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510(k) Data Aggregation
(183 days)
The device is intended for intra-operative short term use in the biliary tree to aid in the removal of ductal stones and debris.
The catheter consists of a single lumen stainless steel wire reinforced silicone lube that is end formed to create a rounded leading nose. A silicone balloon is bonded to the cather at the end form. The proximal end of the catheter consists of a female luer connector and a strain relief that are bonded to the silicone shaft. The "DEVICE" is packaged in an ErO breathable tray for protection and then sealed in an ErO breathable pouch. It is EtO sterilized and non-pyrogenic. The "DEVICE" is for Single Use Only By or On the Order of a Physician.
This 510(k) premarket notification describes a medical device, the LMI Biliary Catheter, which is a physical device used in a surgical procedure. Therefore, the questions related to AI/algorithm performance, ground truth, training/test sets, and expert review are not applicable in this context. These questions are typically relevant for AI/ML-based diagnostic or prognostic devices.
However, I can extract information related to the acceptance criteria and how the device meets them based on the provided text.
1. A table of acceptance criteria and the reported device performance
Based on the provided text, the primary "acceptance criterion" for this 510(k) submission is Substantial Equivalence to a legally marketed predicate device. The performance is therefore demonstrated by showing that the new device is "the same" as the predicate device in key aspects.
| Acceptance Criterion | Reported Device Performance |
|---|---|
| Substantial Equivalence to a Predicate Device (ABI Cathlab Silicone Biliary Catheter, K910917) | "The design parameters and intended use of the "DEVICE" are the same as the substantially equivalent catheter. The "DEVICE" utilizes the same materials of construction and packaging as the substantially equivalent catheter." |
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. This is a physical medical device submission, not an AI/ML-based device relying on a test set of data. The "testing" involves demonstrating manufacturing quality, material compatibility, and adherence to design specifications to show substantial equivalence.
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. Ground truth for an AI/ML model is not relevant to this physical device submission.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable.
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. This is not an AI-assisted diagnostic or prognostic device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is a physical medical device.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
Not applicable.
8. The sample size for the training set
Not applicable. This is not an AI/ML-based device.
9. How the ground truth for the training set was established
Not applicable.
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