Sensitivity of unconstrained quantitative magnetization transfer MRI to Amyloid burden in preclinical Alzheimer's disease.
Andrew MaoSebastian FlassbeckElisa MarchettoArjun V MasurkarHenry RusinekJakob AssländerPublished in: medRxiv : the preprint server for health sciences (2024)
Magnetization transfer MRI is sensitive to semi-solid macromolecules, including amyloid beta, and has previously been used to discriminate Alzheimer's disease (AD) patients from controls. Here, we fit an unconstrained 2-pool quantitative MT (qMT) model, i.e., without constraints on the longitudinal relaxation rate R 1 s of semi-solids, and investigate the sensitivity of the estimated parameters to amyloid accumulation in preclinical subjects. We scanned 15 cognitively normal volunteers, of which 9 were amyloid positive by [ 18 F]Florbetaben PET. A 12 min hybrid-state qMT scan with an effective resolution of 1.24 mm isotropic and whole-brain coverage was acquired to estimate the unconstrained 2-pool qMT parameters. Group comparisons and correlations with Florbetaben PET standardized uptake value ratios were analyzed at the lobar level. We find that the exchange rate and semi-solid pool's R 1 s were sensitive to the amyloid concentration, while morphometric measures of cortical thickness derived from structural MRI were not. Changes in the exchange rate are consistent with previous reports in clinical AD, while changes in R 1 s have not been reported previously as its value is typically constrained in the literature. Our results demonstrate that qMT MRI may be a promising surrogate marker of amyloid beta without the need for contrast agents or radiotracers.
Keyphrases
- contrast enhanced
- magnetic resonance imaging
- computed tomography
- diffusion weighted imaging
- cognitive decline
- magnetic resonance
- positron emission tomography
- systematic review
- newly diagnosed
- end stage renal disease
- high resolution
- prognostic factors
- single molecule
- multiple sclerosis
- bone marrow
- optical coherence tomography
- mesenchymal stem cells
- dual energy
- electronic health record