on mechanical, electrical, functional, biocompatibility, sterilization, and animal (ex-vivo/in-vivo) studies.
The request asks for:
- Table of acceptance criteria and reported device performance (for AI/ML): Not applicable, as this is not an AI/ML device. The document summarizes various engineering and biological tests, but not specific AI performance metrics like sensitivity, specificity, or AUC.
- Sample size for test set and data provenance: The document mentions "fresh porcine renal arteries" for burst pressure, "porcine model" for lymphatic and acute hemostasis studies, and a "chronic hemostasis porcine study." It does not specify sample sizes in terms of number of cases for these animal studies beyond indicating they were sufficient for verification. Data provenance is "porcine model" (animal data), which is prospective in the context of these experiments. There is no human patient data test set for AI.
- Number of experts and qualifications for ground truth: Not applicable for an AI/ML device. Ground truth in this context would be physical measurements, biological response, or pathological findings from the animal studies, not expert consensus on AI outputs.
- Adjudication method: Not applicable for an AI/ML device.
- MRMC comparative effectiveness study: Not applicable, as there's no AI component or human reader interaction with AI.
- Standalone AI performance: Not applicable.
- Type of ground truth: For the physical device, it's based on physiological and pathological outcomes in animal models (e.g., vessel burst pressure, acute hemostasis, lymphatic sealing, lateral thermal spread over time).
- Sample size for training set: Not applicable, as there is no AI training set.
- How ground truth for training set was established: Not applicable.
In summary, the provided document describes a medical device clearance for an electrosurgical tool, not an AI/ML device. Therefore, none of the requested information pertaining to AI/ML acceptance criteria and performance studies can be found or inferred from the text.
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(101 days)
The Valleylab LS10, LS Series Single Channel Vessel Sealing Generator is an electrosurgical generator containing LigaSure vessel sealing technology.
The vessel sealing function is indicated for use in sealing (fusing) vessels (including pulmonary) up to and including 7mm in diameter, tissue bundles, and lymphatics during general surgery including, but not limited to surgical specialties such as urologic, vascular, thoracic, gynecologic, plastic and reconstructive, and colorectal.
Refer to each instrument's instructions for use (IFU) for additional indications, warnings, and specific contraindications.
The LigaSure system has not been shown to be effective for tubal coagulation for sterilization procedures. Do not use this function for these procedures
Valleylab™ LS10, LS Series Single Channel Vessel Sealing Generator (VLLS10GEN) is a bipolar electrosurgical generator with LigaSure™ vessel sealing output mode. The generator is an electrically isolated, microcontroller-based device, incorporating closed-loop control for LigaSure™ mode implemented in the microcontroller firmware. It incorporates tissue sensing circuitry to constantly measure the electrical resistance of the tissue and instantaneously adjust the generator output to maintain the desired power.
The generator is used with compatible LigaSure™ instruments to ligate (seal) and divide (cut) vessels up to and including 7mm, tissue bundles, and lymphatics during the general surgical procedures using radio frequency (RF) energy. When a LigaSure™ instrument is applied to a vessel or tissue bundles, and RF energy is activated by the generator, the collagen and elastin in the tissues are reformed by heat and pressure to fuse vessel walls, thereby forming a permanent seal. The microprocessor within 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.
This document is a 510(k) premarket notification for the Valleylab™ LS10, LS Series Single Channel Vessel Sealing Generator (VLLS10GEN). The purpose of this notification is to demonstrate that the new device is substantially equivalent to a legally marketed predicate device.
Here's an analysis based on your request:
1. Table of Acceptance Criteria and Reported Device Performance
The submission does not explicitly list "acceptance criteria" in a quantitative format typical for AI/ML device performance alongside reported device performance. Instead, it focuses on demonstrating that the new device (VLLS10GEN) operates "as intended" and is "substantially equivalent" to its predicate device (ForceTriad™ Electrosurgical Generator) through various bench and preclinical tests.
The performance is primarily evaluated against established medical device standards and functional objectives, rather than specific numerical thresholds for a diagnostic outcome that would have clear acceptance criteria (e.g., sensitivity > X%, specificity > Y%).
