Investigating AD and non-AD [¹⁸F]flortaucipir distribution patterns in a memory clinic cohort

Amyloid (A) deposition represents a specific pathological hallmark of Alzheimer's disease (AD). Clinical diagnostic protocols frequently rely on the combined use of amyloid (A)- and tau (T)- positron emission tomography (PET) imaging to distinguish AD from non-amyloid-associated neurodegenerative conditions. Many neurodegenerative disorders are characterized by distinct tauopathies, which result in different [¹⁸F]flortaucipir T-PET topographic patterns. The aim of this study was to investigate, in a memory clinic cohort, whether [¹⁸F]flortaucipir distribution patterns derived from scaled subprofile modelling using principal component analysis (SSM/PCA) could differentiate between A + and A - individuals, potentially eliminating the need for an A-PET.

A total of 81 subjects were included in this study: 40 with AD characterized by both A and T accumulation (A + T +), 13 with suspected non-Alzheimer's pathology (A - T +), and 28 without A and T abnormality (A - T -). SSM/PCA was applied on [¹⁸F]flortaucipir images to identify two disease patterns (DPs), representing amyloid-positive (A + DP) and amyloid-negative (A- DP) accumulation. Each subject's imaging data was then compared to these DPs and the resulting similarity scores were used as inputs for three machine learning models - Support Vector Machine, Random Forest, and Multi-Layer Perceptron - to predict amyloid status. Finally, Spearman correlation analyses were conducted between SSM/PCA-derived scores and plasma biomarkers levels.

The two identified disease patterns exhibited distinct PET signatures consistent with current disease knowledge. Their representativeness was further supported by significant correlations with plasma biomarkers in nearly all cases. All machine learning models confirmed the capacity of the A + DP to predict AD pathology, correctly classifying at least 36 out of 40 cases. In contrast, the A - DP showed limited discriminative power for non-AD conditions, as indicated by its higher misclassification rate (best performance: 7 correct out of 13).

SSM/PCA applied on [¹⁸F]flortaucipir-PET imaging provide information on both A and T status, supporting its potential use as first and possibly sole examination in the investigation of suspected AD. While for non-AD cases, A-PET scans are still recommended.