European radiology experimental · 2026
Radiomics-enhanced 18F-AV45 PET/MRI for integrative assessment and centiloid estimation of amyloid-β burden in Alzheimer's disease.
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Yuan Zengbei, Zhang Jianzhou, Zhou Zirong, Chen Xing, Qi Na, Wang Weilun, Cheng Xinwei, Lin Yingkang, Zhao Jun
Аннотация
OBJECTIVE: Reliable assessment of cerebral amyloid-β (Aβ) deposition is essential for the diagnosis and management of Alzheimer's disease (AD). This study aimed to evaluate the feasibility of integrating radiomics-enhanced 18F-florbetapir positron emission tomography/magnetic resonance imaging (18F-AV45 PET/MRI) features for Aβ status evaluation and to further explore their potential for continuous Centiloid prediction in AD.
MATERIALS AND METHODS: Ninety-four subjects who underwent (18F-AV45 PET/MRI (60 Aβ-positive, 34 Aβ-negative) were retrospectively included. Standardized uptake value ratio (SUVr) features were extracted from seven cortical regions (frontal, temporal, parietal, occipital, insular, cingulate, and white matter), and corresponding T1-weighted images' radiomics features were computed. Three feature sets (PET, radiomics, and combined) were analyzed using logistic regression (LR), k-nearest neighbor (kNN), and linear discriminant analysis (LDA) with 10-fold cross-validation. The best performing model was further interpreted using SHapley Additive exPlanations (SHAP) analysis. Additionally, Centiloid regression was performed using random forest, ElasticNet, and ExtraTrees regressors.
RESULTS: The combined feature achieved the best performance with the LR model, with area under the receiver operating characteristic curve = 0.9373, accuracy = 0.8723, F1-score = 0.898). SHAP analysis identified biologically meaningful features derived from both radiomics and PET modalities, showing clear inter-group separation. In Centiloid regression, the ExtraTrees model achieved strong agreement with measured values.
CONCLUSION: This framework provides an interpretable and quantitative solution for amyloid evaluation, enabling both categorical Aβ status discrimination and continuous Centiloid estimation from routine PET/MRI data. This approach represents a proof-of-concept for supporting 18F-AV45 PET-based assessment in AD.
RELEVANCE STATEMENT: This study demonstrates that radiomics-enhanced PET/MR features can reliably predict both Aβ status and Centiloid values without specialized processing platforms, offering a clinically deployable, standardized, and interpretable approach to improve AD diagnosis and monitoring.
KEY POINTS: Radiomics-enhanced 18F-AV45 PET/MRI enabled quantitative Aβ evaluation in AD. Radiomics-enhanced 18F-AV45 PET/MRI provided a noninvasive and interpretable assessment to improve clinical confidence. Radiomics-enhanced 18F-AV45 PET/MRI allowed Centiloid estimation without specialized platforms for wider clinical use.
MATERIALS AND METHODS: Ninety-four subjects who underwent (18F-AV45 PET/MRI (60 Aβ-positive, 34 Aβ-negative) were retrospectively included. Standardized uptake value ratio (SUVr) features were extracted from seven cortical regions (frontal, temporal, parietal, occipital, insular, cingulate, and white matter), and corresponding T1-weighted images' radiomics features were computed. Three feature sets (PET, radiomics, and combined) were analyzed using logistic regression (LR), k-nearest neighbor (kNN), and linear discriminant analysis (LDA) with 10-fold cross-validation. The best performing model was further interpreted using SHapley Additive exPlanations (SHAP) analysis. Additionally, Centiloid regression was performed using random forest, ElasticNet, and ExtraTrees regressors.
RESULTS: The combined feature achieved the best performance with the LR model, with area under the receiver operating characteristic curve = 0.9373, accuracy = 0.8723, F1-score = 0.898). SHAP analysis identified biologically meaningful features derived from both radiomics and PET modalities, showing clear inter-group separation. In Centiloid regression, the ExtraTrees model achieved strong agreement with measured values.
CONCLUSION: This framework provides an interpretable and quantitative solution for amyloid evaluation, enabling both categorical Aβ status discrimination and continuous Centiloid estimation from routine PET/MRI data. This approach represents a proof-of-concept for supporting 18F-AV45 PET-based assessment in AD.
RELEVANCE STATEMENT: This study demonstrates that radiomics-enhanced PET/MR features can reliably predict both Aβ status and Centiloid values without specialized processing platforms, offering a clinically deployable, standardized, and interpretable approach to improve AD diagnosis and monitoring.
KEY POINTS: Radiomics-enhanced 18F-AV45 PET/MRI enabled quantitative Aβ evaluation in AD. Radiomics-enhanced 18F-AV45 PET/MRI provided a noninvasive and interpretable assessment to improve clinical confidence. Radiomics-enhanced 18F-AV45 PET/MRI allowed Centiloid estimation without specialized platforms for wider clinical use.