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The NanoCross 0.014" OTW PTA Dilatation Catheter is intended to dilate stenoses in the iliac, femoral, ilio-femoral, popliteal, infra-popliteal, and renal arteries, and for the treatment of obstructive lesions of native or synthetic arteriovenous dialysis fistulae.

The NanoCross .014" OTW PTA Dilatation Catheter is an over the wire (OTW) 0.014" coaxial lumen catheter with a distally mounted semi-compliant inflatable balloon and an atraumatic, tapered tip. The distal portion of the catheter shaft and the balloon has a hydrophilic coating. The manifold includes a lumen marked "THRU". This is the central lumen of the catheter that terminates at the distal tip. This lumen is used to pass the catheter over a guidewire with a maximum outer diameter of 0.014". The lumen marked "BALLOON" is used to inflate and deflate the dilatation balloon with a solution of contrast medium and saline. The balloon has two radiopaque markers for positioning the balloon relative to the stenosis. The radiopaque marker bands indicate the dilating or working section of the balloon. The 210mm balloon contains two additional radiopaque marker bands that denote the middle of the balloon body.

The provided 510(k) summary for the "NanoCross™ .014" OTW PTA Dilatation Catheter" indicates that this is a medical device clearance application, not an AI/ML-driven diagnostic device. Therefore, the information requested regarding acceptance criteria, performance metrics like sensitivity/specificity, ground truth establishment, expert adjudication, MRMC studies, and sample sizes for training/test sets is not applicable to this submission type.

Instead, this submission seeks substantial equivalence to a predicate device (NanoCrossTM .014" OTW PTA Dilatation Catheter (K082854)) based on device characteristics and bench testing.

Here's an analysis based on the provided document:

1. A table of acceptance criteria and the reported device performance

The document does not specify quantitative acceptance criteria in terms of performance metrics like sensitivity or specificity, as it's not a diagnostic AI/ML device. Instead, the acceptance criteria are implicitly met by demonstrating substantial equivalence to a legally marketed predicate device (K082854).

The reported device performance is described as conformance to requirements for its intended use through "bench testing."

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 device is not an AI/ML diagnostic and therefore does not have a "test set" of patient data in the typical sense for performance evaluation. The "testing" refers to bench testing of the physical catheter.

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. There is no concept of "ground truth" established by experts for this type of medical device submission.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

Not applicable. There is no expert adjudication for a test set in this context.

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 device, so MRMC studies are irrelevant.

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

Not applicable. This is a physical medical device, not an algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

Not applicable. "Ground truth" as a concept for performance evaluation of diagnostic or AI/ML systems is not relevant here. The evaluation relies on engineering principles and similarity to a predicate device.

8. The sample size for the training set

Not applicable. This is not an AI/ML device, so there is no training set.

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

Not applicable. As there is no training set for an AI/ML algorithm, this question is not relevant.

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