Search Results

This product is intended to be used in combination with an endoscope to assist endoscopic insertion into the body. Never use this product for any other purpose. This product is intended for use in medical facilities by medical professionals who are properly trained in using it as well as in endoscopic procedures and endoscopic treatments.

Not Found

The provided text is an FDA 510(k) clearance letter and its associated summary for a medical device called "Over-tube (TR-1108A)". This document describes the device, its intended use, and its substantial equivalence to a predicate device.

Crucially, this document is for an "Over-tube" which is a physical accessory used with an endoscope, not an AI/software-based medical device. Therefore, the concepts of acceptance criteria, study design (like MRMC, human-in-the-loop, standalone performance), data provenance, expert ground truth establishment for AI models, and training/test sets as commonly understood for AI/ML device clearances do not apply to this specific product.

The document discusses performance testing of the physical device to demonstrate that changes in size (outer diameter, maximum outer diameter) compared to the predicate device do not affect its safety or efficacy.

Here's how the information provided relates to the closest equivalent concepts for a physical device:

Acceptance Criteria and Reported Device Performance

The document states that "the subject device met performance specifications in the following additional testing." This implies that the 'acceptance criteria' were met if the device passed these tests. The reported performance is simply that it "passed all test objectives."

Table of "Acceptance Criteria" (Implied) and "Reported Device Performance" for an Over-tube (TR-1108A):

Note: For a physical device, these are typically engineering specifications and not statistical performance metrics like sensitivity, specificity, AUC as seen in AI/ML devices.

Study Details (as applicable to a physical device)

1. Sample Size Used for the Test Set and Data Provenance:

   • Sample Size: Not explicitly stated as a 'sample size' of cases/patients in the context of a typical AI study. For a physical device, this refers to the number of units tested or the number of movements/stresses performed during testing. This information is not detailed in the provided summary.
   • Data Provenance: Not applicable in the AI/ML sense. The testing is likely done in a lab or benchtop setting by the manufacturer, not with patient data from specific countries or in retrospective/prospective studies.

2. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of those Experts:

   • Not Applicable. Ground truth, in the context of an AI/ML device, refers to a definitive diagnosis or annotation of medical images/data. For a physical device like an over-tube, performance is assessed against engineering specifications and functional requirements, not expert-labeled "ground truth."

3. Adjudication Method for the Test Set:

   • Not Applicable. Adjudication is typically for expert disagreements on ground truth labels in AI studies. For a physical device, test results are typically objective measurements against specifications.

4. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

   • No. MRMC studies are specific to evaluating how AI impacts human reader performance, primarily in image interpretation. This is a physical device, so such a study would not be performed.

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

   • Not Applicable. This is a physical device, not an algorithm.

6. The Type of Ground Truth Used:

   • Engineering Specifications / Functional Requirements. The "ground truth" for a physical device's performance is whether it meets its designed specifications (e.g., minimum flexibility, maximum diameter, insertion force within limits). This is determined by direct measurement and testing, not by expert consensus or pathology on patient data.

7. The Sample Size for the Training Set:

   • Not Applicable. "Training set" refers to data used to train an AI model. This is a physical device.

8. How the Ground Truth for the Training Set was Established:

   • Not Applicable. As there's no training set for a physical device.

In summary, the provided document is for a conventional hardware medical device, not an AI/ML software device. Therefore, many of the questions related to AI/ML study design and ground truth establishment are not applicable. The manufacturer demonstrated "substantial equivalence" by showing that the physical changes (size) did not negatively impact the device's ability to meet its performance specifications.

Ask a specific question about this device