Optimizing cutoffs for clinical interpretation of brain amyloid status using PET/MRI: a multisite study
Year: 2026
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Amyloid-β PET (Aβ-PET) imaging is playing an increasingly important role in the diagnosis and treatment of Alzheimer's Disease (AD). The Centiloid (CL) scale has been developed to standardize the measurements of Aβ PET imaging. Previous CL threshold settings were based on PET/CT, while our team's preliminary study found that CL values from PET/MRI are higher than those from PET/CT. Therefore, there is an urgent need to establish clinical interpretation cutoffs for Aβ status via PET/MRI to facilitate application in clinical practice. METHODS: The clinical performance of Aβ PET/MRI and cerebrospinal fluid biomarkers were evaluated in a multisite cohort of 720 participants. Aβ-PET scans were visually read and quantified using CL method. A two-cutoff approach identified thresholds maintaining > 90% sensitivity/specificity and ≤ 20% intermediate cases, selected by maximal Youden index. Group comparisons of cerebrospinal fluid biomarkers and cognition used generalized linear models adjusted for age and sex. RESULTS: The two-cutoff approach categorized Aβ-PET status as negative (CL ≤ 18.7), gray-zone (18.7-44.2), and positive (CL > 44.2). In Xuanwu cohort, it achieved an accuracy of 94.1%, a positive predictive value of 97.4%, a negative predictive value of 86.1%. In External cohort, the accuracy was 97.4%, positive predictive value 98.5%, negative predictive value 90.8%. Patients in the gray-zone group had lower cerebrospinal fluid(CSF) Aβ-42, Aβ-42/40 levels and a higher P-tau/Aβ-42 ratio. CONCLUSIONS: This study established optimal CL-cutoff, providing a clinically applicable framework for interpreting Aβ PET/MRI findings. Incorporating a two-cutoff system facilitates the tracking of the AD continuum and supports individualized therapeutic decision-making.
Source: Alzheimer s Research & Therapy
Authors: Hanxiao Xue, Sheng Bi, Meixi Wang, Xiaohua Zhu, Feng Wang, Yong Wang, Yujie He, Yan Wang, Xiaocao Liu, Bixiao Cui, Na Li, Zhilian Zhao, Chun Zhang, Liyong Wu, Zhigang Qi, Shaozhen Yan, Jie Lu
Institutions: Ministry of Education of the People's Republic of China, Capital Medical University, Xuan Wu Hospital of the Capital Medical University, Tongji Hospital, Huazhong University of Science and Technology, Nanjing First Hospital, Nanjing Medical University, Hebei Medical University, First Hospital of Shijiazhuang, First Affiliated Hospital of Hebei Medical University
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $4,290
OpenAlex ID: W7162093323
