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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, or therapeutic 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 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.

The provided text describes the Bendit2.7™ Steerable Microcatheter and its FDA 510(k) clearance. However, it does not contain information about acceptance criteria in terms of performance metrics (sensitivity, specificity, AUC, etc.) from a clinical study, nor does it detail a study that proves the device meets such criteria in the context of an AI/ML device.

The document focuses on the substantial equivalence of a physical medical device (a microcatheter) to a predicate device, primarily through bench testing and animal studies to demonstrate its functional and safety performance, rather than an AI/ML component's diagnostic or predictive accuracy.

Therefore, many of the requested categories in your prompt (e.g., sample size for test set, data provenance, number of experts for ground truth, MRMC study, standalone performance, training set size, etc.) are not applicable to the data provided in this document, as it pertains to a physical medical device.

I can, however, extract related information from the document as best as possible, focusing on the available "acceptance criteria" through the lens of device performance testing.

1. Table of Acceptance Criteria and Reported Device Performance (based on the provided document):

Study that proves the device meets the acceptance criteria:

The primary studies conducted to demonstrate that the Bendit2.7™ Steerable Microcatheter meets its acceptance criteria for substantial equivalence are:

• In Vitro Bench Testing: This involved testing finished, sterilized, unaged, and accelerated-aged samples of the device against predefined design inputs.
• Animal Testing: This involved evaluating the device's performance in reaching target vessels and delivering materials.
• Sterilization Validation: This involved validating the ethylene oxide sterilization process.
• Biocompatibility Testing: This involved testing for various biological responses to patient-contacting materials.
• Package Testing: This involved testing package integrity after aging and simulated transportation.

Details requested that are NOT APPLICABLE to this document (as it concerns a physical medical device, not an AI/ML diagnostic/predictive system):

• 2. Sample size used for the test set and the data provenance: Not applicable. The "test set" here refers to physical devices and animal models, not a dataset for an algorithm.
• 3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable in the context of diagnostic "ground truth." For the animal studies, four interventional radiologists evaluated performance, which could be considered expert evaluation, but not for establishing a "ground truth" for diagnostic labels.
• 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/ML device.
• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
• 7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): For the animal studies, the "ground truth" was the observed performance of the device by interventional radiologists against the predicate devices in terms of handling, tracking, and radiopacity/tip visualization. For bench tests, "ground truth" was meeting design specifications.
• 8. The sample size for the training set: Not applicable. This is not an AI/ML device.
• 9. How the ground truth for the training set was established: Not applicable.

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