(234 days)
The xvision Spine System, with xvision System Software, is intended as an aid for precisely locating anatomical structures in either open or percutaneous spine procedures. Their 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 CT imagery of the anatomy. This can include the following spinal implant procedures:
- Posterior Pedicle Screw Placement in the thoracic and sacro-lumbar region.
- Posterior Screw Placement in C3-C7 vertebrae
- Iliosacral Screw Placement
The Headset of the xvision System displays 2D stereotaxic screens and a virtual anatomy screen. The stereotaxic screen is indicated for correlating the tracked instrument location to the registered patient imagery. The virtual screen is indicated for displaying the virtual instrument location to the virtual anatomy to assist in percutaneous visualization and trajectory planning.
The virtual display should not be relied upon solely for absolute positional information and should always be used in conjunction with the displayed stereotaxic information.
The xvision Spine (XVS) system is an image-guided navigation system that is designed to assist surgeons in placing pedicle screws accurately, during open or percutaneous computer-assisted spinal surgery. The system consists of a dedicated software, Headset, single use passive reflective markers and reusable components. It uses wireless optical tracking technology and displays to the surgeon the location of the tracked surgical instruments relative to the acquired intraoperative patient's scan, onto the surgical field. The 2D scanned data and 3D reconstructed model, along with tracking information, are projected to the surgeons' retina using a transparent near-eye-display Headset, allowing the surgeon to both look at the patient and the navigation data at the same time.
The following modifications have been applied to the previously cleared XVS system:
The indications for use of the subject device are expanded compared to the cleared predicate device and include screw instrumentation in additional spine segments, i.e., cervical C3-C7 vertebrae and iliosacral region. Additionally, an Artificial Intelligence (AI) spine segmentation algorithm, based on Convolutional Neural Network (CNN), has been added to provide an improved virtual 3D spine model. The virtual 3D model can be built from the original CT scan or from the Al segmented CT scan. Neither of these modifications alters the intended use of the device as an aid in localization during spine surgery or its principles of operation.
Here's a breakdown of the acceptance criteria and study details for the xvision Spine System, based on the provided FDA 510(k) summary:
1. Table of Acceptance Criteria and Reported Device Performance
The document provides the "System Accuracy Requirement" as the primary acceptance criterion related to performance. The study then reports on validation studies that demonstrate the device meets these specifications.
| Acceptance Criterion (System Level Accuracy) | Reported Device Performance |
|---|---|
| Mean 3D positional error of 2.0 mm | Validated in two cadaver studies. Positional errors calculated as the difference between actual and virtual screw tip position. |
| Mean trajectory error of 2° | Validated in two cadaver studies. Trajectory errors calculated as the difference between screw orientation and its recorded virtual trajectory. |
| Additional Performance Parameter (AI Segmentation) | Reported Device Performance |
| Not explicitly stated as an "acceptance criterion" in a quantitative manner, but performance of the AI segmentation algorithm was validated. | Mean Dice coefficient calculated. Compared to manual segmentations approved by US physicians. |
| Additional Performance Parameter (Clinical Accuracy) | Reported Device Performance |
| Not explicitly stated as an "acceptance criterion," but clinical accuracy was evaluated. | Evaluated using the Gertzbein-Robbins score by viewing post-op scans. |
2. Sample Size Used for the Test Set and Data Provenance
- Test Set Sample Size: Two cadaver studies were conducted. The specific number of cases, screws, or segments tested within these cadaver studies is not explicitly stated in the provided document.
- Data Provenance: The document states "two cadaver studies." This suggests the data is prospective (generated for this specific testing) and likely from a laboratory or research setting. The country of origin of the cadavers or the study location is not specified.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications
- For the cadaver studies (positional and trajectory errors), the method of establishing ground truth (e.g., through physical measurements) is implied by "actual... screw tip position" and "actual... screw orientation" but the number or qualifications of experts involved in these measurements are not specified.
- For the AI segmentation algorithm validation: "manual segmentations that were approved by US physicians" were used as ground truth. The number of physicians/experts and their specific qualifications (e.g., years of experience as radiologists or surgeons) are not specified.
4. Adjudication Method for the Test Set
- For the cadaver studies, no adjudication method is described. Measurements for positional and trajectory errors are typically objective and can be directly measured.
- For the AI segmentation validation, the manual segmentations were "approved by US physicians." This suggests a consensus or review process, but the specific adjudication method (e.g., 2+1, 3+1) is not detailed.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size
- The document does not indicate that an MRMC comparative effectiveness study was done to evaluate how human readers improve with AI vs. without AI assistance. The AI component is described as providing an "improved virtual 3D spine model" but its impact on human reader performance is not measured in this submission.
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done
- Yes, a standalone performance evaluation was conducted for the AI segmentation algorithm. The "mean Dice coefficient was calculated" to measure the quality of the algorithm's segmentation compared to manual ground truth. This is a common metric for evaluating the performance of segmentation algorithms independently.
7. The Type of Ground Truth Used
- For system accuracy (positional/trajectory errors): The ground truth was based on physical measurements of actual screw tip position and orientation in cadavers.
- For AI segmentation algorithm: The ground truth was established by manual segmentations approved by US physicians.
8. The Sample Size for the Training Set
- The document does not specify the sample size for the training set used for the Convolutional Neural Network (CNN) based AI spine segmentation algorithm. It only mentions that the algorithm has been "added to provide an improved virtual 3D spine model."
9. How the Ground Truth for the Training Set Was Established
- The document does not explicitly state how the ground truth for the training set of the AI algorithm was established. While it mentions manual segmentations by US physicians for the validation set, it does not detail the process for the training data. It's common practice for training data ground truth to also be established by expert annotation, but this is not explicitly confirmed in the provided text.
§ 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).