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The Fiagon Navigation System is intended as an aid for 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
• Pediatric Catheter Shunt Placement

The user should consult the "Bench Accuracy" section of the User Manual to assess whether the accuracy of the system is suitable for their needs.

The Fiagon Navigation System displays the position of the instruments in preoperative scans (e.g., CT, MRI, fluoroscopy) utilizing electromagnetic tracking technology. The instrument with integrated sensor and the patient equipped with 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 is updated with a rate of 15 to 45 Hz.

The components of the navigation system are

1. Navigation unit with Navigation software. It has interfaces for screen, mouse and the components 2 – 4 below.

• 2. Navigation sensor (Headrest with field generator)
• 3. Navigation instrument (ShuntPointer, BiopsyPointer190 and BiopsyPointer 250)

4. Patient reference localizer (Localizer Set Bone Anchor and Localizer 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) are 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 includes the spatial measuring device electronics as well. This has connections to the field generating device (navigation sensor), the patient localizer and the navigation instrument.

The 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 patient's anatomy and references it, while the instrument is tracked in relation to the patient localizer and thus to the patient's anatomy.

The provided text describes the Fiagon Navigation System, a stereotaxic instrument used as an aid for locating anatomical structures in neurosurgical procedures. The document focuses on demonstrating the substantial equivalence of this device to existing predicate devices, rather than a standalone AI-driven diagnostic system. As such, many of the requested elements pertaining to AI model validation, such as training set details, multi-reader multi-case studies, and expert consensus for ground truth, are not applicable to this type of medical device submission.

The document primarily details bench testing to assess the accuracy of the navigation system.

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

Acceptance Criteria and Reported Device Performance

The acceptance criteria for this device appear to be implicitly defined by demonstrating accuracy similar to predicate devices. The key performance metrics are Target Registration Error (TRE) and Angular Registration Error (ARE).

The document states, "The results showed that the average Target Registration Error (TRE) for the device with Localizer Set Bone Anchor was 1.17 mm (99% Cl upper bound: 2.47 mm) and the average Angular Registration Error (ARE) was 1.45° (99% CI upper bound: 2.8°), which were similar to the accuracy of the predicate devices." A similar statement is made for the Adhesive Pads. The predicate devices are listed with "Mean bench accuracy: Position Mean: < 2mm; Angular: Mean: < 2º", which serves as the implicit acceptance threshold.

Details of the Study Proving Device Meets Acceptance Criteria

1. Sample Size Used for the Test Set and Data Provenance:

   • The document describes a bench test using a phantom model. It does not refer to a "test set" in the context of patient data or a dataset of medical images for an AI.
   • The sample size for the bench testing (e.g., number of measurements taken) is not explicitly stated.
   • Data Provenance: The data is generated from a physical phantom model and CT scans of that phantom. It is a prospective test conducted specifically for this submission, not retrospective patient data. There is no country of origin for the "data" as it's a bench test, not clinical data from patients.

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

   • This is not applicable for this type of device and study. The "ground truth" for the bench test was established by a Coordinate Measurement Machine (CMM) with an accuracy of 0.018 mm and the CT scans of the phantom with known reference points. This is a physical, measurable ground truth, not one established by human experts or clinical outcomes for an AI system.

3. Adjudication Method for the Test Set:

   • Not applicable. There was no human interpretation or adjudication involved in establishing the "ground truth" for the performance metrics. The accuracy was measured physically against known points on the phantom.

4. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

   • No. This type of study is typically performed for diagnostic or AI-assisted devices where human interpretation is a key component. This device is a navigation system used during surgery, and its evaluation focuses on its physical accuracy, not its impact on human reader performance in interpreting medical images.

5. If a Standalone Performance Study (i.e. algorithm only without human-in-the-loop performance) was done:

   • Yes, in essence, the bench testing is a standalone performance study. The accuracy of the navigation system itself (the "algorithm" in a broad sense, though it's a physical tracking system) was measured independently of surgeons using it in a live setting. The measurements captured the system's ability to accurately register and track instruments against a known physical model.

6. The Type of Ground Truth Used:

   • Physical/Measured Ground Truth: The ground truth was established by precise measurements of target points on a phantom using a Coordinate Measurement Machine (CMM) and the known geometry derived from CT scans of the phantom. This is objective, physical data, not expert consensus or pathological findings.

7. The Sample Size for the Training Set:

   • Not applicable. This document describes a medical device (navigation system) with electromagnetic tracking, not a machine learning or artificial intelligence algorithm that requires a "training set." The system's functionality is based on established physical principles and engineering, not on learning from a dataset.

8. How the Ground Truth for the Training Set was Established:

   • Not applicable, as there is no "training set" for this device.

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The Fiagon Navigation System is intended as an aid for precisely locating anatomical structures in either open or percutaneous 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 ENT surgery, such as the paranasal sinuses, mastoid anatomy, can be identified relative to a CT or MR based model of the anatomy.

Example procedures include, but are not limited to:

ENT Procedures: Transphenoidal access procedures. Intranasal procedures. Sinus procedures, such as Maxillary antrostomies, Sphenoidotomies/Sphenoid explorations, Turbinate resections, and Frontal sinusotomies. ENT related anterior skull base procedures.

