Brain Atrophy - Cross-Sectional with White-Matter Lesions

The picture below shows the setup for assessing brain atrophy at a single time-point (cross-sectionally) when there are white-matter (WM) lesions present. For this, you need both a T1-weighted image and a FLAIR image.

Setup for cross-sectional brain atrophy assessment

The T1-weighted image should, ideally, have been acquired using a 3-D (not multi-slice) pulse sequence.
  1. Load the T1-weighted image in the first input image selection panel. In the example above, this is called "T1Weighted.nii". Load the FLAIR image in the second input image selection panel. In the example above, this is called "FLAIR.nii".

  2. Selecting whether the T1-weighted image is multislice or 3D acquired. If the T1-weighted image was acquired multi-slice (with slice selection), rather than 3-D (with the slice dimension being phase-encoded), then select this option.

  3. Leave the The Markov Random Field regularisation strength slider slider at its default value of 5. This should not need to be changed.

  4. Select Button to select automatic lesion segmentation. Jim has been trained to segment WM lesions using a selection of images from different MR scanners with variations in pulse sequence. However, if your images have unusual contrast (particularly the FLAIR images) then you may need to change the "lesion threshold fraction" setting from its default value of 0.5. Either move the slider, or type in a value between 0 and 1.

    Lesion threshold fraction to alter the WM lesion load

    Using lower values will increase the WM lesion load, and higher values will decrease it.

    If you trained the lesion segmentation using your own data, you will need to select Specifying that you have trained your own region stats, and set the file containing the trained image region statistics using: Specifying that lesion region statistics file.

  5. Set the base name and folder for the output images.

Now press the Button to start the atrophy analysis button to start the analysis, which will take some time. When the analysis is complete, you will see a pop-up message showing the results:

Results for cross-sectional brain atrophy assessment with lesions

These results show: To make a permanent record of these results, you can: For an input T1-weighted image called "T1Weighted.nii", and FLAIR image called "FLAIR.nii", and a base name of "Test", these output images will be created in the selected folder:

Lesion review

Also produced is an ROI file called (in this example) "rFLAIR.roi", where the ROIs outline the segmented lesions on every image slice. These ROIs can be reviewed by loading them onto either rFLAIR.nii or bcrFLAIR.nii, to ensure that the outlining of lesions is satisfactory. If the outlining is not satisfactory, you can either:

Note: when the analysis is repeated like this, as long as the output images initally produced are not removed, and the output images Basename is not changed, then the analysis will run in a much shorter time, since intermediate registration steps can be skipped.

The procedure for cross-sectional atrophy assessment when hyperintense lesions are present (after the registration steps), is summarised in the flow-chart below.

Flow chart for cross-sectional brain atrophy assessment with lesions

The Expectation-Maximization first classifies the tissue. Lesions are then segmented using a lesion intensity model, before the E-M classifier is run again after excluding lesion pixels. The location of the lesions (GM or WM) is determined by examining their position relative to the prior tissue class probabilities. The GM and WM lesion volumes are added to the E-M segmented GM and WM volumes when reporting the final tissue volumes.

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