(149 days)
The TruDi™ Navigation System is intended for use during surgical procedures in ENT and ENT skull base surgery to support navigation of instruments to targeted anatomy, where reference to rigid anatomic structure can be identified relative to a CT or MR based model.
The TruDi™ Navigation System V2 is intended to be used during surgical procedures in ENT and ENT skull base surgery to support navigation of instruments to the targeted anatomy, where reference to a rigid anatomical structure can be identified relative to a CT or MR based model.
The TruDi™ Navigation System V2 enables ENT physicians to access sphenoid, frontal, and maxillary sinuses, as well as the skull base, by using the systems magnetic tracking technology, which is the same technology used by both of the predicate devices.
The system incorporates a Navigation Console, Emitter Pad, Instrument Hub, Patient Tracker, Registration Probe, and Holder, Workstation and accessories. A magnetic field generated by the Emitter Ring (Field Ring) induces a current in the magnetic sensor embedded in the tip of the flexible navigated tool, which helps to accurately calculate the tool tip position. A CT image is imported and registered to the patient coordinates and a tool tip icon is displayed on top of the registered image, indicating the position of the tool in reference to the patient anatomy. A Patient Tracker is fixed to the patient forehead to compensate for the head movement during the navigation procedure.
The provided text describes the TruDi™ Navigation System V2 and its testing to demonstrate substantial equivalence to predicate devices, focusing on non-clinical performance data. Here's a breakdown of the requested information:
1. Table of Acceptance Criteria and Reported Device Performance
The document provides "Location Accuracy" and "Simulated Use Location Accuracy" as key performance metrics. It compares these against predicate devices.
| Metric | Acceptance Criteria (Implicit from Predicate/Testing) | Reported Device Performance (TruDi™ Navigation System V2) |
|---|---|---|
| Bench Location Accuracy | Similar to or better than predicate devices (e.g., 0.9 mm, 0.55 mm) | 0.55 mm (standard Deviation 0.7 mm) |
| Simulated Use Location Accuracy | Similar to or better than predicate devices (e.g., 1.79 mm, 0.63 mm) | 1.1 mm (Standard deviation 0.2 mm) |
| System Accuracy | Within 2 mm | Within 2 mm |
| Instrument Angular Accuracy | Within 6° | Within 6° |
| Location Update Rate | Similar to predicate (e.g., 15-45Hz, 10Hz) | 10Hz |
| Hardware Modules Performance | Within specifications | Verified |
| Software Functionality | Complete functionality, error handling, usability, time performance | Verified |
| Safety, EMC, and Mechanical Compliance | Compliance with relevant standards | Verified |
2. Sample Size Used for the Test Set and the Data Provenance
The document primarily describes non-clinical testing.
- Sample Size for Test Set: Not explicitly stated as a number of "cases" or "patients" in the traditional sense, as the tests were non-clinical bench and cadaver studies. For location accuracy tests, it refers to measurements over the "entire navigation volume." For the simulated use accuracy test, it involved a "complete CT image registration and instrument navigation workflow."
- Data Provenance: Non-clinical (bench testing, software functional tests, cadaver tests). No country of origin is specified for these non-clinical tests, and they are inherently retrospective in that they are performed on the device itself and not on human subjects for clinical data collection.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts
- Number of Experts: Not applicable, as the ground truth for non-clinical accuracy was established using a "highly accurate robot system" and "pre-clinical (cadaver) tests" mimicking surgical procedures. These methods rely on controlled measurements and simulated environments rather than expert consensus on clinical cases.
- Qualifications of Experts: Not applicable.
4. Adjudication Method for the Test Set
Not applicable, as the described tests are non-clinical, controlled laboratory measurements, and cadaver studies, not human subject studies requiring adjudication of clinical outcomes or assessments.
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 comparative effectiveness study was not done. The document states: "Clinical data was not necessary to determine that the subject TruDi™ Clinical Performance Navigation System V2 performs as intended." The device is an image-guided navigation system, not an AI-assisted diagnostic device requiring human reader improvement comparison.
6. If a Standalone (i.e. algorithm only without human-in-the loop performance) Was Done
The device is a "Navigation System" intended to aid surgeons. Its "standalone" performance (algorithm only) would be its accuracy in localizing instruments relative to image data, which is captured by the "Location Accuracy" and "Simulated Use Accuracy" tests. These tests assess the system's ability to accurately track and display instrument position within a simulated environment without direct human "performance" in the sense of a diagnostic interpretation.
7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)
The ground truth for the non-clinical tests were:
- Location Accuracy: The locations provided by a "highly accurate robot system."
- Simulated Use Accuracy: The actual positions within the simulated CT image registration and instrument navigation workflow.
- System/Angular Accuracy: Controlled measurements against expected values for system and instrument angles.
8. The Sample Size for the Training Set
The document does not describe the use of machine learning or AI models with a "training set" in the context of this 510(k) submission. The TruDi™ Navigation System uses electromagnetic tracking technology and image registration, not a machine learning algorithm that typically requires a large training dataset.
9. How the Ground Truth for the Training Set Was Established
Not applicable, as there is no mention of a training set for a machine learning model.
§ 882.4560 Stereotaxic instrument.
(a)
Identification. A stereotaxic instrument is a device consisting of a rigid frame with a calibrated guide mechanism for precisely positioning probes or other devices within a patient's brain, spinal cord, or other part of the nervous system.(b)
Classification. Class II (performance standards).