(287 days)
Brainlab Elements are software applications indicated for the processing of medical image data to support the intended user group to perform image guided surgery and radiation treatment planning.
Brainlab Elements Contouring provides an interface with tools and views to outline, refine, combine and manipulate structures in patient image data. The generated 3D structures are not intended to create physical replicas used for diagnostic purposes.
Brainlab Elements Image Fusion 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.
Brainlab Elements Fibertracking is an application of cranial white matter tracts based on Diffusion Tensor Imaging (DTI) data for use in treatment planning procedures.
Brainlab Elements BOLD MRI Mapping provides tools to analyze task based blood oxygen level dependent data (BOLD MRI Data) to visualize the activation signal.
Brainlab Elements Image Fusion Angio is a software application that is intended to be used for the co-registration of cerebrovascular image data.
The Brainlab Elements 6.0 are applications that transfer DICOM data to and from picture archiving and communication systems (PACS) and other storage media devices. They include modules for 2D & 3D image viewinq, imaqe processing, image co-registration, image seqmentation and 3D visualization of medical image data for treatment planning procedures.
They consist of the following software applications:
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- Contouring 4.5
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- Imaqe Fusion 4.5
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- Fibertracking 2.0
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- BOLD MRI Mapping 1.0
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- Image Fusion Angio 1.0
This device is a successor of the Predicate Device Brainlab Elements 5.0 (K212420).
Brainlab Elements Contouring provides an interface with tools and views to outline, edit, refine, combine and manipulate structures in patient image data. The output is saved as 3D DICOM seqmentation object and can be used for further processing and treatment planning.
Brainlab Elements Image Fusion is an application for the co-registration of image data within medical procedures by using rigid and deformable registration methods.
The co-registration consists on providing spatial alignment/fusion of medical imaging data, which are derived from different or same imaging modalities (e.g. CT, MRI, PET, SPECT, US). Once two image sets are fused, they can be viewed simultaneously. All planned content (e.g. objects and trajectories) defined in one image set is visible in any other fused image set. The algorithm used in Image Fusion matches two image sets together with common anatomical structures for optimal fusion results. Therefore, the two image sets must share the same common anatomical area.
Brainlab Elements Fibertracking is an application for the processing and visualization of information based upon Diffusion Tensor Imaging (DTI) data, i.e. to calculate and visualize cranial white matter tracts in selected regions of interest, which can be used for treatment planning procedures.
Diffusion Tensor Imaging (DTI) is a magnetic resonance technique, that allows the measurement of diffusion anisotropy in the brain using diffusion weighted images that were scanned with magnetic field gradients applied in several directions. The Fibertracking software uses the scans to calculate the diffusion direction of the water molecules alonq potential white matter fibers for the entire data volume.
Brainlab Elements Image Fusion Angio is a software application that is intended to be used for the co-registration of cerebrovascular image data. It allows to register digital subtraction anqiographies to vascular images in order to combine flow and location information. In particular, 2D DSA (digital subtraction angiography) sequences can be fused to MRA, CTA and 3D DSA sequences.
The provided text is a 510(k) Summary for Brainlab Elements 6.0 and related applications. It describes the device, its intended use, and argues for its substantial equivalence to predicate devices, including an older version of Brainlab Elements and iPlan.
However, the document does not contain the detailed performance study information requested in your prompt. Specifically, it lacks:
- A table of acceptance criteria and reported device performance. The document states "Verification and validation activities carried out established that the set requirements were met and that the device performs as claimed," but does not provide specific metrics or a table.
- Sample size and data provenance for a test set. It mentions a "test pool data" set aside for AI/ML algorithm evaluation but gives no size or details on provenance.
- Number and qualifications of experts for ground truth.
- Adjudication method for the test set.
- Details on any MRMC comparative effectiveness study, including effect size.
- Specific standalone performance results for the algorithm.
- Type of ground truth used (e.g., pathology, outcomes).
- Sample size and ground truth establishment for the training set.
The document primarily focuses on software verification and general clinical validation conclusions (e.g., "All applicable safety and performance requirements are fulfilled," "Clinical data collected establishes the performance and safety"). It mentions an AI/ML algorithm for tumor segmentation but provides no details on its performance, training, or testing methodology beyond general statements.
Therefore, based solely on the provided text, it is not possible to answer your request for specific acceptance criteria and detailed proof of meeting those criteria. The document contains general statements about validation and verification but lacks the specific quantitative and methodological details needed to fill out your requested table and information points.
§ 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).