Dynamic Contrast-Enhanced MRI (DCE-MRI) Analysis

Having set up your input and output images as described in the Introduction, you can now set up the quantification parameters for DCE-MRI.

Quantification Parameters
In the DCE-MRI Analysis tool, you will see:


You should set the following parameters to obtain quantitative values from the DCE-MRI analysis:

Further down you will also see:


In this section you setup for quantification from the pulse sequence. Set:

Arterial Input Function (AIF)

Arterial Input Function selection parameters

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

Analysis Type


First choose the model for the tissue response that you want to use:

Now choose whether you want to perform pixel-by-pixel analysis, or region of interest (ROI) analysis. You can either:

DCE-MRI Output Parametric Images
The DCE-MRI analysis produces either several output images, depending on the Analysis Type chosen. The output images will have the same base name, but with the output parameter name appended. These are: Note: that if you have chosen to perform semi-quantitative analysis, the iAUC values are the areas under the enhancement curves, while if you have chosen to calculate the contrast agent concentration, then the iAUC values will be the areas under the contrast agent concentration curves.

All models will also produce an RMSE (root-mean-square error) image, which is a measure of the goodness of fit. This is the 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.

What Happens When Fitting Fails?
Model fitting may be caused by several factors:

If you are performing ROI analysis, a fitting failure will result in an pop-up error message indicating the nature of the failure. If you are performing pixel-by-pixel analysis, any pixel where fitting 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.

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