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The 40L High Flow Insufflator F108 with low flow mode is a device intended to facilitate the use of the laparosoope by filling the peritoneal cavity with gas to distend it. The low flow application of this device is indicated for pediatric use.

The 40 L High Flow Insufflator F108 is a microprocessor controlled device designed to insufflate medical CO2 gas into peritoneal cavities during diagnostic and therapeutic laparoscopic procedures. The 40 L High Flow Insufflator F108 consists of the following main components: a housing, power supply, pressure reducers, a venting system, a fluid sensor, a gas heater, various setting kevs and display elements. A continuous redundant pressure measurement controls the conformity of the actual pressure in the abdomen with the pre-set nominal pressure. The device is to be used with a specially designed heating tube and with an optional remote control.

The 40 L High Flow Insufflator F108 is a medical device and therefore does not have acceptance criteria or performance metrics directly comparable to AI/ML software. The provided text describes its regulatory submission (510(k)) and substantial equivalence to a predicate device, rather than a study with acceptance criteria for device performance in the way an AI model would be evaluated.

Here's a breakdown of the specific points you requested, based on the provided document:

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

This information is not applicable in the context of this medical device submission. The 510(k) process focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than establishing new acceptance criteria for novel performance metrics with a quantitative study design.

However, the document states:

• Acceptance Criteria (Implicit): Substantial equivalence to the predicate device, Surgiflator 40 (K001533), in intended use, design, and technological characteristics. The main difference, a new software logarithm for accurate flow measurements (0.1 V/min to 1 V/min) and a Low Flow Mode, was deemed not to raise new questions of safety and effectiveness.
• Reported Device Performance: "Bench tests demonstrate the safety and effectiveness of the 40 L High Flow Insufflator F108 when used in the Low Flow Mode to insufflate small abdominal cavities." No specific quantitative performance metrics are provided in the summary.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

Not applicable. No test set or data provenance is mentioned as this is a medical device for which bench testing was performed, not a data-driven AI/ML model.

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. No experts are mentioned in the context of establishing ground truth for a test set. Bench tests were performed to demonstrate safety and effectiveness.

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

Not applicable. No adjudication method is mentioned as no test set requiring human adjudication was utilized.

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. No MRMC comparative effectiveness study was performed or mentioned. This is a hardware medical device, not an AI-assisted diagnostic tool.

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

Not applicable. This device is a standalone hardware product. The mention of "software logarithm" refers to an internal control system for accurate flow measurements, not an AI algorithm for diagnostic interpretation or decision-making. Its performance is its standalone performance without a human in the loop for its primary function of insufflation.

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

Not applicable in the sense of a data-driven model. The "ground truth" for this device's safety and effectiveness was established through bench tests and a comparison to the predicate device's known performance record and literature review on CO2 insufflators.

8. The sample size for the training set

Not applicable. No training set is mentioned. This device does not use machine learning in the conventional sense that would require a training set.

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

Not applicable. No training set was used.

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