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Assembly Series

A tradition of convening thought leaders since 1953

McKelvey School of Engineering

Brown School

ESE Defense: Peiwang Liu

Monday, April 22 | 2:00 PM - 4:00 PM

Stephen F. & Camilla T. Brauer Hall, 3015
6548 Forest Park Pkwy, St. Louis, MO 63112, USA

Evaluating Neuroimaging Modalities in the A/T/N Framework: Single and Combined FDG-PET and T1-Weighted MRI for Alzheimer’s Diagnosis

Abstract: With the escalating prevalence of dementia, particularly Alzheimer's Disease (AD), the need for early and precise diagnostic techniques is rising. This study delves into the comparative efficacy of Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) and T1-weighted Magnetic Resonance Imaging (MRI) in diagnosing AD, where the integration of multimodal models is becoming a trend. Leveraging data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we employed linear Support Vector Machines (SVM) to assess the diagnostic potential of these modalities, both individually and in combination, within the AD continuum. Our analysis, under the A/T/N framework's 'N' category, reveals that FDG-PET consistently outperforms T1w-MRI across various stages of cognitive impairment. Contrary to expectations and previous studies that suggested enhanced diagnostic accuracy through the fusion of neuroimaging modalities—including CSF markers—our findings do not demonstrate a significant improvement in diagnostic performance from combining FDG-PET and MRI data. This outcome aligns with Narazani et al. (2022), challenging the prevailing assumption about the added value of multimodal data fusion in AD diagnosis. Through the interpretation of activation maps, our study further elucidates the distinct yet complementary roles of FDG-PET and MRI in highlighting the pathological underpinnings of AD, contributing to a nuanced understanding of neuroimaging biomarkers in clinical settings. Our research underscores the critical need for refined strategies in neuroimaging data integration, advocating for a more discerning application of single and multimodal approaches in the early detection of AD.

Event Type



McKelvey School of Engineering


Science & Technology

Electrical & Systems Engineering


Event Contact

Aaron Beagle | abeagle@wustl.edu

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