[wullemom]

The bacling store is the area to which the graphics will be pasted. I assume that Your dataset contains thousends of images. This will result in a huge canvas, which cannot be handled by IDl. If you are just interested in a few images you should extarct them before using Tools/Geometry/Extract volumes and then go back to the display function.

[wullemom]

Hi,

We’ll email you details on how to upload the file to our ftp server.

[wullemom]

There might be two explanations:
1) the atd-values for a potential AIF-voxel are out of the expected range. In that case adjust min/max-values in the table below.
2) the data and therefore the atd-parameter maps are of low quality: Movement of the head, to high concentration of CA, low resolution, strong paramagnetic shift effect. If you like, you can send one dataset to us for inspection.

Please note: absolute quantification of perfusion parameters depends critically on the AIF. If it is only a little bit distorted you will obtain values which are far off from what you expected. For this reason we have designed a robust sequence with a very short TE just for the AIF slice (Rausch et al. MRI, 200x).

[wullemom]

Most probably you don’t have write-permission to this folder. BioMAP stores the information on scans and subjects in a seperate file (subject.dat and scan.dat) to shorten lengthy scanning procedures.

[wullemom]

The CTC does not need the AIF. It simply transform signal values to concentration values by calculating somthing like exp(-Signal/Signal0).

Perfusion analysis can just be done for data, which was already stored in the database.

The maps are indeed the same

[wullemom]

If you can see other icons you path settings should be OK. Are you working with UNIX or WINDOWS? If you want to change the settings you can also edit the uparsrc in your biomap directory e.g. ~.biomap on UNIX

[wullemom]

The unit of the TTP map is sec after steady state. The units for the other parameter maps are as expected:
MTT: sec
rCBV ml/100g
rCBF ml/100g/min

[wullemom]

You can read the values e.g. with the pixel scan function or draw ROIs und use the Roi/Statistics function.

If your values are off from the expected range, you should check the AIF. The AIF is defined either by the ROI-method or cluster analysis. The ROI method is very stable also for pure image quality.

See also these manual pages:

Absolute quantification of blood volume, blood flow and MTT is obtained in two steps. First the parameters of the GVF for pure vessel signal are selected. This can be achieved either manually or by using cluster analysis. The method can be chosen in FlowQuan parameter area.
? ROI: Use the pixels defined by ROI n. The ROI must be drawn manually in the window, which contains the raw data set. It is advised to draw very small ROIs, which contain only pure blood signal. However, it is possible to define ROIs for more than one vessel (e.g. right and left carotid artery and both vertebral arteries) and to merge them with ROI/Merge.
? CA: Perform a cluster analysis on the GpDF-maps and select the cluster with the largest signal amplitude. This function will perform a cluster analysis on the three parameters (height, width, delay). Cluster analysis can be employed for multivariate statistical analysis. It attempts to group similar samples of a population each characterized by a set of common variables. During computation of a cluster analysis, cluster centers are formed and each sample is assigned to one cluster. Clusters and cluster centers are arranged in order to minimize the distance between samples within one cluster and maximize the distance between different clusters. The distance is defined by a metric, which was Euclidean here. The maximum number of clusters that should be created can be defined in the dialog window. Moreover, limits for each parameter can be defined. Voxels, which are outside these limits are not taken into account for the computation. Usually three non-empty clusters were defined from the pixel parameters of the AIF-slice. The one containing the pixels from feeding arteries, was characterized by high amplitudes a, high values for s and early peak times p. The second cluster contained pixels from draining veins, characterized by a late peak time. The third cluster contained pixels from tissue or small vessels.
? Actual: Use the values of the parameter field
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