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The NeuroSystems 1™ monitor has been designed for use by a qualified neurosurgeon to display variables from existing legally marketed primary measuring devices used to monitor neurosurgical patients. The variables displayed by the NeuroSystems 1™ monitor include intracranial pressure, cerebral blood flow, brain tissue oxygen, brain temperature and pH, carbon dioxide and arterial blood pressure, and these are presented both continuously and as trends in these variables, and in the form of relationship graphs. The presentation of both measured variables and the relationships between them is intended as an adjunct to the information provided by existing primary monitors, and the NeuroSystems 1™ monitor should not be used alone as the sole basis for decisions as to diagnosis or therapy.

The NeuroSystems 1TM monitor is a secondary display system that collects together on a single large color display screen all of the measured variables relevant to the multi-modality monitoring of the patient in a neurosurgical intensive care unit. The NeuroSystems 17M monitor has inputs to receive analog data from primary monitors used in the measurement of intracranial pressure, cerebral blood flow, brain tissue oxygen, brain temperature and pH, carbon dioxide and arterial blood pressure. The monitor can also derive the cerebral perfusion pressure. The NeuroSystems 17M monitor displays the measured and derived variables in digital and analog trace form, and can store and display trends over periods of 1,2,8 or 24 hours. The system also facilitates the display of the interrelationships between the measured and derived variables. This allows the approximation of Cerebral Autoregulation, Vasoreactivity and O2 Metabolic Index.

This document describes the NeuroSystems 1™ Monitor, a secondary display system for neurosurgical intensive care units (NICU). It consolidates data from primary monitors measuring intracranial pressure, cerebral blood flow, brain tissue oxygen, brain temperature, pH, carbon dioxide, and arterial blood pressure. The monitor displays these variables in digital, analog trace, and trend forms, and can also visualize relationships between them.

Here's an analysis of the provided information concerning acceptance criteria and study details:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly state specific numerical acceptance criteria or performance metrics for the NeuroSystems 1™ Monitor in a tabular format. The document is a 510(k) summary, which focuses on demonstrating substantial equivalence to predicate devices rather than providing detailed performance validation studies often seen for novel devices.

The key claim regarding performance is:

• "The NeuroSystems 1TM system is similar in design, intended use and performance characteristics to the predicate devices." (Section 6)
• "No new issues of safety or effectiveness are introduced by using this device." (Section 6)

This implies that the device's performance is considered acceptable because it is substantially equivalent to already legally marketed devices (Novus Monitoring Limited NeuroSensor® System K013930 and Diametrics Medical Limited Neurotrend System K980380), which are presumed to meet established performance and safety standards. The "performance" in this context refers to its ability to accurately receive, display, and process data from primary monitors, consistent with its intended use as a secondary display system.

2. Sample Size Used for the Test Set and Data Provenance

The document does not report any specific sample size for a test set or the provenance of data used for validation. This is typical for 510(k) submissions focusing on substantial equivalence where extensive de novo clinical trials or performance studies with specific sample sizes might not be required if predicate devices provide sufficient evidence of safety and effectiveness. The device's function is data presentation and derivation, not direct measurement or diagnosis, which would typically necessitate specific test sets for accuracy validation.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

No information is provided regarding experts or ground truth establishment for a test set. As the device is a secondary display and data aggregator, its validation would likely involve engineering verification of data display accuracy, calculation correctness for derived variables, and software functionality, rather than expert-adjudicated ground truth scenarios.

4. Adjudication Method for the Test Set

No adjudication method is mentioned as there's no reported test set or expert evaluation described.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No MRMC comparative effectiveness study is mentioned. This type of study is usually conducted for diagnostic or AI-assisted devices that directly influence clinical decision-making or improve human reader performance. The NeuroSystems 1™ Monitor is an information display system, not a diagnostic aid that would typically undergo MRMC studies.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

The concept of "standalone performance" does not directly apply in the way it would for an AI diagnostic algorithm. The NeuroSystems 1™ Monitor is inherently a "human-in-the-loop" device in that it presents information to a qualified neurosurgeon. Its performance would be assessed on the accuracy and reliability of its data presentation and derived calculations, independent of direct human interaction during those processes, but ultimately for human interpretation. The document does not describe specific tests for this, relying on the overall substantial equivalence claim.

7. The Type of Ground Truth Used

No specific type of ground truth is mentioned. For a device of this nature (secondary display), "ground truth" would likely involve:

• Engineering verification: Ensuring the device accurately receives data inputs from primary monitors.
• Software validation: Confirming that the display of digital and analog traces correctly reflects the input data.
• Calculation verification: Ensuring derived variables (e.g., cerebral perfusion pressure, O2 Metabolic Index) are calculated correctly based on established physiological formulas and input data.
• Comparison to predicate devices: Demonstration that its functionality for display and derivation is comparable to previously approved devices.

8. The Sample Size for the Training Set

No training set is mentioned. The device is not described as using machine learning or AI that would require a "training set" in the conventional sense. Its functionality is based on pre-programmed logic, data display, and calculation rather than learning from data.

9. How the Ground Truth for the Training Set Was Established

Not applicable as there is no mention of a training set.

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