PET/MRI multimodality imaging to evaluate changes in glymphatic system function and biomarkers of Alzheimer's disease.
Hidehiko OkazawaMunenobu NogamiShota IshidaAkira MakinoTetsuya MoriYasushi KiyonoMasamichi IkawaPublished in: Scientific reports (2024)
The glymphatic system is considered to play a pivotal role in the clearance of disease-causing proteins in neurodegenerative diseases. This study employed MR diffusion tensor imaging (DTI) to evaluate glymphatic system function and its correlation with brain amyloid accumulation levels measured using [ 11 C]Pittsburgh compound-B (PiB) PET/MRI. Fifty-six patients with mild cognitive impairment and early Alzheimer's disease (AD: 70 ± 11 y) underwent [ 11 C]PiB PET/MRI to assess amyloid deposition and were compared with 27 age-matched cognitively normal volunteers (CN: 69 ± 10y). All participants were evaluated for cognitive function using the Mini Mental State Examination (MMSE) before [ 11 C]PiB PET/MRI. DTI images were acquired during the PET/MRI scan with several other MR sequences. The DTI analysis along the perivascular space index (DTI-ALPS index) was calculated to estimate the functional activity of the glymphatic system. Centiloid scale was applied to quantify amyloid deposition levels from [ 11 C]PiB PET images. All patients in the AD group showed positive [ 11 C]PiB accumulation, whereas all CN participants were negative. ALPS-index for all subjects linearly correlated with PiB centiloid, MMSE scores, and hippocampal volume. The correlation between the ALPS-index and PiB accumulation was more pronounced than with any other biomarkers. These findings suggest that glymphatic system dysfunction is a significant factor in the early stages of Alzheimer's disease.
Keyphrases
- pet imaging
- contrast enhanced
- computed tomography
- positron emission tomography
- mild cognitive impairment
- cognitive decline
- magnetic resonance imaging
- pet ct
- diffusion weighted imaging
- white matter
- magnetic resonance
- deep learning
- high resolution
- ejection fraction
- newly diagnosed
- convolutional neural network
- squamous cell carcinoma
- mental health
- optical coherence tomography
- mass spectrometry
- photodynamic therapy
- patient reported
- machine learning
- blood brain barrier