(190 days)
The Image Fusion Element is an application for the co-registration of image data within medical procedures by using rigid and deformable registration methods. It is intended to align anatomical structures between data sets.
The Image Fusion Element can be used in clinical workflows that benefit from the co-registration of image data. For example, this applies to navigation systems or medical data information terminals for image processing or image guided surgery in general as well as for treatment planning software for radiosurgery and radiotherapy. The device itself does not have specific clinical indications.
The Image Fusion Element is intended to co-register volumetric medical image data (e.g. MR, CT). It allows rigid image registration to adjust different spatial position and orientation of two data sets. It also offers deformable registration to compensate image distortion or spatial deviation between image acquisitions.
The Image Fusion Element gives the possibility to show basic planning content (e.g. objects, points, trajectories) defined from one dataset on another dataset and to display datasets of corresponding anatomic planes simultaneously. Further it could process co-registered data to highlight differences between distinct scanning sequences or to assess the response to a treatment.
The provided document is a 510(k) premarket notification for Brainlab AG's "Image Fusion" device. It outlines the device's intended use, technological characteristics, and a summary of safety and effectiveness, primarily through demonstrating substantial equivalence to predicate devices.
However, this document does not contain the detailed study information typically found in a clinical performance study report that would prove the device meets specific acceptance criteria using a test set, ground truth, and statistical analysis as requested in your prompt. The document outlines a verification and validation (V&V) process, but it does not specify quantitative acceptance criteria or report the results of a controlled study against a predefined ground truth in the manner you've described.
Instead, the document focuses on:
- Substantial Equivalence: Comparing the device's features and functionality to existing legally marketed predicate devices (Mirada XD, K101228, and iPlan, K113732). The "Changes to Predicate Device" section and the "Technological Characteristics" table highlight this comparison.
- Verification and Validation Summary: Stating that verification and validation were performed according to internal plans and processes, including usability testing, to ensure design specifications are met and the device can be used safely. There are no specific performance metrics or statistical results presented.
Therefore, I cannot provide the information requested in your numbered list for this specific device from the provided text, as the necessary details regarding acceptance criteria, study design, sample sizes, ground truth establishment, or expert involvement for a clinical performance study are not present.
The document's statement: "Functionality and features considered as substantially equivalent have been verified and validated. The system Image Fusion with its set of functionalities is substantially equivalent to its predicate devices," serves as the core of its argument for market clearance rather than presenting a detailed clinical study demonstrating quantitative performance against specific acceptance criteria.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).