# CEST MRI Processing Pipeline in Pilot Study of Alzheimer's Disease Patients

## TL;DR

A new MRI processing pipeline was developed and tested to detect differences in brain imaging between Alzheimer's patients and healthy individuals.

## Contribution

A novel CEST MRI processing pipeline was created and applied to a pilot study comparing Alzheimer's disease and cognitively normal subjects.

## Key findings

- Motion correction improved CEST image quality and reduced artifacts.
- Cortical and white matter regions showed significant MTRasym differences between cognitively impaired and normal groups.
- Lower mean MTRasym and Lorentzian amplitudes were observed in Alzheimer's patients compared to controls.

## Abstract

To develop a processing pipeline combining neuroimaging analysis tools with CEST postprocessing and utilize it in a pilot study probing differences between cognitively impaired (CI) Alzheimer's disease (AD) patients and cognitively normal (CN) individuals.

Eight subjects (4 biomarker confirmed CI with underlying AD and 4 CN) were scanned on a 3T MRI scanner. The processing pipeline included rigid motion correction and co‐registration of the CEST images with the 3D T1w images using Advanced Normalization Tools (ANTs). MTRasym maps at 1 ppm, 2 ppm and 3.5 ppm were generated on a voxel‐by‐voxel basis. Each subject's 3D T1w images were processed with FreeSurfer to generate brain region specific ROIs, and the MTRasym values were averaged over the generated ROIs. In addition, a 6‐pool Lorentzian multi‐peak model was fitted to averaged Z‐spectrum data per ROI. Between‐group (CI vs. CN) CEST effects were evaluated using Mann–Whitney U tests.

Motion correction reduced artifacts and visually improved CEST results. Multiple cortical and white matter ROIs showed differences in MTRasym values between CI and CN groups (p < 0.05). Overall, the mean MTRasym and Lorentzian amplitudes were lower in the CI than in the CN group.

Our proposed pipeline enables robust data analysis using either MTRasym or multi‐pool Lorentzian quantification approaches. The results suggest feasibility for detecting CEST differences between CI and CN groups in brain regions previously implicated in AD, motivating future validation in larger cohorts.