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The Disposable Ureteral Access Sheath is used to establish a conduit during endoscopic urological procedures facilitating the passage of endoscopes and other instruments into the urinary tract.

The product is composed of sheath tube, sheath tube base, dilator and center base of dilator. The sheath tube base contains a backwater interface. The center base of dilator consists of upper cover of dilator base, lower cover of dilator base , fiber image channel interface F, irrigation channel interface I, equipment channel interface E, obturator, two-way water valve, needle free joint. There is no guide wire. The product is sterilized by EO, it should be sterile and only for single use.

This document describes the premarket notification (510(k)) for the Disposable Ureteral Access Sheath by YouCare Technology Co., Ltd. (Wuhan). The submission aims to demonstrate substantial equivalence to a predicate device, K151084 Well Lead Ureteral Access Sheath.

No human-in-the-loop or standalone AI performance studies were conducted or are mentioned in this submission, as this device is a physical medical instrument, not an AI/software device. The "acceptance criteria" discussed here refer to the performance standards and material safety criteria for the physical device, rather than the performance of an AI algorithm.

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

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

The document does not specify exact sample sizes for each non-clinical test conducted (e.g., number of devices tested for bending resistance, friction, etc.). The non-clinical tests were conducted to assess the intrinsic properties of the device, likely a representative sample of manufactured units.

The data provenance is from YouCare Technology Co., Ltd. (Wuhan), China. The tests are non-clinical (laboratory/bench testing) and thus not applicable to retrospective or prospective human patient data.

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

This information is not applicable as the device is a physical medical instrument, and the testing involves non-clinical performance and material safety assessments, not an AI or diagnostic algorithm requiring expert "ground truth" establishment for image interpretation or similar.

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

This information is not applicable for the same reasons as point 3. Testing involves objective measurements against established technical standards (e.g., tensile strength in Newtons, friction coefficients, visual inspection for defects after bending).

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 as the device is a physical medical instrument, not an AI/software device. No MRMC study was conducted or mentioned.

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

This information is not applicable as the device is a physical medical instrument, not an AI/software device. No standalone algorithm performance was assessed.

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

The "ground truth" for this device's performance is based on established engineering standards, material specifications, and regulatory guidelines for mechanical properties, material biocompatibility, sterility, and physical dimensions. For example, testing for "Peak tensile force" has a "ground truth" defined as "not less than 15N." Biocompatibility is assessed against ISO 10993 standards.

8. The sample size for the training set:

This information is not applicable as the device is a physical medical instrument, not an AI/software device. There is no concept of a "training set" in the context of this 510(k) submission.

9. How the ground truth for the training set was established:
This information is not applicable for the same reasons as point 8.

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It is used for percutaneous puncture to the renal pelvis, establishing a percutaneous approach and providing access for endoscopes and surgical instruments.

The product consists of a needle tube, a needle hub, a rear end, equipment channel interface E, fiber image channel interface F, irrigation channel interface I, an obturator, a needle-free joint and a two-way water valve, and that primary package of the product contains a protective sleeve which is only used for product protection. The product is sterilized by ethylene oxide and is single use.

The provided text is a 510(k) summary for an "Introducer Needle" device. It outlines the device's comparison to a predicate device and the performance data submitted to demonstrate substantial equivalence. However, it does not describe a study involving an AI/Machine Learning device or a Multi-Reader Multi-Case (MRMC) comparative effectiveness study.

The performance data section (9. Performance Data) details physical and chemical performance testing, biocompatibility testing, and packaging/shelf-life testing, which are standard for medical devices like introducer needles. These tests are to demonstrate the device meets design requirements and performs as intended, but they do not involve acceptance criteria related to algorithmic performance, expert image interpretation, or human reader improvement with AI assistance.

Therefore, I cannot provide the requested information about acceptance criteria, a study proving device meets acceptance criteria, sample sizes for test/training sets, expert qualifications, adjudication methods, MRMC studies, standalone algorithm performance, or ground truth establishment in the context of an AI/ML device, as this document pertains to a physical medical device.

Here's what I can extract from the provided text regarding the physical device's "acceptance criteria" and "performance data" if interpreted broadly:

Acceptance Criteria and Reported Device Performance (Physical Device)

The document doesn't explicitly list "acceptance criteria" in a table format with specific quantitative thresholds that need to be met for each test for the "Introducer Needle." Instead, it states that "Performance testing was performed in accordance with applicable clauses in ISO 9626-2016 and ISO 7864-2016" and that the testing was "to demonstrate that the Introducer Needle met applicable design requirements." The conclusion then states, "The results of these tests provide reasonable assurance that the Introducer Needle will perform as intended."

However, based on the performance tests listed, we can infer the "acceptance criteria" are implied by meeting the standards of ISO 9626-2016 (presumably for stainless steel needle tubing for the manufacture of medical devices) and ISO 7864-2016 (likely for sterile hypodermic needles for single use).

Here's a representation of the implied acceptance criteria based on the testing performed, and the "reported performance" is that the device met these criteria.

Other Requested Information (Not Applicable to this Document as it's not an AI/ML Device)

The following points are not applicable to the provided document, as it describes a physical medical device (introducer needle) and not an AI/Machine Learning device. Therefore, information regarding AI/ML-specific testing is absent.

• Sample sizes used for the test set and the data provenance: Not applicable to a physical device performance study of this nature. The "test set" here refers to physical units subjected to tests.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for a physical device refers to engineering specifications and performance standards.
• Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
• 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.
• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
• The type of ground truth used (expert concensus, pathology, outcomes data, etc): Not applicable in the context of AI/ML. For this physical device, the ground truth is established by the specified engineering standards (ISO 9626-2016, ISO 7864-2016) and biocompatibility standards (ISO 10993 series).
• The sample size for the training set: Not applicable (no ML training).
• How the ground truth for the training set was established: Not applicable (no ML training).

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