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The SelectFlex 072 Neurovascular Access System is indicated for the introduction of interventional devices into the peripheral and neurovasculature.

The SelectFlex 072 Neurovascular Access System is a sterile, single-use intravascular catheter used to facilitate access to target vasculature during interventional procedures. The system is composed of a the SelectFlex 072 Catheter, a 3cc Inflation Syringe, a 7Fr Peel Away Introducer, and Hub Extension Line. The 072 SelectFlex Catheter has a usable length of 105cm. The SelectFlex 072 Catheter has variable stiffness along its length and has a dual mode stiffness mechanism on the distal portion of the catheter that is activated by the user allowing the device to transition between tracking and support modes. The distal end of the SelectFlex 072 Catheter has a hydrophilic coating.

The provided document is a 510(k) summary for the SelectFlex 072 Neurovascular Access System, asserting its substantial equivalence to a predicate device (SelectFlex 072 Neurovascular Access System K181000). The summary focuses on comparing the new device to the predicate and presenting nonclinical bench test data. It does not detail a study proving the device meets acceptance criteria for an AI/ML-based medical device. The documentation pertains to a traditional medical device (a catheter system), not an AI-enabled device.

Therefore, the following information cannot be extracted from the provided text for an AI/ML-based device:

• A table of acceptance criteria and the reported device performance: The document lists bench tests and states "PASS" for all, meaning all samples met "pre-determined acceptance criteria," but it does not specify the numerical or qualitative acceptance criteria for each test in a detailed table that would be typical for an AI/ML performance summary (e.g., sensitivity, specificity, AUC thresholds). The acceptance criteria for the new device are implicitly that they perform equivalently to the predicate device in the listed bench tests.
• Sample size used for the test set and the data provenance: No information on test set sample size or data provenance in the context of an AI/ML study is provided. The bench tests would have their own sample sizes, but these are not for an AI model.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable as this is not an AI/ML study requiring expert-derived ground truth.
• Adjudication method for the test set: Not applicable.
• 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.
• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
• The type of ground truth used: Not applicable.
• The sample size for the training set: Not applicable.
• How the ground truth for the training set was established: Not applicable.

However, based on the document, I can provide information relevant to a traditional medical device's nonclinical performance evaluation:

1. Table of Acceptance Criteria and Reported Device Performance (Nonclinical Bench Testing):

The document states that all tests resulted in "PASS," meaning all samples met "pre-determined acceptance criteria." The specific numerical acceptance criteria themselves are not listed in this summary, only the outcome.

2. Sample sized used for the test set and the data provenance:

The document mentions "All samples met the pre-determined acceptance criteria" for various bench tests, but does not specify the sample size (n) for each test set used in the nonclinical bench testing. Data provenance is not applicable in the context of clinical data for an AI/ML device, as these are bench tests.

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

For the "Simulated Use/Usability" test, the document states it "includes a usability assessment with multiple physicians." The specific number and qualifications of these physicians are not provided. This is not establishing "ground truth" in an AI/ML context, but rather assessing usability.

4. Adjudication method for the test set:

Not applicable in the context of bench testing for a traditional medical device.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

No, this type of study was not conducted as this is a non-AI/ML device.

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

Not applicable, as this is not an AI/ML device.

7. The type of ground truth used:

Not applicable, as this is not an AI/ML device. For the bench tests, the "ground truth" is defined by established international and national standards (e.g., ISO, ASTM, USP) and the device's own specifications.

8. The sample size for the training set:

Not applicable, as this is not an AI/ML device that requires a training set.

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

Not applicable, as this is not an AI/ML device.

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The SelectFlex 072 Neurovascular Access System is indicated for the introduction of interventional devices into the peripheral and neurovasculature.

The SelectFlex 072 Neurovascular Access System is a sterile, single-use intravascular catheter used to facilitate access target vasculature during interventional procedures. The system is composed of a the SelectFlex 072 Catheter, a 3cc Inflation Syringe, and a 7Fr Peel Away Introducer. The 072 SelectFlex Catheter has a usable length of 105cm. The SelectFlex 072 Catheter has variable stiffness along its length and has a dual mode stiffness mechanism on the distal portion of the catheter that is activated by the user allowing the device to transition between tracking and support modes. The distal end of the SelectFlex 072 Catheter has a hydrophilic coating.

This document, a 510(k) summary for the SelectFlex 072 Neurovascular Access System, describes various performance tests conducted to demonstrate the device's suitability for its intended use, rather than a clinical study evaluating an AI algorithm's performance.

Therefore, many of the requested fields regarding AI algorithm evaluation are not applicable (N/A) in this context. The document focuses on demonstrating substantial equivalence to a predicate device through physical and biological performance testing.

Here's the breakdown based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state numerical acceptance criteria for each test in a table, but rather indicates that all samples "met the pre-determined acceptance criteria" or "passed" the tests. The acceptance criteria are implicitly defined by the referenced ISO/ASTM standards and internal product specifications.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document does not specify the exact sample sizes used for each individual performance test (e.g., how many catheters were tested for flex fatigue). It generally states "All samples met the pre-determined acceptance criteria," implying that a sufficient number of samples were tested per the relevant standards.

• Sample Size for Test Set: Not explicitly stated for each test, but implied to be adequate for standard compliance.
• Data Provenance: Not specified. This typically refers to data like patient images or clinical records, which are not relevant to these engineering and biocompatibility tests. The tests themselves are laboratory-based.

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

• Number of Experts: For the "Simulated Use/Usability" test, it states "a usability assessment with multiple physicians." The exact number or qualifications are not provided beyond "physicians."
• Qualifications of Experts: "Multiple physicians" for usability assessment. For other tests, "ground truth" is established by adherence to recognized international standards (e.g., ISO, ASTM, USP) and internal product specifications, carried out by qualified testing personnel, but not "experts" in the sense of clinical specialists interpreting results.

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

Not applicable. This is not a clinical study involving interpretation of data by multiple readers. The assessment of performance tests is based on objective measurements against pre-defined criteria in laboratory settings.

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 document pertains to the performance and safety testing of a neurovascular access system, not an AI or imaging diagnostic device. No AI component is mentioned.

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

Not applicable. This is not an AI algorithm.

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

For the performance and biocompatibility tests, the "ground truth" is established by:

• Compliance with international standards: ISO, ASTM, AAMI, USP.
• Adherence to internal product specifications: Dimensional verification.
• Comparison to predicate/reference devices: For tip deflection, flow rate, and device removal forces.
• Usability assessment: By "multiple physicians" in a simulated environment.

No pathology or outcomes data are referenced as this is a pre-market notification for a device and not a clinical trial.

8. The sample size for the training set

Not applicable. This is not an AI algorithm, so there is no training set.

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

Not applicable. There is no AI training set.

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