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2023 | OriginalPaper | Buchkapitel

A Platform for the Radiomic Analysis of Brain FDG PET Images: Detecting Alzheimer’s Disease

verfasst von : Ramin Rasi, Albert Guvenis

Erschienen in: Bioinformatics and Biomedical Engineering

Verlag: Springer Nature Switzerland

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Abstract

The objective of this work is to present a radiomics-based platform (RAB-PET) and method to detect Alzheimer’s disease (AD) non-invasively using 18FDG-PET images. Radiomic analysis allows the identification of regional features that serve to predict the presence or characteristics of diseases using images as data. We first, used the FastSurfer a deep learning-based toolbox to segment the whole brain into 95 classes by the utilization of the DKT-atlas. Then the PyRadiomics toolbox was used to extract features from 18FDG-PET scans. After preprocessing, the features were subject to a selection process by making use of eight different methods, namely, ANOVA, PCA, Chi-square, LASSO, Recursive Feature Elimination (RFE), Feature Importance (FI), Mutual Information (MI), and Recursive Feature Addition (RFA). Finally, in order to classify the selected features by feature selection methods, we implemented nine different classifier methods, namely, GradientBoosting (GB), RandomForest (RF), DecisionTree (DT), GaussianNB (GNB), GaussianProcess (GP), MLP, QuadraticDiscriminantAnalysis (QDA), AdaBoost (AB), and KNeighbors (KNN) on selected feature subsets. All data (scans and clinical examination results) were obtained from the AD Neuroimaging Initiative (ADNI) database. The RF classifier with 100 iterations on features obtained with the LASSO algorithm yielded an area under the curve of AUC = 0.976 with a 95% confidence interval of 0.93–0.98 based on 30% independent test data. We conclude that a platform for radiomic analysis can serve as a potential method for deducing accurate information on brain diseases such as Alzheimer’s disease non-invasively using 18FDG-PET images. Further studies are underway to extend this work by studying the association between the set of features and several characteristics of the Alzheimer’s disease.

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Titel: A Platform for the Radiomic Analysis of Brain FDG PET Images: Detecting Alzheimer’s Disease
verfasst von: Ramin Rasi
Albert Guvenis
Verlag: Springer Nature Switzerland
Buch: Bioinformatics and Biomedical Engineering
Print ISBN: 978-3-031-34952-2

Electronic ISBN: 978-3-031-34953-9

Copyright-Jahr: 2023
DOI: https://doi.org/10.1007/978-3-031-34953-9_19

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