Related Experiment Video
Updated: May 1, 2026
Hybrid PET/MRI Imaging of Alzheimer's Disease Based on 18F-AV-1451
Published on: April 18, 2025
Multimodal MRI-based Imputation of the Aβ+ in Early Mild Cognitive Impairment
Duygu Tosun1, Sarang Joshi2, Michael W Weiner1
1Department of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA USA.
Objective:
To identify brain atrophy from structural-MRI and cerebral blood flow(CBF) patterns from arterial spin labeling perfusion-MRI that are best predictors of the Aβ-burden, measured as composite 18F-AV45-PET uptake, in individuals with early mild cognitive impairment(MCI). Furthermore, to assess the relative importance of imaging modalities in classification of Aβ+/Aβ- early mild cognitive impairment.
Methods:
Sixty-seven ADNI-GO/2 participants with early-MCI were included. Voxel-wise anatomical shape variation measures were computed by estimating the initial diffeomorphic mapping momenta from an unbiased control template. CBF measures normalized to average motor cortex CBF were mapped onto the template space. Using partial least squares regression, we identified the structural and CBF signatures of Aβ after accounting for normal cofounding effects of age, sex, and education.
Results:
18F-AV45-positive early-MCIs could be identified with 83% classification accuracy, 87% positive predictive value, and 84% negative predictive value by multidisciplinary classifiers combining demographics data, ApoE ε4-genotype, and a multimodal MRI-based Aβ score.
Interpretation:
Multimodal-MRI can be used to predict the amyloid status of early-MCI individuals. MRI is a very attractive candidate for the identification of inexpensive and non-invasive surrogate biomarkers of Aβ deposition. Our approach is expected to have value for the identification of individuals likely to be Aβ+ in circumstances where cost or logistical problems prevent Aβ detection using cerebrospinal fluid analysis or Aβ-PET. This can also be used in clinical settings and clinical trials, aiding subject recruitment and evaluation of treatment efficacy. Imputation of the Aβ-positivity status could also complement Aβ-PET by identifying individuals who would benefit the most from this assessment.
Insights
Multimodal MRI accurately predicts amyloid positivity in early mild cognitive impairment (MCI). This non-invasive approach identifies individuals likely to have amyloid deposition, aiding clinical trials and diagnosis.
Area of Science:
- Neuroimaging
- Biomarker Discovery
- Alzheimer's Disease Research
Background:
- Early mild cognitive impairment (MCI) diagnosis is crucial for timely intervention in Alzheimer's disease (AD).
- Amyloid-beta (Aβ) deposition is a key pathological hallmark of AD, detectable via PET imaging.
- Non-invasive biomarkers for Aβ detection are needed to complement or replace costly and less accessible methods.
Purpose of the Study:
- To identify structural MRI and cerebral blood flow (CBF) patterns predicting Aβ burden in early MCI.
- To assess the predictive power of multimodal MRI for classifying Aβ-positive (Aβ+) versus Aβ-negative (Aβ-) early MCI.
- To evaluate the relative importance of different imaging modalities in Aβ status classification.
Main Methods:
- Sixty-seven participants with early MCI from ADNI-GO/2 were analyzed.
- Voxel-wise anatomical shape variation and CBF measures were computed using MRI.
- Partial least squares regression identified structural and CBF signatures of Aβ, controlling for age, sex, and education.
Main Results:
- A multimodal MRI-based Aβ score, combined with demographics and ApoE ε4 genotype, achieved 83% classification accuracy for Aβ+ early MCI.
- The classifier demonstrated high positive predictive value (87%) and negative predictive value (84%).
- Structural and CBF patterns from MRI effectively served as predictors for Aβ status.
Conclusions:
- Multimodal MRI can reliably predict amyloid status in individuals with early MCI.
- MRI offers a cost-effective and non-invasive surrogate biomarker for Aβ deposition.
- This approach can aid clinical trial recruitment, subject evaluation, and identify individuals who would benefit most from Aβ-PET assessment.
