Partial volume correction for arterial spin labeling sequences in magnetic resonance imaging. 3DSlicer extension

Arterial spin labeling is becoming an increasingly popular method for evaluating the cerebral blood flow. However, one of the major limitations of arterial spin labeling (and other perfusion assessment methods like PET) is the partial volume effect, by which each voxel of the image contains a mixture of tissues due to the low spatial resolution of ASL. Partial volume correction is required to retrieve the perfusion contribution of each of these tissues, which is important in the study of neurodegenerative diseases such as Alzheimer’s disease. A new partial volume correction method (3D weighted least squares) based on an existing state-of-the-art method (Asllani’s algorithm) is presented in this work. The new algorithm improves the previous algorithm by operating in a 3D way instead of a 2D way and including a weighting to the regression problem as a function of the distance between the voxels.The new method was tested over simulated cerebral perfusion images, giving better results than the Asllani’s algorithm. The algorithm was also implemented as a graphical user interface extension for the open source platform 3DSlicer. This extension automates all the correction process and allows the researchers processing the ASL images rapidly and easily. Using this extension, a real perfusion study was conducted to compare the cerebral perfusion between Alzheimer and control groups in resting state. Alzheimer group showed a significantly lower perfusion in the thalamus, caudate nucleus, hippocampus and cuneus. These regions have been reported in the literature to present atrophies in Alzheimer subjects and are involved in cognitive functions that are negatively affected by the disease. These results provide further validation for the 3DWLS as a suitable correction method and for the extension as a useful research tool.Ingeniería Biomédic