NordicNeuroLab nordicBrainEx Clinical Neuroimaging Software for Functional MRI Instruction Manual

VERSION 2.3
INSTRUCTIONS FOR USE
BRUKERVEILEDNING

nordicBrainEx Clinical Neuroimaging Software for Functional MRI

Workflow

1. Load data
   1.1 Import from disc
   1.2 Query/retrieve from PACS
   1.3 Select patient and series
   1.4 Right click to check type and settings
   1.5 License information
   1.6 Proceed

2. Verify coregistration

3. Result interaction
   3.1 Source data
   3.2 Derived data
   3.3 Right-click to interact
   3.4 Volume-of-interest tools
   3.5 Interact with BOLD, DTI, DSC and DCE
   3.6 BOLD activation maps
   3.7 Merge BOLD/DTI/DSC/DCE results with structural data for neuronavigation
   3.8 Load additional data

4. Right click in MPR to open slice viewer

5.  Report

6. Last data

7. Verifiser koregistrering

8.  Result interaction

9. Right click in MPR to open slice viewer

10. Report

INSTRUCTIONS FOR USE BRUKERVEILEDNING

Intended use
nordicBrainEx is an advanced visualization and processing software, with specific focus on providing algorithms designed to analyze functional MR data of the brain. The software runs on a standard “off-theshelf” PC workstation and can be used with data and images acquired through DICOM compliant imaging devices and modalities.
The software is intended to be used by medical personnel, such as radiologists or medical technicians, trained in the methods provided by the application.
In order to best accommodate this group of users, it is specifically designed to have an easy to use and streamlined workflow, as well as an intuitive graphical user interface.
Indications for use nordicBrainEx provides analysis and visualization capabilities of dynamic MRI data of the brain, presenting the derived properties and parameters in a clinically useful context.
BOLD: BOLD fMRI analysis is used to highlight small magnetic susceptibility changes in the human brain in areas with altered blood-flow resulting from neuronal activity.
DTI: Diffusion analysis is used to visualize local water diffusion properties from the analysis of diffusion-weighted MRI data. Fiber tracking utilizes the directional dependency of the diffusion to display the white matter structure in the brain.
DSC: Calculations of perfusion related parameters that provide information about the blood vessel structure and characteristics. Examples of such maps are blood volume, blood flow, time to peak, mean transit time and leakage.
DCE: Calculations of permeability parameters providing information about vascular permeability and intra- and extra vascular volume. Examples of such maps are area under the curve (AUC), volume transfer coefficient (Ktrans), rate constant (Kep), plasma volume (Vp), fractional volume (Ve), time to peak (TTP), peak, wash-in and wash-out.
System requirements nordicBrainEx is a 32-bit application and must run on a computer that meets the following minimum requirements:

• Operating system:

• Windows 7, 8.1 or 10.

• Hardware:

• Core i3 2.0 GHz processor (or equivalent).

• 4 GB RAM.

• 200 MB of free space on hard disk + 2 GB additional space for images (hard drive space should be added as image storage requirements increase).

• Monitor with 1280 x 1024 or higher resolution.
  Warning

• For US customers, federal law restricts this device to sale by or on the order of a physician or medical technician.

• The performance of the automatic co–reg- istration in nordicBrainEx depends on the inherent quality of the data and the degree of artefacts/motion in the dataset. Consequently, the co–registration may fail to properly correct for motion and artefacts. If the result deviates extremely from the expected result (+/- 10 mm or 10 degrees), nordicBrainEx will give you a warning, but it is important to be aware that the user always have to ensure the correctness of the co-registration.

• When nordicBrainEx visualizes BOLD statistical maps after the BOLD GLM analysis, the threshold is set to 40 % of the maximum t-value for each contrast. The user must make adjustments if needed. In general, setting the threshold too high may discard areas with neuronal activation, while setting the threshold too low may give the opposite result, too large areas shown with neuronal activity.

• The performance of the BOLD analysis is in general highly dependent on both the quality of the input data and the defined design. If the design has not been defined correctly with respect to the acquisition and stimulation protocol, the results may deviate from the expected outcome.

• The performance of the DTI analysis relies on the correct definition of the diffusion gradient configuration. If these settings have not been defined correctly with respect to the acquisition protocol, the results may deviate from the expected outcome.

• The performance of the fiber tracking analysis is in general highly dependent on both the quality of the input data and the limitations within the analysis. In particular, the analysis may fail to correctly reconstruct structures where diffusion pathways are overlapping (crossing/kissing). Care should therefore be taken when interpreting the results as the visualized fiber tracts may not correspond to real white matter structures.

• The vessel segmentation functionality is meant as an aid in identifying vessels in perfusion maps and no claims are made as to the accuracy of the method to truly identify vessels.

• The blood volume and blood flow maps in nordicBrainEx DSC perfusion analysis can be normalized based on an automatic segmentation of healthy tissue, both white and grey matter. This segmentation algorithm requires sufficient quality of the raw data to allow identification of the separate tissue classes. The resulting normalized maps should have values close to one in unaffected tissue when correctly estimated, and should be evaluated with care.

• The leakage correction, vessel segmentation, and normalization algorithms in DSC perfusion are all non-deterministic and will not necessarily provide identical output each time they are run. Their relative standard deviations are less than +/- 10%.

• The accuracy of distance and volume measurements depend on screen resolution and the resolution and voxel size of the dataset. Under normal conditions, the uncertainties of these parameters are less than 1mm and 2%, respectively.

• In DSC and DCE analysis, the user should verify the temporal resolution, because the value extracted from the DICOM header may be incorrect.

• Population arterial input function (AIF) is used for DCE perfusion analysis. Two pre-defined AIF curves (one with a sharper peak than other), based on approximated population data, are available. Select AIF-1 (one with the sharper peak) as the default option, if results are not satisfactory, data should be re-analyzed with AIF-2. DCE maps (Ktrans, Kep, Vp and Ve) are dependent on selection of AIF.

• When using user-defined AIF in DCE analysis, the shape of the curve must be verified by the user.

• Bolus arrival time could slightly differ in different regions of the brain, however for DSC and DCE analysis, mean bolus arrival time from all the voxels has been used. An option has been provided to modify the bolus arrival time.

• DCE maps are computed using extended kinetic Tofts model. Two options of signal conversion Delta SI and SPGR (Spoiled gradient echo sequences) are available with SPGR as the default option. Delta SI signal conversion should be used if results using SPGR are not satisfactory.

• Noise level should be verified before starting DCE analysis. Noise is set to manual by default for DCE module.

**** NordicNeuroLab AS, Mølllendalsveien 1, N-5009 Bergen, Norway,
E-mail: info@nordicneurolab.com,
www.nordicneurolab.com

References

• NordicNeuroLab | User friendly, plug-and-play fMRi solution

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