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This device is a sterile, single-use device and indicated for use in general, thoracic, gynecologic, or minimally invasive procedures to establish a path of entry for minimally invasive instruments.

The NexPort™ Trocar System is a basic equipment used during laparoscopic surgical, and the surgical device will enter into abdominal cavity via the passage established by the trocar. The proposed devices are available to accommodate 5mm and 10mm surgical instruments.

The 5mm NexPort™ Trocar System is consisted of:

• Obturator Shaft a)
• Cannula Cap b)
• Seal c)
• Duckbill Valve d)
• e) Cannula Body
• f) Luerlock Cap
• g) Obturator Tip Protector
• Cannula Tip Protector h)

The 10mm NexPort™ Trocar System is consisted of:

• a) Obturator Shaft
• Cannula Cap b)
• Seal c)
• Cannula Intermediate Plate d)
• Duckbill Valve e)
• f) Cannula Housing
• Stopcock g)
• Face Seal h)
• i) Cannula Sleeve
• Reducer j)
• Adaptor Cap k)
• I) Adaptor Top Body
• m) Adaptor Seal
• n) Adaptor Bottom Body

This is a 510(k) premarket notification for a medical device called the "NexPort™ Trocar System". This document does not describe a study that uses AI or machine learning. Therefore, most of the requested information regarding acceptance criteria and study design for AI/ML performance evaluation is not available in this document.

However, I can provide the available information related to the device's validation and comparison to predicate devices, as well as the non-clinical tests performed.

Current Device: NexPort™ Trocar System

Summary of Device Validation and Performance (based on provided text):

The document primarily focuses on demonstrating substantial equivalence to predicate devices for regulatory clearance, rather than presenting a standalone performance study with specific acceptance criteria that would typically be seen for an AI/ML device. The validation involves non-clinical tests and comparison to legally marketed predicate devices.

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

The document does not explicitly present a table of "acceptance criteria" and "reported device performance" in the way one would for an AI/ML algorithm with metrics like sensitivity, specificity, or AUC. Instead, it details that the device has undergone various non-clinical tests and has been found to conform to applicable medical device safety standards.

The relevant "performance" is implicitly demonstrated through:

• Identical Intended Use/Indications for Use as predicate devices.
• Identical Principles of Operation as predicate devices.
• Identical Application Sites as predicate devices.
• Identical Single Use nature and Operation Mode (Manually) as predicate devices.
• Identical Sterilization Assurance Level (SAL) ($<=10^{-6}$) as predicate devices.
• Biocompatibility: Confirmed to meet the same biocompatibility tests as predicate devices (Cytotoxicity, Sensitization, Intracutaneous reactivity, Acute systemic toxicity, Material-mediated pyrogenicity).
• Mechanical Safety: Confirmed through non-clinical tests.
• Aging/Shelf-Life: Evaluated through accelerated and real-time aging tests.
• In Vivo Study (Porcine Model): Evaluated penetration force, fixation force, and tip integrity, found to conform to applicable medical device safety standards. (No specific numerical results or acceptance criteria are presented in this summary).

Therefore, a table summarizing acceptance criteria and performance would look like this based on the provided text:

The following information is not applicable or not found in the provided text, as this document is for a traditional medical device (trocar system) and not an AI/ML driven device:

2. Sample size used for the test set and the data provenance: Not applicable for an AI/ML test set. The in-vivo study mentioned a "porcine model" but did not specify sample size or provenance.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable.
4. Adjudication method for the test set: Not applicable.
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: Not applicable.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): For the non-clinical tests and the in-vivo study, the "ground truth" would be established by the physical and biological properties being measured and compared against established engineering and medical standards. For instance, biocompatibility is evaluated against ISO 10993 standards.
8. The sample size for the training set: Not applicable.
9. How the ground truth for the training set was established: Not applicable.

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