(25 days)
BrainLAB VectorVision hip is intended to be an intraoperative image guided localization system. It links a freehand probe, tracked by a passive marker sensor system to virtual computer image space either on a patient's preoperative image data being processed by a VectorVision workstation or on an individual 3D-model of the patient's bone, which is generated through acquiring multiple landmarks on the bone surface. The system is indicated for any medical condition in which the use of stereotactic surgery may be appropriate and where a reference to a rigid anatomical structure, such as the skull, a long bone, or vertebra, can be identified relative to a CT, X-ray, MR based model of the anatomy. The system aids the surgeon to accurately navigate a hip endoprothesis to the preoperatively or intraoperatively planned position. Example orthopedic surgical procedures include but are not limited to: Total Joint Replacement (TJR), Revision surgery of TJR, Tumor resection and bone/joint reconstruction.
BrainLAB VectorVision® Hip is intended to enable operational planning and navigation in orthopedic surgery. It links a surgical instrument, tracked by flexible passive markers to virtual computer image space on an individual 3D-model of the patient's bone, which is either based on a patients preoperative image data or generated through acquiring multiple landmarks on the bone surface. VectorVision® Hip uses the registered landmarks to navigate the needed surgical tools like cup reamer, cup inserter, stem rasp, bone saw and the implant to the planned position. If no implant data is available it is possible to provide information in order to achieve a generally targeted alignment relative to the bone orientation as defined by the operating surgeon. VectorVision® Hip allows 3-dimensional reconstruction of the relevant mechanical axes and planes of femur and pelvis and alignment of the VectorVision® Hip software has been designed to read in data of implants and tools if provided by the implant manufacturer and offers to individually choose the prosthesis during each surgery. The VectorVision® Hip software registers the patient data needed for planning and navigating the surgery intra-operatively within the CT free module. The System can be used to generally align tool orientations according to the anatomy described and defined by the landmarks acquired by the surgeon. Using the CT based module the patient data can be used additionally for surgery, the patient data is then is provided by the CT data stored on a standard data storage media.
The provided document is a 510(k) summary for the VectorVision® hip system. It describes the device, its intended use, and states that it has been verified and validated according to BrainLAB's procedures. However, this document does not contain the specific acceptance criteria and detailed study results that would typically be used to prove a device meets those criteria.
The document states: "VectorVision® hip has been verified and validated according to BrainLAB's procedures for product design and development. The validation proves the safety and effectiveness of the system." This suggests that a study was conducted, but the details of that study, including the acceptance criteria and performance metrics, are not included in this publicly available summary.
Therefore, I cannot provide the requested information based only on the input you shared. A 510(k) summary is a high-level overview. The detailed validation and verification studies, including acceptance criteria and performance data, are typically found in the full 510(k) submission, which is not publicly accessible in its entirety.
Here's what I can tell you based on the provided text, and what I cannot:
1. A table of acceptance criteria and the reported device performance
- Cannot be provided. This information is not present in the 510(k) summary.
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Cannot be provided. This information is not present in the 510(k) summary.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
- Cannot be provided. This information is not present in the 510(k) summary. The nature of the device (a surgical navigation system) suggests that "ground truth" might relate more to mechanical accuracy and alignment compared to a planned position, rather than diagnostic interpretation by experts.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Cannot be provided. This information is not present in the 510(k) summary.
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
- Not applicable and cannot be provided. This device is a surgical navigation system, not an AI-assisted diagnostic tool for "human readers." Its purpose is to guide a surgeon during an operation to accurately navigate a hip endoprothesis.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not explicitly stated, but the nature of the device implies a "standalone" accuracy assessment. Surgical navigation systems are generally evaluated on their inherent accuracy in tracking and displaying anatomical structures and instrument positions relative to a plan. This would be an "algorithm and hardware only" performance assessment, where the performance of the system itself (tracking accuracy, registration accuracy) is measured. However, the specific details or results of such a test are not included in this document.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- Cannot be explicitly stated. For a surgical navigation system, ground truth would likely involve highly precise measurements of physical alignment and position (e.g., using a coordinate measuring machine or highly accurate phantom models) compared to the system's reported measurements or the surgical plan. This is not "expert consensus" or "pathology" in the typical sense for a diagnostic device.
8. The sample size for the training set
- Not applicable and cannot be provided. This device is a surgical navigation system. It does not typically "learn" or require a "training set" in the way a machine learning algorithm for image analysis does. Its functionality is based on geometric computations and tracking algorithms.
9. How the ground truth for the training set was established
- Not applicable and cannot be provided. As above, it's not a machine learning device in the sense that it has a "training set" to establish ground truth for.
In summary, the provided 510(k) summary confirms that validation and verification were performed but does not contain the detailed study results or acceptance criteria. You would need to access the full 510(k) submission to find this level of detail.
§ 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).