Longitudinal Pipeline

Longitudinal version of UBO Detector is only available in commandline at the moment.

Data Preparation

The longitudinal pipeline required a slightly different data preparation. Specifically, T1 and FLAIR data need to be renamed as ID_tp1_*.nii.gz, ID_tp2_*.nii.gz, where tp is an abbreviation of time point, tp1 means the first time point, and tp2 is the second time point, etc. These data should be saved in a similar folder structure as that described for cross-sectional UBO Detector processing:

../_images/UBO_Detector_Figure_1.png

Running Longitudinal Pipeline

Step 1: Add path in MATLAB. addpath (‘/path_to_CNS/WMH_extraction/WMHextraction_long’);

Step 2: Run longitudinal pipeline. WMHextraction_long_paired (studyFolder, Ntp, spm12path, dartelTemplate, k, PVWMH_magnitude, coregExcldList, segExcldList, classifier, ageRange, probThr, outputFormat);

where:

  • studyFolder is the path to the study folder
  • Ntp is the number of time points
  • spm12path is the path to SPM12
  • dartelTemplate is either ‘existing template’ or ‘creating template’
  • k is the k for kNN
  • PVWMH_magnitude is the distance (in mm) from lateral ventricles which defines periventricular and deep WMH
  • coregExcldList is the list of IDs who failed FLAIR-to-T1 coregistration, and will be excluded in future analyses. Use ‘’ to pass an empty list
  • segExcldList is the list of IDs who failed the T1 segmentation step, and will be excluded in future analyses. Use ‘’ to pass an empty list
  • classifier is either ‘built-in’ or ‘customised’
  • ageRange is either ‘lt55’, ‘65to75’, or ‘70to80’
  • probThr is the probability threshold to threshold WMH probability map
  • outputFormat is how you want to view the QC results, either ‘web’, ‘arch’, or ‘web&arch’.