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To measure pressure in blood vessels including both coronary and peripheral vessels, during diagnostic angiography and/ or any interventional procedures.

Blood pressure measurements provide hemodynamic information, such as fractional flow reserve, for the diagnosis and treatment of blood vessel desease.

The proposed OptoMonitor 3 and its components are considered accessories to Opsens OptoWire™ pressure guidewires and are intended for use with legally marketed pressure guidewires.

The proposed OptoMonitor 3 includes an Optical Unit (OU), a Display Unit (DU), a Handle Unit (HU) and accessories (cables, power supply, etc).

The device is a non-sterile, non-patient contact device.

The provided text describes the 510(k) submission for the OptoMonitor 3 device, which is a pressure monitor used with OptoWire™ pressure guidewires to measure pressure in blood vessels. The submission focuses on demonstrating substantial equivalence to a previously cleared predicate device (OptoMonitor 3 cleared via K193620).

Crucially, this document does not describe a study involving an AI/Machine Learning algorithm for diagnostic purposes, nor does it present acceptance criteria and performance data in the context of an AI-based system. Instead, it concerns a medical device that measures physiological pressure. The "performance data" section specifically refers to electrical safety, electromagnetic compatibility (EMC), and wireless coexistence testing, not diagnostic accuracy or efficacy.

Therefore, many of the requested points related to AI/ML (e.g., ground truth, expert consensus, MRMC study, training data) are not applicable to the content of this document.

However, I can extract the relevant information regarding acceptance criteria and performance testing for this specific device.

Device Type: Medical Device - Catheter Tip Pressure Transducer (OptoMonitor 3)
Intended Use: To measure pressure in blood vessels (coronary and peripheral) during diagnostic angiography and/or interventional procedures, providing hemodynamic information such as fractional flow reserve for diagnosis and treatment of blood vessel disease.

Here's an attempt to answer the prompt based only on the provided text, recognizing that it's for a traditional medical device, not an AI product:

Acceptance Criteria and Device Performance Study for OptoMonitor 3

The OptoMonitor 3 is a pressure monitoring device, and the provided document is a 510(k) submission seeking substantial equivalence to a predicate device. The "study" described here is primarily a series of verification and validation (V&V) tests to confirm that changes in the new device version do not introduce new questions of safety and effectiveness, and that its performance remains comparable to the predicate. It is not a clinical study assessing diagnostic accuracy in the way an AI algorithm would be evaluated.

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't present a formal "acceptance criteria" table with numerical targets in the same format as for an AI/ML diagnostic. Instead, it focuses on demonstrating that the performance characteristics of the new OptoMonitor 3 are "essentially the same" or "equivalent" to the predicate OptoMonitor 3 (K193620). The changes are primarily related to communication methods (Bluetooth) and display unit options, along with minor software updates. The "performance data" section details compliance with various electrical safety, EMC, and wireless coexistence standards.

The table below summarizes the key performance characteristics compared to the predicate, implying that the acceptance criterion is "same" or "equivalent performance" to the legally marketed and cleared predicate device.

Performance Data provided to support substantial equivalence (Verification & Validation (V&V))

• Electrical safety and electromagnetic compatibility (EMC) testing:
  • Compliance with IEC 60601-1:2012 (Consolidated text - edition 3.1)
  • Compliance with IEC60601-1-2:2007 (third edition)
  • Compliance with IEC60601-1-2:2014 (fourth edition)
• Wireless coexistence testing:
  • Successfully tested per ANSI/IEEE C63.27:2017 in accordance with the FDA guidance (2013) Radio Frequency Wireless Technology in Medical Devices.
• Risk Management Process: Evaluated changes, and "no new questions of safety and effectiveness were identified."
• Verification and Validation activities: "No new questions of safety and effectiveness were identified during the execution of Verification and Validation activities."
• Software Validation: Changes are validated in accordance with Opsens QMS, including code review, unit testing, system testing, and regression testing.

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

• Sample Size: Not applicable in the context of clinical data for diagnostic accuracy. The testing described is primarily laboratory-based V&V testing (e.g., electrical safety, EMC, wireless coexistence), not a patient-based test set size.
• Data Provenance: Not applicable. The "study" is a technical V&V assessment of the device hardware and software, not a collection of patient data.
• Retrospective/Prospective: Not applicable.

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

• Not applicable. This is not a study requiring expert-established ground truth for diagnostic purposes. The "ground truth" for the V&V tests are the established standards for electrical safety, EMC, and wireless communication, and the specifications of the predicate device.

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

• Not applicable. This is not a study requiring adjudication of expert 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:

• No. This is not an AI-assisted device, therefore an MRMC study is not relevant.

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

• Not applicable. This is not an AI algorithm. Its performance is inherent in its measurement capabilities.

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

• Not applicable in the AI/clinical ground truth sense. The "ground truth" for this device's performance relies on:
  • Engineering specifications and standards: Compliance with IEC 60601-1, IEC 60601-1-2, ANSI/IEEE C63.27, etc., which define acceptable performance for medical electrical equipment.
  • Predicate device performance: The previously cleared OptoMonitor 3 (K193620) serves as the benchmark for "equivalent" performance characteristics.

8. The sample size for the training set:

• Not applicable. The device is not an AI/ML algorithm that requires a training set.

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

• Not applicable.

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