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The RIWOtrack Navigation System is intended to continuously display the position and orientation of RIWOspine surgical instruments relative to the anatomy in medical image data in either open or minimal invasive orthopedic procedures.

The use is indicated for any medical condition in which the use of stereotactic surgery may be appropriate, and where reference to a rigid anatomical structure, such as the spine or pelvis, can be identified relative to images of the anatomy.

This can include spinal procedures, where the target point for the access to the access to the area of interest, is a rigid landmark, such as:

· Transforaminal procedure

• Interlaminar procedure

The RIWOtrack Navigation System is an image guided surgery system, visualizing instrument positions on intraoperative fluoroscopy images (AP and LAT) utilizing electromagnetic tracking technology. The positions of the instrument and of the patient localizer, both equipped with sensors, are localized within an electromagnetic field, generated by a field generator, called navigation sensor. 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 physical position of the patient and the position of the patient in intraoperative scans by means of autodetection of x-ray marker of a device called MapperBridge. 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.

Here's a breakdown of the acceptance criteria and study information for the RIWOtrack Navigation System, based on the provided FDA 510(k) summary:

Acceptance Criteria and Device Performance

Study Details for Accuracy Bench Testing

The document mentions "Accuracy bench testing for each instrument probe and localizer" as a performance test. While it confirms the device met the specified criteria of "Position error < 2mm" and "Angular error < 2°", the detailed information regarding the test set, ground truth, and training set is not explicitly provided in this 510(k) summary.

Based on the information available:

• Sample size used for the test set and data provenance: Not explicitly stated. The description refers to "each instrument probe and localizer," suggesting multiple tests for different components, but specific quantities or origin (e.g., country, retrospective/prospective) are not provided.
• Number of experts used to establish the ground truth for the test set and their qualifications: Not explicitly stated. For bench testing, ground truth is typically established through precise measurement devices rather than expert human interpretation.
• Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable for a bench test where objective measurements are taken against a known standard.
• If a multi reader multi case (MRMC) comparative effectiveness study was done: No, an MRMC study was not done. The tests performed were primarily technical performance assessments.
• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Yes, the accuracy bench testing assessed the system's performance directly, independent of human interaction during the measurement process, to determine its inherent accuracy in tracking position and orientation.
• The type of ground truth used: For accuracy bench testing, the ground truth would be established by highly precise measurement systems or calibrated references (e.g., optical trackers, coordinate measuring machines) against which the device's electromagnetic tracking measurements are compared. The document does not specify the exact method but implies a highly accurate reference.
• The sample size for the training set: Not applicable for this type of bench testing. The device is a navigation system that localizes physical objects using electromagnetic tracking, not a machine learning model that requires a training set for pattern recognition.
• How the ground truth for the training set was established: Not applicable, as there is no mention of a training set for this type of performance evaluation.

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