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To measure pressure in blood vessels including both coronary and peripheral vessels, during diagnostic angiography and/or other any interventional procedures. Blood pressure measurements provide hemodynamic information, such as fractional flow reserve, for the diagnosis and treatment of blood vessel disease.

The proposed OptoWire III is a new version of the OptoWire Deux that includes changes to strengthen the robustness of the product. Additional changes have been made to improve manufacturability. Changes include a reduction in tip length and coil gap, changes in the tube inner and outer configuration, and a minor material change in the PTFE coating.

The Opsens OptoWire III is used in conjunction with the Opsens OptoMonitor and Accessories, the "OptoMonitor System" consisting of an electronic signal processing and display units (OptoMonitor) that process signals received from the OptoWire to display intravascular blood pressure and hemodynamic information, such as fractional flow reserve (FFR) values, and various connection cables.

The OptoWire III consists of the following items:

1. OptoWire assembly (quidewire) including the pressure sensor sub-assembly
2. Fiber Optic Interface Cable (FOIC)
3. Packaging including tray, Torque Device, pouch and box
4. Labelling including labels and printed IFU

The provided text describes a 510(k) premarket notification for the OptoWire III. This document focuses on demonstrating substantial equivalence to a predicate device (OptoWire Deux) rather than proving the device meets acceptance criteria from a clinical study with specific performance metrics like sensitivity, specificity, or accuracy compared to a ground truth.

Therefore, much of the requested information regarding acceptance criteria for a diagnostic study, sample sizes for training/test sets, expert qualifications, and adjudication methods is not present in this regulatory submission. The document emphasizes engineering and bench testing to demonstrate that changes made to the OptoWire III do not raise new questions of safety or effectiveness compared to its predicate.

Here's a breakdown of the available information based on your request:

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

The document does not present a table of specific acceptance criteria (e.g., target sensitivity, specificity) with corresponding reported device performance for a diagnostic task. Instead, it compares the technological characteristics and performance of the proposed device (OptoWire III) to its predicate device (OptoWire Deux) to demonstrate substantial equivalence.

The "Performance Data" section describes various design verification tests, biocompatibility tests, and animal studies to ensure the OptoWire III functions as intended and is safe. Key performance aspects like Pressure Accuracy and Thermal Zero Shift for the pressure sensor are explicitly stated and are identical to the predicate:

Other performance characteristics evaluated in animal studies were assessed qualitatively against the predicate:

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

The document mentions an animal study for performance testing:

• Sample Size for Test Set: 1 female pig (Sus scrofa – Hybrid farm pigs), with one spare animal not used.
• Data Provenance: The study was conducted on an animal model, not human data. The specific country of origin is not stated, but the submission is to the U.S. FDA. The study was conducted prospectively as part of the device verification.

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 to this type of submission. Ground truth for diagnostic accuracy (e.g., FFR values from the device vs. a gold standard) is not explicitly established by independent expert review in this context. The animal study focused on functional performance and comparison to a known safe and effective predicate.

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

Not applicable. The animal study described qualitative assessments of guidewire performance characteristics compared to a control device, not a diagnostic decision requiring adjudication.

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 device is a pressure guidewire, not an AI-powered diagnostic tool for interpretation by human readers. Therefore, no MRMC study or AI assistance improvement analysis was performed or is relevant.

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

Not applicable. The OptoWire III is a physical medical device (guidewire with a sensor) that measures pressure. It is not an algorithm, and thus standalone algorithm performance is not relevant. Its functionality is linked to the OptoMonitor System.

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

For the pressure measurement capability, the "ground truth" is typically the physical principles of pressure measurement and calibration against known pressure standards. The document states "Simultaneous acquisition of 2 pressure values: distal pressure from sensor embedded in OptoWire; aortic pressure from external pressure transducer" for FFR determination, implying a comparison against an external reference for aortic pressure, but not a separate "ground truth" derived from expert consensus or pathology in a diagnostic sense. For the animal study, the ground truth was the observable performance of the device in a living system, judged comparatively against the predicate.

8. The sample size for the training set

Not applicable. This is a medical device approval, not an AI algorithm. Therefore, there is no "training set" in the context of machine learning.

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

Not applicable, as there is no training set for an AI algorithm.

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