Radiomics-enhanced 18F-AV45 PET/MRI for integrative assessment and centiloid estimation of amyloid-β burden in Alzheimer’s disease

Abstract 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 18 F-florbetapir positron emission tomography/magnetic resonance imaging ( 18 F-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 ( 18 F-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 18 F-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 18 F-AV45 PET/MRI enabled quantitative Aβ evaluation in AD. Radiomics-enhanced 18 F-AV45 PET/MRI provided a noninvasive and interpretable assessment to improve clinical confidence. Radiomics-enhanced 18 F-AV45 PET/MRI allowed Centiloid estimation without specialized platforms for wider clinical use.

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Journal
European Radiology Experimental
Published
2026-06-18
DOI
https://doi.org/10.1186/s41747-026-00766-3
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
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article

Radiomics-enhanced 18F-AV45 PET/MRI for integrative assessment and centiloid estimation of amyloid-β burden in Alzheimer’s disease

Xinwei Cheng, Jun Zhao, Jianzhou Zhang, Weilun Wang et al.
European Radiology Experimental
Dementia and Cognitive Impairment Research
article

Radiomics-enhanced 18F-AV45 PET/MRI for integrative assessment and centiloid estimation of amyloid-β burden in Alzheimer’s disease

Xinwei Cheng, Jun Zhao, Jianzhou Zhang, Weilun Wang, Zirong Zhou, Na Qi, Yingkang Lin, Zengbei Yuan, Xing Chen
article en

Abstract

Abstract 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 18 F-florbetapir positron emission tomography/magnetic resonance imaging ( 18 F-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 ( 18 F-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 18 F-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 18 F-AV45 PET/MRI enabled quantitative Aβ evaluation in AD. Radiomics-enhanced 18 F-AV45 PET/MRI provided a noninvasive and interpretable assessment to improve clinical confidence. Radiomics-enhanced 18 F-AV45 PET/MRI allowed Centiloid estimation without specialized platforms for wider clinical use.

European Radiology ExperimentalVol. 10(1)
Guangdong Work Injury Rehabilitation Hospital (CN), Shanghai East Hospital (CN)
Reduced inequalities
Openalex Percentile: Top 6%
Dementia and Cognitive Impairment Research
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