CT-derived brain volumes and plasma p-Tau217 for risk stratification of amyloid positivity in early-stage Alzheimer's disease.

BACKGROUND: Early detection of amyloid-β (Aβ) pathology is critical for timely intervention in Alzheimer's disease (AD). While Aβ positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers are accurate, their high cost and limited accessibility hinder routine use. We developed a computed tomography (CT)-based, two-stage workflow combining CT-derived atrophy patterns with plasma phosphorylated tau 217 (p-Tau217) to predict Aβ PET positivity. METHODS: In this cohort of 616 participants (521 with mild cognitive impairment (MCI], 95 with early dementia of Alzheimer's type (DAT]; age 60-93 years), CT, p-Tau217 assays, and Aβ PET were performed. A random forest model incorporating CT-derived regional W-scores and apolipoprotein E ε4 (APOE ε4) status stratified individuals into low-, intermediate-, and high-risk groups. p-Tau217 testing was reserved for the intermediate-risk group. RESULTS: At a 95% sensitivity/specificity threshold, CT-based stratification yielded a low-risk negative predictive value (NPV) of 95.8% (93.0-98.6%) and a high-risk positive predictive value (PPV) of 98.4% (96.8-100.0%), with 28.2% classified as intermediate-risk. Targeted plasma testing of intermediate-risk group improved the overall PPV to 92.8% (88.5-97.1%) and the overall NPV to 88.9% (78.6-99.2%), achieving an overall accuracy of 95.8% (94.2-97.4%). The CT-based workflow's accuracy was non-inferior to our MRI-based method (area under the curve 0.96 vs. 0.95; p = 0.14). CONCLUSIONS: This CT-based, two-stage approach is a cost-effective, scalable alternative to MRI-based strategies, leveraging routine CT and selective p-Tau217 testing to enhance early AD detection and optimize resource utilization in clinical practice.