(102 days)
BrainLAB VectorVision fluoro3D is intended as an intraoperative image-guided localization system to enable minimally invasive surgery. It links a freehand probe, tracked by a passive marker sensor system to virtual computer image space on a patient's preoperative or Intraoperative 2D or 3D image data.
VectorVision fluoro3D enables computer-assisted navigation of medical image data, which can either be acquired preoperatively or intraoperatively by an appropriate image acquisition system.
The software offers screw implant size planning and navigation on rigid bone structures with precalibrated and additional individually-calibrated surgical tools.
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, the pelvis, a long bone or vertebra can be identified relative to the acquired image (CT, MR, 2D fluoroscopic image or 3D fluoroscopic image reconstruction) and/or an image data based model of the anatomy.
VectorVision fluoro 3D is a device that allows surgical planning and navigation. It links a surgical instrument, (tracked by passive marker sensor system) to a location on a virtual computer image, which is either based on patient's intraoperative 3D information acquired with a 3D C-arm or based on patient's intraoperative acquired 2D fluoro image(s) of an analog or digital c-arm.
The device enables the navigation based on 3D data and / or based on acquired fluoro images. Based on 2D fluoro images, the registration is done automatically by using the exact spatial position information of the intra-operatively acquired fluoro images.
Based on 3D data, the registration is also done automatically by using the exact spatial position information of the start position of the scan. Beforehand, the 3D Siemens C-arm has to be calibration with the navigation svstem.
For 3D data, the paired point matching and the 2D 3D fluoro matching are also available as reregistration methods. The last registration method uses two fluoro images (one in lateral position) to regain accuracy on previously acquired 3D scans. This may become necessary if the reference on the patients bone has become lose.
The device assists the surgeon in performing certain surgical procedures as described in the indications for use.
The provided document is a 510(k) summary for the BrainLAB VectorVision fluoro 3D system, which is an intraoperative image-guided localization system. This document focuses on demonstrating substantial equivalence to predicate devices and outlines the intended use and device description.
Crucially, the provided text does NOT contain information regarding acceptance criteria, specific device performance metrics, or details of a study designed to prove the device meets such criteria. It largely focuses on regulatory aspects, intended use, and a general statement about verification and validation without providing the results or methodology.
Therefore, many of the requested items cannot be answered from the provided text.
Here's what can be extracted and what is missing:
1. Table of Acceptance Criteria and Reported Device Performance
| Metric | Acceptance Criteria | Reported Device Performance |
|---|---|---|
| Accuracy / Performance | Not provided in the document. | Not provided in the document. The document states that the device has been "verified and validated according to BrainLAB's procedures for product design and development" and that "The validation proves the safety and effectiveness of the information provided by BrainLAB," but no specific performance metrics or thresholds are given. |
2. Sample size used for the test set and the data provenance
- Sample Size for Test Set: Not specified.
- Data Provenance: Not specified. (The document mentions "patient's preoperative or Intraoperative 2D or 3D image data" but does not detail where this data came from for testing purposes, nor if it was retrospective or prospective.)
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- This information is not provided in the document.
4. Adjudication method for the test set
- This information is not provided in the document.
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
- The document does not describe an MRMC comparative effectiveness study. The VectorVision fluoro 3D system is described as an image-guided navigation system for surgeons, not an AI-assisted diagnostic tool for human readers in the traditional sense of an MRMC study. Its function is to provide real-time localization and guidance during surgery.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- The document describes the device as an "intraoperative image-guided localization system to enable minimally invasive surgery," which inherently involves a human (surgeon) in the loop using the system for navigation. Therefore, a purely standalone algorithm performance without human involvement, as might be done for an AI diagnostic tool, is not applicable or described. The system's performance is tied to its ability to guide human clinical action.
7. The type of ground truth used
- Not explicitly stated for any testing. For an image-guided navigation system, ground truth would typically relate to the accuracy of instrument tip localization relative to anatomical structures, often verified through direct measurement with high-precision tools or against a gold standard imaging modality. The document does not detail how this ground truth was established for any validation.
8. The sample size for the training set
- The document does not mention a "training set" in the context of machine learning, as this is an older regulatory submission (2007) for an image-guided surgery system, not a contemporary AI/ML device in the sense of deep learning or predictive models requiring large training datasets. The validation mentioned refers to standard software and device engineering validation processes.
9. How the ground truth for the training set was established
- As the concept of a "training set" in the context of contemporary AI/ML is not applicable to this document, there's no information on how its ground truth was established.
§ 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).