ArticleAlzheimer's research & therapy2026
Lecanemab in practice: AI-derived MRI predictors of benefit and Amyloid Related Imaging Abnormalities (ARIA).
Article in Alzheimer's research & therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Anti-Amyloid Monoclonal Antibodies in Early Alzheimer Disease: Lecanemab and Donanemab.Neurology international · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionLecanemab, a monoclonal antibody targeting amyloid beta, has demonstrated meaningful clinical benefits in early Alzheimer's disease (AD), yet real-world data is needed to optimize patient selection and enhance safety monitoring, particularly with respect to amyloid-related imaging abnormalities (ARIA). Integration of quantitative and AI-derived MRI biomarkers may improve risk stratification and prediction of clinical trajectory.
methodsWe conducted a retrospective real-world study of eighty-two patients with biomarker-confirmed early AD who initiated lecanemab at Tel Aviv Sourasky Medical Center between November 2023 and June 2025. Baseline MRI included volumetric T1-weighted imaging and susceptibility-weighted imaging (SWI). Automated whole-brain, regional cortical, and hippocampal volumes, and percentiles were extracted using FDA-cleared AI tools (icobrain by icometrix). Microhaemorrhage (MH) burden was assessed by both human and AI-assisted reads. Cognitive outcomes were evaluated using change in Mini-Mental State Examination (MMSE). Linear regression models assessed MRI predictors of cognitive response, and multivariable logistic regression identified predictors of ARIA.
resultsPatients exhibited significantly lower cerebral volumes at treatment initiation. Mean whole brain percentile, mean gray-matter (GM) percentile, and mean white matter percentile were 11.45%, 8.6% and 38% respectively. Higher baseline GM volume predicted less MMSE decline at 12 months (β = 0.64, FDR-corrected p < 0.003). Hippocampal and white-matter volumes were not associated with cognitive outcomes. Seventeen patients (20.7%) developed ARIA. Baseline MH burden was the strongest predictor of ARIA (human rated OR=3.48 per MH, p=0.015, icobrain rated OR=3.25, p=0.01), while APOE ε4 carriage showed a strong directional trend which did not reach significance. Aspirin use and hypertension were not associated with ARIA. Agreement between icobrain and experts for MH ratings was excellent with a single-measure intraclass correlation coefficient (ICC) of 0.89 (95% CI: 0.83-0.93).
conclusionsAI-derived MRI markers, particularly GM volume and MH burden, provide valuable predictors of cognitive response and ARIA risk in patients treated with lecanemab. Integrating quantitative neuroimaging into clinical workflows may enhance personalized treatment decisions and improve real-world implementation of Amyloid-targeting therapies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.