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The da Vinci Trocar has application in a variety of endoscopic procedures to provide a port of entry for endoscopic instruments.

The Universal Seal (5-12 mm) is a sterile, single-use device. It provides a seal within a port of entry for endoscopes, instruments, and accessories with a diameter range between 5 mm and 12 mm. It also provides an attachment for insufflation accessories and allows for air to flow in or out of the body cavity while minimizing gas leakage.

I am sorry. This document does not contain information about acceptance criteria and device performance for an AI/ML device. It describes a medical device, the Universal Seal (5-12 mm), which is a physical seal used in endoscopic procedures. The document focuses on regulatory approval (510(k) clearance) based on substantial equivalence to a predicate device, specifically highlighting a minor material change and biocompatibility testing. It does not involve any AI or machine learning components.

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The da Vinci Trocar has application in a variety of endoscopic procedures to provide a port of entry for endoscopic instruments.

The Universal Seal (5-12 mm), as part of the da Vinci Trocar system, supports a port of entry for endoscopes, instruments, and accessories. It is intended to be used with a compatible da Vinci cannula to provide a seal within a port of entry for endoscopes, instruments, and accessories. It is intended to provide an attachment for gas insufflation while minimizing gas leakage.

The Universal Seal (5-12 mm) is a sterile, single-use device. It provides a seal within a port of entry for endoscopes, instruments, and accessories with a diameter range between 5 mm and 12 mm. It also provides an attachment for insufflation accessories and allows for air flow in or out of the body cavity while minimizing gas leakage.

The provided text is a 510(k) summary for the "Universal Seal (5-12 mm)" device. The document states that the device is "substantially equivalent" to a predicate device and details the performance testing conducted to demonstrate this equivalence. However, it does not describe a study involving an AI algorithm or human readers, but rather engineering-focused performance testing of a physical medical device (a cannula seal).

Therefore, I cannot provide a direct answer to your request as it pertains to AI algorithm performance evaluation. The document describes a traditional medical device submission, not an AI/ML medical device where acceptance criteria would involve metrics like accuracy, sensitivity, specificity, and human reader performance.

However, I can interpret the acceptance criteria and "proof" provided for this specific physical device based on the information given.

Based on the provided document for the "Universal Seal (5-12 mm)", here's a breakdown of the acceptance criteria and study that proves the device meets them:

Crucial Note: This document pertains to a physical medical device (a trocar seal), not an AI algorithm. Therefore, the "study" described is a series of engineering and biocompatibility tests, not a clinical trial or algorithm performance study with human readers. Many of the requested details (like ground truth establishment for AI, human expert involvement for AI interpretation, MRMC studies) are not applicable to this type of device submission.

Acceptance Criteria and Reported Device Performance (Non-AI Device)

The acceptance criteria for this physical device are implied by the "Design Verification" and "Design Validation" sections, which ensure the device functions as intended and meets user needs.

• "Successfully meets design inputs and user needs." (Implied) |
  | | - Torque Limits: (Within specified operational range) | - Bench testing performed for "Torque limits".
• "Successfully meets design inputs and user needs." (Implied) |
  | | - Force Limits: (Withstands expected operational forces) | - Bench testing performed for "Force limits".
• "Successfully meets design inputs and user needs." (Implied) |
  | | - Reliability: (Consistent performance over time/use) | - Bench testing performed for "Reliability".
• "Successfully meets design inputs and user needs." (Implied), Reliability testing also mentioned separately. |
  | Clinical Use Simulation | - Product Specifications meet user's needs & intended use | - "Simulated clinical use testing was performed with a porcine model to validate that the product specifications continued to meet the user's needs and intended use." (Successful completion implied by overall conclusion of substantial equivalence) |
  | Biocompatibility | - Meets recognized standards for biocompatibility | - "Determined that the subject device met the requirements of the recognized standards for biocompatibility for its intended clinical use." (ISO 10993-1:2018 and FDA Guidance) |
  | Shelf-Life | - Maintain a shelf-life of two years | - "Shelf-life testing was performed through an accelerated aging study to verify that the product can maintain a shelf-life of two years." (Successful verification implied) |
  | Packaging/Transit | - Withstands shipping conditions | - "Transit testing was performed in accordance with ASTM D4169-16, Standard Practice for Performance Testing of Shipping Containers and Systems." (Successful completion implied) |

Details of the "Study" (Performance Testing)

Given that this is a physical medical device (a cannula seal) and not an AI algorithm, many of the typical questions for AI studies are not applicable (N/A).

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

   • Test Set (Device Performance): The document refers to "a series of tests" and "bench testing." It does not specify sample sizes (e.g., number of seals tested for leakage, torque, etc.).
   • Data Provenance: N/A for country/retrospective/prospective as this refers to engineering and laboratory testing of a product. The testing was performed internally by the manufacturer, Intuitive Surgical, Inc.

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

   • Not Applicable. For this physical device, "ground truth" is established by engineering specifications, validated performance metrics via testing equipment, and adherence to recognized standards (e.g., ISO, ASTM, FDA guidance). There are no human experts interpreting data to establish a diagnostic "ground truth" in the way one would for an AI algorithm in medical imaging.

3. Adjudication method for the test set:

   • Not Applicable. Test results are quantitative measurements against predefined engineering specifications. There is no human interpretative "adjudication."

4. 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 type of study is specifically for AI-assisted diagnostic devices involving human readers. This device is a physical surgical seal.

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

   • Not Applicable. This is not an AI algorithm. Its performance is evaluated through bench testing and simulated use, not standalone algorithm metrics.

6. The type of ground truth used:

   • Engineering Specifications and Standard Compliance: The "ground truth" for this device's performance is adherence to its design inputs, functional specifications, and relevant industry standards (e.g., ISO 10993 for biocompatibility, ASTM D4169-16 for transit testing). For clinical utility, it's validated in a porcine model to confirm it meets user needs and intended use, but this is a validation against expected clinical function, not a diagnostic ground truth.

7. The sample size for the training set:

   • Not Applicable. This is not an AI algorithm; therefore, there is no "training set."

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

   • Not Applicable. As there's no training set for an AI algorithm, this question is irrelevant.

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