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The SigniaTM Loading Units with Tri-StapleTM 2.0 cartridges have applications in abdominal, gynecologic, pediatric and thoracie surgery for resection and creation of anastomosis. They may be used for transection and resection of liver substance, hepatic vasculature and biliary structures and transection and resection of pancreas.

The SigniaTM Loading Units and Tri-StapleTM 2.0 Cartridges place staggered rows of titanium staples and simultaneously divides the tissue so that three staggered rows of staples are placed on either side of the cut line. The size of the staples is determined by the selection of the following single use Tri-StapleTM 2.0 cartridges:

Tri-Staple TM 2.0 cartridge, vascular/medium:

• Tan- three height progressive rows of 2.0 mm, 2.5 mm, 3.0 mm titanium staples on o either side of the cut line.
  Tri-StapleTM 2.0 cartridge, medium/thick:

• · Purple-three height progressive rows of 3.0 mm, 3.5 mm and 4.0 mm titanium staples on either side of the cut line.
  The Tri-StableTM 2.0 Cartridge is available in 45 mm and 60 mm lengths. The SigniaTM Loading Unit is available in articulating 45 mm and 60 mm lengths. Tri-StapleTM 2.0 Cartridges are able to be loaded into the SigniaTM Loading Unit by the User. SigniaTM Loading Units may be used up to twelve times in the same procedure. SigniaTM Loading Units with Tri-Staple TM 2.0 Cartridges, similar to the predicate devices, are compatible with Covidien's Endo GIA TM Ultra Universal manual stapler handles and iDriveTM Ultra powered stapler handle with associated Endo GIATM Adapter.

The provided text describes a medical device, the "Signia Loading Units with Tri-Staple™ 2.0 Cartridges," and its 510(k) submission to the FDA. However, the document does not contain information related to software, algorithms, AI, or diagnostic studies that would typically have the specific acceptance criteria and study design elements you've requested.

This document is a 510(k) summary for a surgical stapler system, which is a physical medical device. The "tests" performed are engineering and biological validations of the stapler's mechanical function and safety, not a study of an AI or algorithm's diagnostic performance.

Therefore, I cannot populate the table or answer most of your detailed questions about acceptance criteria, AI performance, ground truth, or expert involvement as they are not applicable to the information provided in this document.

Here's what can be extracted, focusing on the device performance and the nature of the non-AI testing described:

1. Table of Acceptance Criteria and Reported Device Performance

As this is a mechanical surgical device, the "acceptance criteria" are related to mechanical and biological function rather than diagnostic accuracy. The document states that "design differences were found to not affect safety or performance through applicable design verification activities that showed continued conformance to applicable technical design specifications and performance requirements, applicable medical device performance standards, and other nonclinical testing." Specific numerical acceptance targets are not provided in this summary.

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: Not specified for individual tests. The document mentions "bench tests using simulated tissue medium" and "in vivo and ex vivo tests using porcine and canine animal models."
• Data Provenance: Not specified, but animal models (porcine and canine) were used for some tests. The studies were likely conducted internally or by contract research organizations. The nature suggests they are prospective experiments/tests as part of device development and validation.

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)

• Not Applicable. This is a hardware device validation, not a diagnostic study requiring expert ground truth for interpretation of medical images or data. The "ground truth" here would be the successful mechanical function of the stapler and the physical/physiological outcomes (e.g., successful hemostasis).

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• Not Applicable. Adjudication methods are typically used in diagnostic studies for resolving discrepancies in expert interpretations. This device undergoes engineering and biological performance testing.

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. This is a hardware device, not an AI or diagnostic software. Therefore, no MRMC study or AI assistance improvement metrics are relevant or provided.

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

• Not Applicable. No algorithms or AI are described.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

• For the bench tests: The "ground truth" would be objective engineering measurements and pre-defined acceptance ranges for mechanical parameters (e.g., staple formation geometry, force measurements).
• For the in vivo/ex vivo tests: The "ground truth" would be direct observation of physiological outcomes (e.g., absence of acute air leak, successful hemostasis, measurement of burst pressure, visual assessment of tissue trauma). This is direct observation of device effect on biological tissue.
• For biocompatibility: Conformance to ISO Standard 10993-1.

8. The sample size for the training set

• Not Applicable. This is not an AI/machine learning device. There is no "training set" in the context of the information provided. The development and testing of this device would involve engineering design iterations and subsequent verification/validation tests.

9. How the ground truth for the training set was established

• Not Applicable. No training set for an algorithm is described.

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