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The HANAROSTENT LowAxTM Colon/Rectum (NNN) is indicated for the palliative treatment of colorectal strictures produced by malignant neoplasms and to relieve large bowel obstruction prior to colectomy in palignant structures.

The HANAROSTENT LowAxTM Duodenum/Pylorus (NNN) is indicated for the palliative treatment of pyloric or duodenal obstructions caused by malignant neoplasms.

This self-expanding tubular prosthesis designed to maintain patency of colorectal or duodenal obstructions caused by malignant tumors. It consists of a self-expandable metal stent and a delivery system. The self-expandable metal stent is made of nickel titanium alloy (Nitinol) wire and the delivery system is made of polymeric materials. The stent is loaded into the distal part of the delivery system. The HANAROSTENT® LowAx™ Colon/Rectum (NNN) and HANAROSTENT® LowAx™ Duodenum/Pylorus (NNN) are intended for single use only.

This document (a 510(k) summary) describes a submission for a medical device re-clearance rather than a de novo submission. The primary purpose of this submission is to demonstrate substantial equivalence to a previously cleared predicate device (K180180), not to prove de novo clinical efficacy or safety of a fundamentally new device through extensive clinical trials.

Therefore, the typical components of acceptance criteria and the detailed study proving the device meets those criteria (especially regarding human-in-the-loop AI performance, ground truth establishment for large datasets, etc.) are not present in this type of regulatory document. The focus shifts to demonstrating that the new version of the device is essentially the same as the previously cleared version, with any minor changes like MR compatibility testing still ensuring safety and effectiveness.

Here's a breakdown based on the provided text, explaining why certain requested information is absent or not applicable:

Key Takeaway: The device in question (HANAROSTENT LowAx™ Colon/Rectum and Duodenum/Pylorus) is a self-expanding metal stent. Its performance is assessed through bench testing (physical and material properties) and by demonstrating identical characteristics to a previously cleared device, not through studies involving AI, human reader improvement, or large-scale clinical outcomes data in the way a diagnostic AI device would be.

Acceptance Criteria and Device Performance (Based on "Substantial Equivalence" and "Performance Testing" sections):

This submission leverages the substantial equivalence pathway. The primary "acceptance criteria" are demonstrating that the subject device is identical or nearly identical to its predicate device (K180180) in critical aspects, and that any small change (MR compatibility) does not compromise safety or effectiveness.

Here's a table reflecting what is implicitly stated as "met" by virtue of substantial equivalence and new testing:

Regarding the Absence of Specific Study Details (as related to AI/Diagnostic Devices):

This submission is for a medical device (physical stent), not a diagnostic algorithm or AI software for image analysis. Therefore, many of the requested details related to AI study design are not applicable or not part of this type of submission.

1. Sample sizes used for the test set and data provenance:

   • N/A (for AI/diagnostic data). This device is a physical stent. Performance testing involves bench tests (e.g., force measurements, corrosion) on device samples, not patient data sets or images. The "test set" in this context refers to the physical devices or components tested. There are no "patients" or "data" in the sense of a diagnostic study.

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

   • N/A. Ground truth for a physical stent is established by engineering specifications, material science, and established test methods (e.g., ASTM standards for mechanical properties). No human experts are adjudicating "ground truth" on images or clinical outcomes for this device in this submission.

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

   • N/A. Applies to human reading/AI performance studies, not physical device testing.

4. 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:

   • N/A. This device does not involve human readers, AI assistance, or image interpretation.

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

   • N/A. This is not an algorithm or AI device. Its "standalone performance" refers to its physical characteristics and functionality as a stand-alone stent and delivery system, assessed via bench tests.

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

   • For the physical properties: Engineering specifications, established test methods (e.g., ISO, ASTM standards), and material science principles.
   • For comparison to the predicate: The previously cleared predicate device (K180180) itself serves as the "ground truth" for substantial equivalence regarding its established safety and effectiveness.

7. The sample size for the training set:

   • N/A. This is not an AI/machine learning device that requires a "training set."

8. How the ground truth for the training set was established:

   • N/A. No training set is involved.

In summary, this 510(k) submission leverages the "Substantial Equivalence" pathway for a physical medical device. The "study that proves the device meets the acceptance criteria" primarily consists of:

• A detailed comparison demonstrating identical technological characteristics to a previously cleared predicate device (K180180).
• Reliance on the performance testing data submitted for that predicate device.
• New bench testing specifically for MR compatibility to support new labeling.

The document explicitly states: "The subject device in this Traditional 510(k) submission is the exact same, identical device as predicate device K180180." This claim, supported by the comparison of characteristics and leveraging prior testing, is the core of demonstrating it meets the implicit "acceptance criteria" for clearance via substantial equivalence.

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