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Irritrol™ is intended to cleanse and disinfect root canal systems after endodontic instrumentation.

Irritrol™ is an aqueous solution for use during the irrigation phase of endodontic root canal preparation procedures. This multi-purpose device disinfects the root canal, flushes out any loosened debris, and removes the smear layer produced from root canal instrumentation.

The provided text describes the submission for a medical device (Irritrol™) to the FDA for a 510(k) premarket notification. This type of submission aims to demonstrate substantial equivalence to a legally marketed predicate device, rather than proving novel effectiveness through clinical trials. As such, the information you're requesting regarding acceptance criteria and a study proving a device meets those criteria, particularly in the context of an AI device with specific performance metrics, is not directly applicable to this document.

However, I can extract the information that is present and frame it in a way that aligns with your request where possible, while clearly indicating when specific aspects (like AI performance metrics or human reader studies) are not pertinent to this traditional medical device submission.

Here's an analysis based on the provided text:

Device: Irritrol™ (Root Canal Cleanser)

Purpose of Submission: Demonstrate substantial equivalence to a predicate device (QMix™ 2in1 Endodontic Irrigating Solution) for regulatory clearance, not to prove meeting specific performance criteria for an AI algorithm.

1. Table of Acceptance Criteria and Reported Device Performance

For this type of device (a chemical solution), "acceptance criteria" and "device performance" are typically related to its physical properties, biocompatibility, and intended functions (antimicrobial activity, smear layer removal) compared to its predicate. There isn't a direct "acceptance criteria" in the sense of accuracy, sensitivity, or specificity as one would find for an AI diagnostic tool.

2. Sample Size Used for the Test Set and Data Provenance

This information is not directly provided in the submission summary. The non-clinical tests were "in vitro," meaning conducted in a lab setting, not on human patients. Therefore, terms like "test set" in the context of patient data or data provenance (country of origin, retrospective/prospective) are not applicable.

• Sample Size: Not specified for the in vitro tests (e.g., number of bacterial cultures, number of teeth/root canals tested).
• Data Provenance: Not applicable as these were laboratory tests (in vitro), not human data.

3. Number of Experts Used to Establish Ground Truth and Qualifications

This is not applicable to the submitted document. Ground truth for an AI device involves expert consensus on medical images or clinical outcomes. For this chemical solution, "ground truth" relates to the objective outcomes of the in vitro tests (e.g., bacterial growth measurements, microscopic evaluation of smear layer removal), which are typically determined by laboratory methods and instrumentation, not expert human interpretation in the sense of diagnostic imaging.

4. Adjudication Method

Not applicable. Adjudication methods (e.g., 2+1, 3+1) are used for resolving discrepancies among human experts in establishing ground truth for diagnostic decisions, which is not relevant for this device.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done

No. An MRMC study is designed for AI-assisted diagnostic devices to assess how the AI impacts human reader performance. This device is a chemical solution used in a procedure, not a diagnostic tool read by humans.

6. If a Standalone (Algorithm Only) Performance Study Was Done

Again, this is not applicable. This device is not an algorithm. The performance studies mentioned (biocompatibility, antimicrobial, smear layer removal) assess the chemical properties and effects of the solution itself, not an algorithm.

7. The Type of Ground Truth Used

The "ground truth" for the non-clinical tests would have been established through:

• Biocompatibility: Standardized toxicological endpoints as per ISO 10993 (e.g., cell viability, irritation indices).
• Antimicrobial testing: Direct measurement of bacterial growth/inhibition (e.g., colony counts, zones of inhibition).
• Smear layer removal testing: Likely microscopic evaluation (e.g., SEM) of instrumented root canal walls to assess the presence or absence of smear layer.

This is objective, laboratory-based measurement, not expert consensus on diagnostic images or clinical outcomes.

8. The Sample Size for the Training Set

Not applicable. This device does not involve an AI algorithm, and therefore there is no "training set."

9. How the Ground Truth for the Training Set Was Established

Not applicable, as there is no AI algorithm or training set for this device.

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