Using CT Data to Improve the Quantitative Analysis of 18F-FBB PET Neuroimages

• Published in: Frontiers in aging neuroscience Vol. 10; p. 158
• Main Authors: Segovia, Fermín, Sánchez-Vañó, Raquel, Górriz, Juan M., Ramírez, Javier, Sopena-Novales, Pablo, Testart Dardel, Nathalie, Rodríguez-Fernández, Antonio, Gómez-Río, Manuel
• Format: Journal Article
• Language: English
• Published: Lausanne Frontiers Research Foundation 07.06.2018; Frontiers Media S.A
• Subjects: Alzheimer's disease; Automation; Cognitive ability; Computed tomography; Data acquisition; Dementia; florbetaben; Hospitals; Image processing; Medical imaging; multivariate analysis; Neurodegeneration; Neuroimaging; Neuroscience; NMR; Nuclear magnetic resonance; Nuclear medicine; Patients; Positron emission tomography; Quantitative analysis; Substantia grisea; support vector machine; Tomography; United States > US; Pittsburgh Pennsylvania; Spain
• ISSN: 1663-4365; 1663-4365
• DOI: 10.3389/fnagi.2018.00158

18F-FBB PET is a neuroimaging modality that is been increasingly used to assess brain amyloid deposits in potential patients with Alzheimer’s disease (AD). In this work we analyze the usefulness of these data to distinguish between AD and non-AD patients. A dataset with 18F-FBB PET brain images from 94 subjects diagnosed with AD and other disorders was evaluated by means multiple analyses based on t-test, ANOVA, Fisher Discriminant Analysis and Support Vector Machine (SVM) classification. In addition, we propose to calculate amyloid standardized uptake values (SUVs) using only gray-matter voxels, which can be estimated using Computed Tomography (CT) images. This approach allows assessing potential brain amyloid deposits along with the gray matter loss and takes advantage of the structural information provided by most of the scanners used for PET examination, which allow simultaneous PET and CT data acquisition. The results obtained in this work suggest that SUVs calculated by means of the proposed method allow AD and non-AD subjects to be more effectively differentiated than using SUVs calculated with standard approaches.