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510(k) Data Aggregation
(218 days)
The NextAR Spine platform is intended as an aid for precisely locating anatomical structures in either open or percutaneous spine procedures. It is indicated for any medical condition in which the use of stereotaxic surgery may be appropriate, when reference to a rigid anatomical structure, such as vertebrae or pelvis, can be identified relative to images of the anatomy. This can include posterior approach spinal procedures, such as:
- · Pedicle Screw Placement (Thoracic and Lumbosacral spine)
- Iliosacral Screw Placement
The NextAR Spine platform is intended to be used in combination with NextAR™Struments and / or Medacta preoperative planning. In the case of pre-operative planning software is used pre-operatively to plan the surgical placement of pedicle screws based upon radiological images of the patient. As an optional display, the NextAR Smart Glasses can be used auxiliary to the NextAR Spine Platform to view stereotaxic information as presented by the NextAR Spine Platform. The NextAR Smart Glasses should not be relied upon solely and should always be used in conjunction with the primary computer display.
The NextARTM Spine Platform is a CT based computer-assisted surgical navigation platform used in either open/mini open or percutaneous spine surgery procedure and includes the following components:
- navigation software which displays information to the surgeon; ●
- Augmented Reality glasses:
- optical tracking system;
- PC based hardware platform; ●
- Fiducial Block;
- Adaptor for sensor:
- Spine attachment instruments ●
- Reusable surgical instruments for spine surgery procedures.
The system operates on the common principle of stereotaxic technology in which markers are mounted on the bones and an infrared camera is used to monitor the spatial location of the instruments. Tracking sensors attached to the bones enable the surgeon to view the position and orientation of the instrumentation relative to the intra-operative data in real-time while performing the surgical procedure. The tracking sensors, the fiducial block and a group of pins and drills are provided sterile.
The NextAR™ Spine Platform aid the surgeon in executing the surgical plan by visualizing all the information in real time in a screen monitor.
The NextAR Spine system is a surgical navigation platform which uses the information of either an intra-operative scan or pre-operative CT in combination with an intra-operative 3D-CArm scan in order to register the spine to navigation elements.
The registration can be performed with one of the following approaches:
- . Direct 3D: based on the use of an intra-operative 3D-CArm scan
- . 3D-3D: based on the use of a pre-operative CT scan and an intra-operative 3D-CArm scan
The system's navigation technology is based on an active infrared camera coupled with an active tracker (Target). These elements allow, by means of the different registration approaches and use of compatible instruments, to accurately prepare trajectories in the vertebrae and/or to implant screws while visualizing information in real time on a screen monitor.
The provided document describes the FDA 510(k) clearance for the Medacta NextAR™ Spine Platform. Here's an analysis of the acceptance criteria and study information:
1. Table of Acceptance Criteria and Reported Device Performance
The document does not explicitly present a table of "acceptance criteria" with specific numerical targets and measured device performance in the format requested. Instead, it states that "Testing was conducted according to written protocols with acceptance criteria that were based on standards." It then lists the types of studies performed that would have generated data to demonstrate meeting these criteria.
However, based on the scope of the device (surgical navigation system for pedicle screw placement), the primary performance metric of interest for evaluating stereotaxic instruments is accuracy, specifically the deviation of the navigated instrument from the planned trajectory or anatomical landmark. While a specific numerical value for "accuracy" is mentioned as a shared characteristic with the predicate device, it is not explicitly quantified as an acceptance criterion in the provided text.
Inferred Information:
Acceptance Criteria (Inferred from device type and studies) | Reported Device Performance (Implied by clearance) |
---|---|
Accuracy (Mechanical and Optical) | Demonstrated to be substantially equivalent to predicate devices. Benchtop accuracy verification conducted. |
Software Verification and Validation | Successfully completed. |
Performance Testing (Mechanical and Optical Properties) | Successfully completed. |
Clinical Performance (Cadaveric Study) | Demonstrated that the device aids in precisely locating anatomical structures for pedicle and iliosacral screw placement. |
2. Sample Size for Test Set and Data Provenance
- Test Set (Cadaver Validation Study): The document states that a "cadaver validation study" was performed. However, it does not specify the sample size (e.g., number of cadavers, number of vertebrae, or number of screw placements) used for this study.
- Data Provenance: The document does not explicitly state the country of origin. Given the manufacturer, Medacta International SA, is based in Switzerland, data could originate from there or other regions where testing facilities are available. It is a prospective study as it involves active testing on cadavers.
3. Number of Experts and Qualifications for Ground Truth
The document does not specify the number of experts used to establish ground truth for the test set or their qualifications. For cadaveric studies involving screw placement, ground truth would typically be assessed by experienced surgeons or radiologists.
4. Adjudication Method for the Test Set
The document does not specify the adjudication method used for the test set.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
The document does not mention a Multi-Reader Multi-Case (MRMC) comparative effectiveness study or any effect size related to human reader improvement with or without AI assistance. This type of study is more common for diagnostic AI tools and less directly applicable to a surgical navigation platform focused on physical precision.
6. Standalone (Algorithm Only) Performance Study
The document describes the NextAR™ Spine Platform as a surgical navigation platform that aids the surgeon. While it has algorithms for registration and visualization, its intended use is with a human in the loop. The "benchtop accuracy verification" and "cadaver validation study" would evaluate the system's performance, but it's not explicitly framed as a "standalone algorithm only" study in the sense of a diagnostic AI system without human input. The navigation software displays information to the surgeon, implying human interaction is integral.
7. Type of Ground Truth Used
For the "cadaver validation study," the ground truth would typically be established based on:
- Expert Consensus/Assessment: Post-procedure evaluation by surgeons or imaging specialists using high-resolution imaging (e.g., CT scans) to determine the actual trajectory and position of implanted screws relative to anatomical landmarks or intended trajectories.
- Imaging Data: Post-operative imaging (like CT scans) would be compared against the pre-operative plan and intra-operative navigation data to assess accuracy.
The document does not explicitly state the type of ground truth used, but these are standard practices for such studies.
8. Sample Size for the Training Set
The document does not provide any information regarding a "training set" or its sample size. Surgical navigation systems like NextAR Spine typically rely on principles of image processing, stereotaxy, and 3D registration that are established algorithms, rather than deep learning models that require large proprietary training datasets in the same way an AI diagnostic tool would. If machine learning components are present, information on their training would be missing.
9. How Ground Truth for the Training Set Was Established
As no training set is mentioned (see point 8), there is no information on how ground truth for a training set was established.
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