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The ACMI® MR-6A/MR-6LA Autoclavable Ureteroscopes are intended for the examination/operation of the urinary tract, and using additional accessories, to perform various diagnostic and therapeutic procedures.

Device Description

Like the predicate ACMI® MR-Series Ureteroscopes, the ACMI® MR-6A/MR-6LA Autoclavable Ureteroscopes are semi-rigid endoscopes with two working channels. Flexible accessories such as stone baskets, retrievers, forceps, electrohydraulic lithotripter probes and laser fibers may be used through either working channel. The main component parts of each device include: The metal shaft, Two working channels, An eyepiece, Optical imaging fibers, Light guide connector post, A distal lens, Light carrier fibers. This Special 510(k) proposes the addition of autoclaving processes as a sterilization method, a change in shaft material from stainless steel to MP35N alloy, as well as a change in the manufacturing process to allow the shaft to be hermetically sealed using a micro-TIG and laser welding process in place of epoxy seals.

AI/ML Overview

The provided text describes a Special 510(k) Notification for the ACMI® MR-6A/MR-6LA Autoclavable Ureteroscopes, focusing on modifications to an existing predicate device. This submission primarily addresses changes in sterilization method and material, not performance studies as typically seen with AI/ML devices. Therefore, a direct response to many of your questions regarding acceptance criteria and performance studies in the context of AI/ML evaluation cannot be fully provided by the given text.

However, I can extract information related to the device and the nature of this 510(k) submission, and explain why certain aspects of your request are not applicable based on the provided document.

1. Table of Acceptance Criteria and Reported Device Performance

The document is a 510(k) Summary of Safety and Effectiveness for modifications to an existing device, not a new device requiring extensive performance studies with specific acceptance criteria in the way an AI/ML diagnostic device would. The "acceptance criteria" here are implicitly related to demonstrating substantial equivalence to the predicate device despite the proposed changes.

Acceptance Criteria (Implicit for Substantial Equivalence)	Reported Device Performance (as per submission)
Material Compatibility/Safety: Ensuring the new shaft material (MP35N alloy) is safe and performs comparably to stainless steel.	Substantially equivalent to predicate device. Implies that the safety and performance of the new material for the intended use are acceptable and do not raise new questions of safety or effectiveness.
Sterilization Efficacy: Validating that autoclaving effectively sterilizes the device without compromising its integrity or function.	The proposed addition of autoclaving as a recommended sterilization process is stated as "not substantial changes or modifications, and do not significantly affect the safety or efficacy of the devices." This implies validation of the autoclaving process for the device.
Mechanical Integrity/Durability: Confirming that the new hermetic sealing process (micro-TIG and laser welding) is robust and durable.	The change in manufacturing process to hermetically seal the shaft in place of epoxy seals is similarly categorized as "not significant changes or modifications" to safety or efficacy.
Functional Equivalence: Maintaining the same or essentially the same indications for use, principles of operation, overall length, working channel length, and working channel inner diameters.	"The indications for use, principles of operation, overall length, working channel length and working channel inner diameters of the ACMI® MR-6A/MR-6LA Autoclavable Ureteroscopes remain the same or essentially the same as the predicate device."

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

This information is not provided in the document. The submission focuses on modifications to an existing device (sterilization method and material change), rather than clinical performance testing in a "test set" as would be done for a diagnostic or prognostic AI/ML device. The "data provenance" would likely refer to engineering and biocompatibility testing, but specific details are not outlined here.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

This information is not applicable and not provided in the document. There is no mention of a "ground truth" derived from expert consensus for clinical image interpretation, as this is a physical medical device modification.

4. Adjudication Method for the Test Set

This information is not applicable and not provided in the document for the reasons stated above.

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

This information is not applicable and not provided as this is a physical medical device, not an AI-assisted diagnostic tool.

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

This information is not applicable and not provided as this is a physical medical device.

7. The Type of Ground Truth Used

The "ground truth" in this context would implicitly be engineering specifications, material science data, and sterilization validation results demonstrating that the modified device meets design requirements and remains safe and effective for its intended use, comparable to the predicate device. This is not explicitly detailed in the provided 510(k) summary, as the summary focuses on the conclusion of substantial equivalence rather than the raw data.

8. The Sample Size for the Training Set

This information is not applicable and not provided. "Training set" refers to data used to train AI/ML models, which is not relevant to this type of device modification submission.

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

This information is not applicable and not provided for the same reasons as #8.

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