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The Fiagon Navigation System is intended as an aid for precisely locating anatomical structures in either open or percutaneous neurosurgical procedures. The Fiagon Navigation System is indicated for any medical condition in which the use of stereotactic surgery may be appropriate, and where reference to a rigid anatomical structure in the field of cranial surgery can be identified relative to a CT or MR based model of the anatomy.

Example procedures include, but are not limited to:

Cranial Procedures:

• Craniotomies/Craniectomies (e.g., Tumor Resection)
• Skull Base Procedures
• Cranial Biopsies
• General Catheter Shunt Placement

The Fiagon Navigation System displays the position instruments in preoperative scans (e.g., CT, MRI, fluoroscopy) utilizing electromagnetic tracking technology. For cranial procedures, the use of this device is restricted to rigid fixation with a patient reference localizer attached directly to the skull clamp. The position of the instrument with integrated sensor and the patient referencing localizer (attached to the skull clamp) are localized within an electromagnetic field generated by a field generator. The principle of navigation is based on electromagnetic spatial measuring of localizer element in a generated electromagnetic field.

The display of navigation information requires an image-to-patient registration procedure. During registration procedure, the navigation system determines the coordinate transformation between the intraoperative position of the patient and the position of the preoperative scan by fiducial marker, anatomical landmark or surface matching.

Thereafter, the spatial position of the instrument is displayed superimposed to the image data. The navigation information is updated with a rate of 15 to 45 Hz.

The device Fiagon Navigation System utilizing similar technology than the proposed device has been previously cleared for a different intended use. This device is listed as a reference device.

The components of the navigation system are

• 1. Navigation unit with Navigation software. It has interfaces for screen, mouse and the components 2 - 4.
• 2. Navigation sensor (Headrest with field generator)
• 3. Navigation instrument

4. Patient reference localizer (with fixation of the localizer on the skull clamp using the adhesive pad)

The navigation unit is connected to a medical monitor. The unit runs the navigation software. Preoperative radiological images of the patient (DICOM CT, CBCT, MR) is imported to the system by means of CD-ROM. USB storage media or LAN network and displayed in appropriate way (defined by the software).

The navigation unit compromises the spatial measuring device electronics as well. This has connections to the field generating device (navigation sensor), the patient reference localizer and the navigation instrument.

Patient reference localizer and navigation instrument are tracked within the generated field by localizer elements integrated in the devices.

The patient reference localizer is fixed to the skull clamp and references the patient's anatomy, while the instrument is tracked in relation to the patient reference localizer and thus to the patient's anatomy.

Here's a breakdown of the acceptance criteria and study information for the "Fiagon Navigation System" based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size for Test Set and Data Provenance

The document mentions "Bench testing was conducted to determine the device accuracy and the performance of the electromagnetic field distortion mechanism." However, it does not specify the sample size used for the test set (e.g., number of measurements, number of trials, or number of phantom setups).

The data provenance is from bench testing, meaning it was conducted in a controlled laboratory environment rather than on human subjects. The country of origin of the testing is not explicitly stated, but the company, Fiagon GmbH, is based in Germany. The study is a prospective test in the sense that the device was specifically designed and then tested to meet these criteria.

3. Number of Experts and Qualifications for Ground Truth

The document does not mention the use of experts to establish ground truth for the test set. Bench testing typically relies on metrology equipment to define ground truth.

4. Adjudication Method

The document does not mention an adjudication method as it relates to expert review. For bench testing, the "adjudication" is typically the comparison of the device's output against a known, highly accurate reference measurement performed by the testing equipment.

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

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. This type of study primarily focuses on the interpretation and decision-making of human readers, which is not applicable to an image-guided navigation system's direct performance. The document focuses on the technical accuracy and precision of the device itself.

6. Standalone (Algorithm Only) Performance Study

Yes, a standalone performance study was done. The entire "Performance Data" section describes bench tests performed on the device (the algorithm and hardware) to determine its precision and accuracy, without human interpretation or intervention in the measurement process. "Bench testing was conducted to determine the device accuracy and the performance of the electromagnetic field distortion mechanism."

7. Type of Ground Truth Used

The ground truth for the bench accuracy tests was established using technical measurements and co-ordinate measurement systems. For example, the document states: "measurement of technical accuracy with co-ordinate measurement system followed by measurement of positional and angular accuracy without registration to measure the angular accuracy of the instrument itself."

8. Sample Size for Training Set

The document does not mention a training set or its sample size. Image-guided navigation systems like the Fiagon Navigation System are typically engineered with deterministic algorithms and robust calibration methods, rather than being "trained" in the machine learning sense with large datasets. Their performance is validated through precision and accuracy testing against known physical benchmarks.

9. How Ground Truth for Training Set Was Established

Since a "training set" in the machine learning context is not mentioned or implied for this device, the question of how its ground truth was established is not applicable. The system's underlying principles are based on electromagnetic tracking and geometry, rather than data-driven learning from a labeled training set.

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