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510(k) Data Aggregation
(144 days)
The Through the Scope Tracheal Stent System is in the treatment of tracheobronchial strictures caused by malignant neoplasms.
The Through the Scope Tracheal Stent System consists of a flexible delivery system preloaded with a self-expanding implantable metallic stent. The stent is made of Nitinol wire weaved in a tubular mesh shape. This structure may make the stent more flexible, compliant and self-expanding. The stent is fully covered with silicone membrane and a polymer coating. The Parylene N is added on the surface of silicone membrane to restrict tumor in-growth through the wire mesh. A retrieval loop made of PE&PP is threaded through the proximal and distal ends of the stent and is intended to aid in removal during the stent placement procedure. The stent has different dimension with the diameters of 10mm, 12mm, 16mm, 18mm, with the lengths of 20mm, 30mm, 40mm, 50mm, 60mm, 80mm.
The stent is deployed through the endoscopy working channel and under direct vision of endoscopy. The delivery system allows for desheathing to deploy and reposition the stent during the placement procedure. The delivery system consists of two coaxial sheaths and one inner core. The outer sheath serves to constrain the stent until being retracted during the stent deployment. The middle sheath serves to support the delivery system. The round tip acts as a guide when the delivery system enters the body. The front handle is used for deploying the stent. The seal ring, locking ring, and safe lock work to lock the device and prevent the stent from being exposed. The decoration nut connects with the back handle.
The device is supplied sterile, intended for single use only, and is available for prescription use only. Use of this device is restricted to a trained healthcare professional.
The provided text does not describe a study that uses AI or machine learning. It pertains to a medical device (Tracheal Stent System) and its premarket notification (510(k)) to the FDA. The tests conducted are non-clinical performance tests of the physical device, its materials, and its delivery system, ensuring its safety and effectiveness.
Therefore, many of the requested points related to AI/ML model evaluation (such as sample size for test/training sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, and ground truth establishment for training data) are not applicable to this document.
However, I can still extract the acceptance criteria and performance related to the physical device based on the information provided.
Device: Through the Scope Tracheal Stent System
Product Code: JCT
Regulation Name: Tracheal Prosthesis
Since the document does not contain information about an AI/ML model's performance, I will interpret the request in the context of the physical medical device's performance given the available information.
Acceptance Criteria and Reported Device Performance
The document states that "The results of all the performance testing demonstrated that the proposed device met the acceptance criteria and support substantial equivalence to the predicate device Tracheal Stent System (OTW) cleared under K202204."
While the specific numerical acceptance criteria are not detailed in the provided text (e.g., what percentage drop in expansion force is acceptable), the document lists the types of tests conducted and affirms that the device met these criteria, thus demonstrating substantial equivalence.
Here's a table based on the information provided:
| Acceptance Criteria (Category) | Reported Device Performance (as stated in the document) |
|---|---|
| Biocompatibility (conform to ISO 10993-1) | Met requirements for: Vitro Cytotoxicity, Skin Sensitization, Irritation, Acute Systemic Toxicity, Pyrogen, Muscle Implant, Chemical Characterization and Biological Risk Assessment (for stent). Met requirements for: Vitro Cytotoxicity, Skin Sensitization, Irritation (for delivery system). |
| Material/Design Performance (e.g., mechanical properties, stability) | Met requirements for: Dimension Testing, Silicone Thickness Test, Expansion Force Testing, Compression and Recoil Testing, Deployment Force Testing, Deployment Accuracy and Damage Testing, Dislodgement Testing, Migration Force and Removability Testing, Tensile Strength Testing, Repositioning Testing, Corrosion Testing, Fatigue testing, Austenite Finish Temperature Testing. |
| Shelf-Life & Packaging Integrity (ASTM F1980-16, ISO 11607-1:2019, ISO 11607-2:2019) | Met requirements based on two-year accelerated aging test and subsequent two-year aging test, demonstrating stability. Packaging integrity met. |
| Sterilization (ISO 11135:2014+A1:2018, SAL:10-6) | Met requirements for Ethylene Oxide (EO) sterilization validation. |
| MRI Safety & Compatibility (ASTM F 2052-15, F2182-19e2, F2119-07, F2213-17, F2503-13, FDA guidance) | Met requirements for magnetically induced displacement force, radio frequency induced heating, MR image artifacts, and magnetically induced torque. |
| Overall Equivalence to Predicate Device | Demonstrated substantial equivalence to predicate device (K202204) in terms of safety and effectiveness. |
Non-Applicable Information (for AI/ML studies)
As this document describes a traditional medical device (a tracheal stent), the following points are not applicable and no information is provided for them:
- Sample size used for the test set and the data provenance: Not an AI/ML study. Performance tests are typically done on a defined number of physical samples, but this is not a data test set in the AI sense.
- Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not an AI/ML study involving human reader ground truth.
- Adjudication method for the test set: Not an AI/ML study.
- 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 an AI/ML study.
- If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not an AI/ML study.
- The type of ground truth used (expert concensus, pathology, outcomes data, etc): Not an AI/ML study. Measurements and physical properties constitute the "ground truth" for this device.
- The sample size for the training set: Not an AI/ML study. There is no "training set."
- How the ground truth for the training set was established: Not an AI/ML study.
In summary, the provided document describes the non-clinical performance testing of a physical medical device (a tracheal stent) to demonstrate its substantial equivalence to a predicate device, rather than the evaluation of an AI/ML-driven medical device.
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