The Fiagon Navigation System displays position instruments in preoperative scans (e.g., CT, MRI, fluoroscopy) utilizing electromagnetic tracking technology. The position of the instrument with integrated sensor and the patient equipped with localizers 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 provided document is a 510(k) Premarket Notification from the FDA for a medical device called the Fiagon Navigation System. This type of submission is for demonstrating substantial equivalence to a predicate device, not for establishing novel performance or clinical efficacy through the types of detailed studies typically associated with AI/ML model validation. Therefore, the document does not contain the information required to answer all parts of your request, particularly those related to AI/ML specific evaluations (like training set details, expert consensus for ground truth, MRMC studies, etc.).

However, I can extract the relevant information regarding acceptance criteria and performance data for this device as presented in the submission.

Here's a breakdown based on the provided text:

Acceptance Criteria and Reported Device Performance

The submission focuses on bench testing to demonstrate that the modified device (with WiFi connectivity and iPad remote control with automatic registration) performs as intended and is substantially equivalent to its predicate. The "acceptance criteria" are implied by the types of tests conducted and their successful completion.

1. Table of Acceptance Criteria and the Reported Device Performance:

Study Details (as inferable from the document)

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

• The document mentions "bench testing" but does not specify sample sizes (e.g., number of tests, number of targets, number of wireless interferences) or data provenance (e.g., country of origin, retrospective/prospective). This level of detail is typically not required for a 510(k) submission focused on substantial equivalence of a modified hardware/software system.

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

• This information is not provided. The testing appears to be quantitative bench testing of accuracy and functionality, not a study requiring expert interpretation of medical images or clinical outcomes.

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

• This is not applicable to the type of bench testing described.

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, an MRMC study was not done. This device is a navigation system that displays instrument position relative to pre-operative scans, not an AI/ML diagnostic or assistive tool that would involve "human readers" interpreting images.

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

• The tests described ("Positioning accuracy test for target registration", "Wireless coexisting testing", "Software testing") are essentially standalone performance evaluations of the device's capabilities. However, this is not an AI algorithm in the contemporary sense. The "algorithm" here refers to the underlying calculations for electromagnetic tracking and image-to-patient registration.

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

• For positioning accuracy, the ground truth would likely be established by a precisely measured physical reference (e.g., a known target position in a phantom) rather than clinical expert consensus or pathology. For wireless coexistence and software testing, the ground truth is whether the system performs according to specifications.

8. The sample size for the training set:

• This is not applicable and not provided. This device is not described as an AI/ML system requiring a distinct "training set" in the context of deep learning.

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

• This is not applicable, as there's no mention of a "training set" for an AI/ML model for this device.

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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.

Ask a specific question about this device

The Fiagon Navigation System is intended as an aid for precisely locating anatomical structures in either open or percutaneous 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 ENT surgery, such as the paranasal sinuses, mastoid anatomy, can be identified relative to a CT or MR based model of the anatomy.

Example procedures include, but are not limited to:

ENT Procedures; Transphenoidal access procedures. Intranasal procedures. Sinus procedures, such as Maxillary antrostomies, Ethmoidectomies, Sphenoidotomies/Sphenoid explorations, Turbinate resections, and Frontal sinusotomies. ENT related anterior skull base procedures

The Fiagon Navigation System displays the position instruments in preoperative scans (e.g., CT, MRI, fluoroscopy) utilizing electromagnetic tracking technology. The position of the instrument with integrated sensor and the patient equipped with localizers 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 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 material) :

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 as well the spatial measuring device electronics. This has connections to the field generating device (navigation sensor), the patient 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 patients anatomy and references it, while the instrument is tracked in relation to the patient localizer and thus to the patient's anatomy.

Here's a summary of the acceptance criteria and study details for the Fiagon Navigation System, based on the provided text:

Acceptance Criteria and Device Performance

Study Details

1. Sample Size used for the test set and data provenance:

   • Sample Size: Not explicitly stated in terms of number of cases or patients. The document refers to "bench accuracy" and "clinical accuracy" without providing the sample size for these measurements.
   • Data Provenance: Not explicitly stated. The study appears to be part of the regulatory submission from Fiagon GmbH, a German company, so it's likely the testing occurred in Germany, but this is not confirmed. The document only mentions "Bench testing was conducted" and "Reported mean clinical accuracy," implying these were done by the manufacturer. Retrospective or prospective nature is not specified, but typically performance testing for regulatory submission is prospective.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. The "ground truth" here relates to physical measurements of accuracy and distortion, not expert consensus on medical images or diagnoses.

3. Adjudication method for the test set: Not applicable, as the data are objective measurements of physical accuracy.

4. 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 not an AI/ML-driven diagnostic tool involving human readers; it's an image-guided surgery system. The "AI" in "AI vs without AI assistance" does not apply to this context.

5. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Yes, a standalone performance assessment was done. The "bench testing" and "mean clinical accuracy" reported refer to the inherent accuracy of the device itself in localizing instruments, rather than its performance integrated with human interpretations or decision-making.

6. The type of ground truth used:

   • For bench accuracy, the ground truth would be precise, metrological measurements of known physical locations from a reference standard.
   • For field distortion detection, the ground truth would be controlled induction of electromagnetic field distortions and measurement of when the device detects them.
   • For clinical accuracy, the ground truth would be precise measurements of instrument tip positions relative to anatomical structures, likely through comparison with highly accurate imaging or fiducial markers.

7. The sample size for the training set: Not applicable. This device is an image-guided surgery system based on electromagnetic tracking technology, not a machine learning model that requires a "training set."

8. How the ground truth for the training set was established: Not applicable, as there is no training set mentioned for this type of device.

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