| Acceptance Criteria (Implied from testing intent) | Reported Device Performance (Summary from submission) |
|---|---|
| Compliance with Electromedical Safety Standards (IEC 60601-1, 60601-2-2) | Demonstrated compliance through testing. |
| Compliance with Electromagnetic Compatibility (EMC) Standards (IEC 60601-1-2) | Demonstrated compliance through testing. |
| Software Verification & Validation (IEC 62304) | V&V performed in accordance with standards. |
| Engineering, Mechanical, Electrical, and General Functional Testing | Device operated as intended, demonstrating proper function. |
| Vessel Sealing Performance: Up to 7mm vessel sealing (e.g., maintaining burst pressure) | Demonstrated ability to seal and divide vessels up to and including 7mm. |
| Hemostasis of tissue and tissue bundles | Demonstrated ability to achieve hemostasis. |
| Thermal Profile (e.g., max jaw temp, cool down, shaft temp) | Thermal profile characterized; device performed within safe limits. |
| Lymphatic Burst Pressure | Demonstrated sufficient lymphatic burst pressure. |
| Chronic Animal Study Outcomes | Performed to assess long-term effects and efficacy. (Specific outcomes not detailed in summary, but implied acceptable). |
| Equivalent LigaSure sealing performance to predicate | Achieved equivalent LigaSure sealing performance. |
2. Sample Size Used for the Test Set and the Data Provenance
The document does not specify a "test set" in the context of AI/ML models (i.e., a dataset of cases used to evaluate an algorithm's performance). Instead, it refers to various bench and preclinical testing regimes. The sample sizes for these tests are not provided in this summary.
- Bench Testing: Includes renal and pulmonary burst pressure, thermal profile, and general functional/electrical/mechanical tests. The number of samples for each specific test (e.g., number of vessels tested for burst pressure) is not disclosed.
- Preclinical Testing: Includes animal studies for sealing and dividing vessels, hemostasis, thermal spread, lymphatic burst pressure, and chronic animal studies. The number of animals or vessels/tissues tested is not disclosed.
- Data Provenance: The tests were conducted by Covidien, the manufacturer. The location of these tests (e.g., country of origin) is not specified, but Covidien's address is Boulder, Colorado. The data is prospective as it was generated specifically to test the device.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Experts
This type of information is generally relevant for AI/ML diagnostic devices where human experts independently review cases to establish a "ground truth" diagnosis. Since this device is an electrosurgical generator, the "ground truth" is established by direct physical measurements and observations during bench and preclinical testing (e.g., direct measurement of burst pressure, visual assessment of hemostasis, pathological examination from animal studies). Therefore:
- Number of experts: Not applicable in the traditional sense of human readers reviewing cases.
- Qualifications of experts: The scientific and engineering staff conducting the testing would have the relevant qualifications (e.g., biomedical engineers, veterinarians, surgeons performing or observing preclinical studies), but specific numbers and qualifications are not detailed.
4. Adjudication Method for the Test Set
Not applicable in the AI/ML diagnostic context. The results of the physical and functional tests are typically objective measurements or observations following defined protocols, not subjective interpretations requiring adjudication.
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, an MRMC comparative effectiveness study was not done. This type of study is specific to AI/ML diagnostic or assistive tools where human readers are involved in interpreting medical images or data, and the AI's impact on their performance is being evaluated.
- The Valleylab™ LS10 is an electrosurgical generator, not a diagnostic AI tool. Its performance is assessed through its physical operation and effect on tissue.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done
- Yes, in spirit, standalone performance was done. The entire bench and preclinical testing described (IEC standards compliance, engineering tests, burst pressure, thermal profiles, chronic animal studies) represents the "standalone" performance of the device itself.
- The device (generator) operates autonomously to deliver energy and seal vessels, with the surgeon as the operator, not as an "interpreter" of an algorithm's output. The performance metrics listed directly assess the device's functional integrity and its intended biological effects.
7. The Type of Ground Truth Used
The "ground truth" for this device's performance is established by:
- Direct physical measurements: Pressure readings for burst pressure, temperature measurements for thermal profiles, electrical output measurements.
- Pathological assessment: Tissue analysis (e.g., from preclinical animal studies) to confirm seal integrity, thermal spread, and absence of adverse effects.
- Functional observation: Direct observation of device operation and its effects during preclinical procedures (e.g., visual confirmation of hemostasis).
- Compliance with validated standards: Meeting predefined safety and performance requirements outlined in IEC standards.
8. The Sample Size for the Training Set
- Not applicable. This device is hardware (an electrosurgical generator) with embedded firmware/software for control. It is not an AI/ML system that learns from a "training set" of data in the conventional sense (e.g., images for classification).
- The device's algorithms (e.g., for tissue sensing and energy adjustment) are programmed based on engineering principles and extensive prior knowledge of electrosurgical physics and biology, not "trained" on a dataset in the way a neural network is.
9. How the Ground Truth for the Training Set Was Established
- Not applicable. As there is no "training set" for an AI/ML algorithm in this context, there is no ground truth to be established for it. The underlying principles of the device's operation are based on validated scientific and engineering models.
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