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Applied Medical Laparoscopic Linear Cutter has applications in open and/or minimally invasive general, urologic, gynecologic, pediatic and thoracic surgery for resection and or creation of anastomosis. The instruments may also be used for transection of liver parenchyma (hepatic vasculature and biliary structures), pancreas, kidney and spleen. It can be used with staple line or tissue buttressing materials.

The Applied Medical Laparoscopic Linear Cutter (LLC) is a sterile, single-use stapling system that is intended to be used for mechanically transecting, resecting, and sealing tissue during laparoscopic and open surgical procedures. The stapler places six staggered rows of titanium staples, three on either side of the transection line. The shaft can rotate freely in both directions and the jaws articulate to facilitate access to the operative site. The Applied LLC is available in 3 different shaft lengths (20cm, 37cm, 50cm) that can each accommodate 3 different industrystandard reload lengths (60mm, 45mm, 30mm). Each of the reload lengths is available in three industry-standard reload colors and formed staple heights to accommodate various tissue thicknesses: 1.0mm (white reload), 1.5mm (blue reload), and 2.0mm (green reload).

This document describes the FDA's 510(k) clearance for the Applied Medical Laparoscopic Linear Cutter (LLC), asserting its substantial equivalence to a predicate device. As such, the information provided focuses on the performance testing conducted to demonstrate this equivalence rather than a study proving a device meets specific clinical acceptance criteria for an AI/CADe device.

Therefore, many of the requested categories for AI/CADe systems (e.g., number of experts, adjudication methods, MRMC studies, training set details) are not applicable to this type of medical device submission. The device in question is a surgical stapler, not an AI or imaging diagnostic tool.

However, I can extract the information relevant to establishing the substantial equivalence of this device based on the provided text.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

The document states that "All performance testing acceptance criteria were met." It does not provide the specific numerical acceptance criteria for each test or detailed quantitative results, but rather lists the tests performed and their objectives.

2. Sample size used for the test set and the data provenance

• Test Set (Preclinical Studies): Two porcine studies were conducted. The specific number of animals or cases in these studies is not detailed in the provided text.
• Data Provenance: The studies are described as "preclinical testing" which typically implies laboratory animal studies. The country of origin is not specified but implicitly within the context of an FDA submission, the testing would be expected to meet U.S. regulatory standards. These are prospective studies given they are conducted specifically for the regulatory submission.

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

• Not applicable / Not specified. This device is a surgical instrument, and its performance evaluation involves physical and biological testing, not expert interpretation of diagnostic images.

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

• Not applicable. This concept pertains to establishing ground truth for diagnostic image interpretation, which is not relevant to the testing of a surgical stapler.

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 study design is for evaluating AI/CADe systems in diagnostic imaging. The Applied Medical Laparoscopic Linear Cutter is a surgical device.

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

• Not applicable. This device is a manual surgical instrument. No algorithm is involved.

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

• For Bench Tests: Ground truth is established through physical measurements, engineering standards, and biological models (e.g., media, tissue analogues).
• For Preclinical Tests: Ground truth is established through direct observation of in-vivo performance (e.g., hemostasis) and histopathological evaluations of animal tissues post-procedure.
• For Biocompatibility Tests: Ground truth is established by standardized biological assays (e.g., cytotoxicity, sensitization, systemic toxicity) and chemical characterization following specific ISO standards.

8. The sample size for the training set

• Not applicable. This device is not an AI/machine learning system. There is no concept of a "training set."

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

• Not applicable. As above, no training set for an AI/ML model exists for this device.

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