Brain Perfusion Analysis

Having set up your input and output images as described in the Introduction, you can now set up the quantification parameters for brain perfusion. In the Perfusion Analysis tool, you will see:

Quantification parameters

First, set the imaging modality by selecting one of:

• if you are working with Magnetic Resonance Imaging (MRI) data.
• if you are working with X-ray Computed Tomography (X-ray CT) data.

This determines which quantification parameters should be set.

It is not necessary to set the quantification parameters if you want semi-quantitative analysis to be performed. Semi-quantitative analysis will allow you to obtain relative perfusion parameters, not absolute cerebral blood flow (CBF) and cerebral blood volume (CBV). However, the mean transit time (MTT) is truly quantitative regardless of the settings of these parameters. Regardless of the quantification parameters, the time-to-peak (TTP) is an assessment of the time to the peak of contrast concentration, which may be useful for evaluating the delay in arrival.

Note: it is very difficult to obtain the values you need to enter for true quantification. These values depend very much on your pulse sequence and contrast agent, and Xinapse Systems does not, in general, recommend that you try to obtain quantitative perfusion parameters.

Now set the following parameters, if applicable:

• Scan TE (MRI data only). The scan is assumed to be T₂ or T₂*-weighted. For quantification, enter the correct echo time.
• Arterial relaxivity (relaxivity of the contrast agent for large vessels) (MRI data only). This is the slope of the plot of R₂* versus concentration of contrast agent in the blood plasma in the large vessels. Needed for quantification, otherwise leave as 1.0.
• Tissue relaxivity (relaxivity of the contrast agent for the capillary bed) (MRI data only). This is the slope of the plot of R₂* versus concentration of contrast agent in the blood plasma in the capillaries. Needed for quantification, otherwise leave as 1.0.
• Arterial haematocrit. The haematocrit in large vessels. Needed for quantification, otherwise leave as 0.45.
• Tissue haematocrit. The haematocrit in the capillary bed. Needed for quantification, otherwise leave as 0.45.
• SVD threshold. This affects the sensitivity of the analysis to noise and pseudo-random variation in the input images. Increasing this value will make the analysis more immune to noise, at the expense of bias in the quantification. The default of 40% should be fine for most images.

Arterial Input Function (AIF)

To obtain an arterial input function (the concentration of contrast agent in an artery that feeds the brain), you must set the following:

• The time at which contrast agent first appears in the feeding artery. If you cannot see a feeding artery and are obtaining the AIF by some other means, then this should be the time at which the image first changes in intensity as the contrast arrives in the tissue. By selecting from , you can specify this either as:
• The time at which contrast first appears (the first image is acquired at t=0).
• The scan number at which contrast first appears (the first scan is numbered 1).

Enter one of these. You can graphically confirm the arrival time using the Roaming Response dialog.

• You may optionally enter the time at which the series of images is truncated for the purposes of analysis using . Images after this time will not be used as part of dataset for the analysis. Analysis will proceed as if the data after this time point has not been acquired. By selecting from , you can specify this either as:
• The time at which to truncate the data set, or

• The scan number at which to truncate the data set. Enter one of these, or leave the field blank to use the whole dataset. You can graphically confirm the time of truncation using the Roaming Response dialog.

• Any lag from the measured arterial input function to the actual arterial input feeding directly into the tissue. This is specified as a number of frames (time points) of lag. Change the AIF lag using the AIF lag spinner.

  

  The text to the right of the spinner explains the meaning of the lag value you set.

• Choose how you want to obtain the AIF. You can:

  • Manually draw round one or more feeding arteries to produce a set of regions of interest (ROIs). In this case you can produce an ROI file that contains one or more ROIs drawn at one particular time point. This same set of ROIs will be used for all time points to obtain the AIF. Alternatively, you can define a set of ROIs at one time point, then copy and paste them to the same slice location for all time points, and manually adjust the position to account for patient movement during the scan. If you do this, the tool will expect to find a set of ROIs at every time point, and will given an error if it does not.

  Select the ROI file used for the AIF by pressing the button, or type the name into the text field:

  

  • Use a predefined AIF. You can read the values of the AIF from a file that contains a list of concentration of contrast agent values. The file must contain two columns of numbers:

    • The first column is the time at which the concentration of contrast agent ([Gd]) is measured.
    • The second column contains the blood plasma concentration values (moles/L).

    Whitespace or a comma (",") should separate the two columns.

    Note: the format required for the AIF file has changed between Version 6 of and Version 7 of Jim. The first column (time values) is now used. The onset of the arterial input function is taken to occur at the first time point where the concentration value first rises above zero. This time point (after taking account of any tissue lag that you input) is taken to coincide with the time that you specify for contrast arrival. The time between measures of the concentration may now be unevenly-spaced and does not have to match that of the input images. The pre-defined AIF is automatically resampled to the required time-base of the input images.

  The Perfusion tool will output such a file for every analysis it performs, which will give you an example of what is needed. For semi-quantitative analysis you just need values that are proportional to the concentration of contrast agent in the artery. Select the file used for the predefined AIF by pressing the button, or type the name into the text field:

  

  • Automatic AIF finding - Jim finds the pixels that have AIF-like characteristics. Note: this option is not available for X-ray CT images.

  • First, Jim makes as sweep of the whole image and selects pixels that have the largest intensity change. The number of pixels selected is set in the "No. of candidate pixels" spinner.

    

    Typically this would be set to around 1% to 5% of the total number of pixels in the image. Setting a smaller number here will speed up finding of the AIF, but may cause the tool not to select the best AIF pixels.

  • Next, these candidate pixels are searched for pixels that have the most AIF-like characteristics. The final number of pixels used to define the AIF is set in the "No. of pixels" spinner.

    

    AIF-like characteristics are: a large transient signal change occurring shortly after contrast injection.

  You can visualise the pixels that are have been found by auto-AIF by selecting:

  

  Each pixel found is outlined by a Rectangular ROI and written to an ROI file. The name of the ROI file is constructed from the output image base name that you set, with the suffix AutoAIF.roi.

  Check the "Show AIF graph" check-box if you would like a window to pop up showing you the AIF that is being used in the perfusion analysis.

Brain Perfusion Output Parametric Images

The Brain Perfusion analysis produces five output images, that have the same base name, but have the output parameter name appended. These are:

• CBF. Cerebral blood flow, with units of mls blood / 100g tissue / minute.
• CBV. Cerebral blood volume, with units that indicate the blood volume as a percentage of the total tissue volume.
• MTT. The mean transit time, in seconds.
• TTP. The time from contrast arrival to the peak in capillary concentration, in seconds.
• RMSE. A measure of the goodness of fit. This root-mean-square of the residuals between the fitted curve and the time-series data.

These output images are in floating-point format, and can be viewed using Jim. The output images will be of the same image type as the first input image.

Example output images from the Brain Perfusion Tool.

Cerebral Blood Flow	Cerebral Blood Volume	Mean Transit Time	Time-to-Peak

What Happens When Fitting Fails?

Perfusion analysis failure may be caused by several factors:

• The data are too noisy to perform an accurate fit.
• The data are corrupted by artefacts.
• The model is a poor match to the data.

Any pixel where perfusion analysis fails will have a value in all output images which is either zero, or NaN (not-a-number). Which of these two is written to the images is controlled by a setting in the user preferences.