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The device is intended for the spatial positioning and orientation of instrument holders or tool guides to be used by neurosurgeons to guide standard neurosurgical instruments (biopsy needle, stimulation or recording electrode, endoscope). The device is indicated for any neurosurgical procedure in which the use of stereotactic neurosurgery may be appropriate.

The ROSA One Brain application device is a robotized image-guided device that assists the surgeon during brain surgeries.

It provides quidance of any surgical instruments compatible with the diameter of the adaptors supplied by Medtech. It allows the user to plan the position of instruments or implants on medical images and provides stable, accurate and reproducible guidance in accordance with the planning.

The device is composed of a robot stand with a compact robotic arm and a touch screen.

Different types of instruments may be attached to the end of the robot arm and changed according to the intended surgical procedure. For Brain applications, these neurosurgical instruments (e.g. biopsy needle, stimulation or recording electrode, endoscope) remain applicable for a variety of procedures as shown below in Figure 5.1 for the placement of recording electrodes.

The touchscreen ensures the communication between the device and its user by indicating the actions to be performed with respect to the procedure.

Adequate guidance of instruments is obtained from three-dimensional calculations performed from desired surgical planning parameters and registration of spatial position of the patient.

The ROSA ONE Brain Application device is a robotized image-guided device that assists neurosurgeons during brain surgeries by providing guidance for instruments.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size and Data Provenance

• Test Set Sample Size: Not explicitly stated but inferred to be a series of physical bench tests on the device.
• Data Provenance: The studies were non-clinical performance tests conducted to support the substantial equivalence determination for the ROSA ONE Brain application. The tests are described as "Performance bench Testing in compliance with internal Medtech/Zimmer Biomet robotics procedures." No specific country of origin for the direct test data is mentioned, but Medtech S.A. is based in Montpellier, France.

3. Number of Experts and Qualifications for Ground Truth

This information is not provided in the document. Given that the studies were non-clinical performance tests for engineering specifications, a panel of clinical experts for ground truth establishment, as might be used for diagnostic AI, would likely not be applicable in the same way. The "ground truth" for these tests would be the established engineering specifications and recognized international standards.

4. Adjudication Method

An adjudication method (e.g., 2+1, 3+1) is not applicable as this study involved non-clinical performance and engineering validation tests, not clinical assessment of results by multiple human readers.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The submission explicitly states: "Clinical data were not required to support the safety and effectiveness of ROSA ONE Brain application. All validation was performed based on non-clinical performance tests." Therefore, there is no effect size reported for human readers improving with AI assistance.

6. Standalone Performance

The performance data presented are for the standalone (algorithm only without human-in-the-loop performance) of the robotic system's accuracy and compliance with various engineering and safety standards. The "System applicative accuracy" directly refers to the device's inherent precision.

7. Type of Ground Truth Used

The ground truth for the non-clinical performance tests was based on:

• Established engineering specifications (e.g., target accuracy metrics).
• Compliance with recognized international standards (e.g., IEC 60601-1, IEC 60601-1-2, ISO 10993-1, IEC 62304, ISO 17665-1, ISO 17664, ANSI/AAMI ST79, AAMI TIR 12).
• Predicate device testing results for biocompatibility, where the subject device was evaluated for substantial equivalence.

8. Sample Size for the Training Set

The document does not specify a separate training set or its sample size. This device is a robotic surgical assistance system, and the accuracy and performance data provided relates to the hardware and software's adherence to engineering specifications and regulatory standards, rather than a machine learning model trained on a dataset. The software validation refers to verification and validation activities according to IEC 62304, which are standard for medical device software development, not necessarily the training of an AI model with a distinct training dataset.

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

As no specific "training set" for a machine learning model is mentioned, the method for establishing its ground truth is not applicable or described in this document. The ground truth for the device's overall performance validation was based on compliance with engineering specifications and regulatory standards as described in point 7.

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