Automatic determination of glymphatic flow with the DTI-ALPS-index along the principal axis system in native imaging space corrects for head and fibre orientation

Abstract
This work aims to decrease the dependence of the DTI-ALPS-index on the head and fibre orientation, calculating the DTI-ALPS-index along the principal diffusion directions. It is investigated if an automated ROI placement could lead to a more robust DTI-ALPS-index without native data registration. 

We calculated the DTI-ALPS-index along the principal diffusion directions (ALPS-PAS) and compared it with the original DTI-ALPS-index along the scanner’s laboratory frame (ALPS-LAB) using simulation and in vivo measurements. To calculate the DTI-ALPS-index in native space, we developed a novel calculation algorithm for an automatic ROI placement technique and compared it to a manual ROI placement and existing atlas-based ROI placement.  Further, a whole-brain DTI-ALPS-map was introduced.  

Simulations demonstrated the dependence of the DTI-ALPS-index on the head and fibre orientation and the in vivo measurements yielded higher ALPS-PAS than ALPS-LAB.  The novel ROI placement led to a more robust DTI-ALPS-index evaluation in meaningful regions than the manual ROI placement. The DTI-ALPS map indicated an anisotropy between the second and third principal diffusion direction in other brain areas besides the ALPS-fibre-regions. 

Conclusion:
ALPS-PAS eliminates the head and fibre orientation dependence, which enables the calculation in the native data space without registration of the acquired data. The automatic ROI placement reduces the operator dependent ROI selection, which could be beneficial for longitudinal studies.

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Preprint Notice

This preprint corresponds to the article published in Magnetic Resonance in Medicine:

Ali Ajouz et al. (2025) 
“Automatic determination of glymphatic flow with the DTI-ALPS-index along the principal axis system in native imaging space corrects for head and fiber orientation”  
Magnetic Resonance in Medicine (Wiley, 2025).  
DOI: https://doi.org/10.1002/mrm.70082

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