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The Bendit2.7 Steerable Microcatheter is intended for general intravascular use in the peripheral vasculature. The microcatheter can be used for the delivery of diagnostic, embolic materials into the vasculature.

The Bendit2.7 is not intended to be used in intracranial or coronary vessels.

The Bendit2.7™ is a steerable microcatheter with a steerable distal tip. The tip's deflection is controlled using the Steering Slider on the proximal Steering Handle. The tip can be rotated bi-directionally while deflected by turning the Torque Knob on the Steering Handle.

The total working length of the Bendit2.7™ is 130 cm. It is comprised of two Nitinol hypo tubes that are welded together at their distal ends, with proprietary laser-cut patterns along the 28-centimeter distal section. The laser cuts give the Bendit2.7™ its flexibility while maintaining the Nitinol torsional rigidity for a high torque response. The distal 12 mm section is steerable and includes a radiopaque atraumatic tip. The distal 80 cm of the shaft is covered with a hydrophilic coating.

Sliding the Steering Slider forward moves the hypo tubes so that the distal tip deflects. When the Steering Slider is released, the tip shape is locked. The Bendit2.7™ lumen can accommodate compatible guidewires (≤0.018"). A standard Luer lock port for attachment of accessories is located at the proximal end of the Steering Handle.

This document describes the Bendit2.7 Steerable Microcatheter and its substantial equivalence to a previously cleared device (K190126) following design changes.

The focus here is not on an AI/ML device, but rather a medical device with mechanical and material changes. Therefore, much of the requested information regarding AI/ML studies (such as MRMC studies, ground truth establishment for training, expert qualifications for ground truth in test sets, and separate training/test sets) is not applicable to this submission.

Here's the breakdown based on the provided text, addressing only the applicable points:

1. Table of Acceptance Criteria and Reported Device Performance

The submission states that "All test results met the pre-defined test acceptance criteria." However, the specific acceptance criteria values are not explicitly detailed in the provided document, nor are the quantitative results for each test. Instead, the document lists the types of tests performed to verify the design changes:

2. Sample size used for the test set and the data provenance

The document does not specify the sample sizes used for each of the listed tests. The data provenance is derived from in vitro bench testing performed by the manufacturer (Bend It Technologies, Ltd, Israel). It is not clinical data, nor does it involve human subjects or retrospective/prospective studies.

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

This question is not applicable as the evaluation involved in vitro bench testing of a physical medical device, not an AI/ML system requiring expert-derived ground truth.

4. Adjudication method for the test set

This question is not applicable as the evaluation involved in vitro bench testing of a physical medical device, not an AI/ML system requiring adjudication of interpretations.

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 question is not applicable as the device is a physical microcatheter, not an AI/ML diagnostic tool. No MRMC study was performed.

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

This question is not applicable as the device is a physical microcatheter, not an AI/ML algorithm.

7. The type of ground truth used

The "ground truth" for this device's performance is established by engineering specifications and recognized industry standards for medical devices (e.g., ISO 10993-17-2020 for biocompatibility, and internal specifications for physical properties like tensile strength, kink resistance, etc.). The tests verify that the device meets these pre-defined engineering and safety specifications.

8. The sample size for the training set

This question is not applicable as this is not an AI/ML device.

9. How the ground truth for the training set was established

This question is not applicable as this is not an AI/ML device.

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