ArticleNeuroImage2020
Longitudinal ComBat: A method for harmonizing longitudinal multi-scanner imaging data.
Article in NeuroImage, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 229 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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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.
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Who cites it
229 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
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- Cortical thickness changes precede high levels of amyloid by at least 7 years.Nature neuroscience · 2026Article
- A multiancestry polygenic risk score for Alzheimer's disease is associated with cognitive decline and neuropathological hallmarks in diverse populations.Nature genetics · 2026Article
- Developmental deviations of association-network structural connectivity in youths with ADHD predict symptom and treatment outcomes.Nature biomedical engineering · 2026Article
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- Lower cardiac output is a risk factor for faster cerebral atrophy over a 11-year follow-up period in APOE-ε4 carriers.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- The role of vascular risk factors in white matter tract microstructure: a multi-cohort study in older adults.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Prenatal and early-life determinants of neurodevelopment: A decade of discoveries and new directions in ABCD.Developmental cognitive neuroscience · 2026Review
- Comparative Analysis of Four Commercially Available Artificial Intelligence Software for Brain Volumetry.Diagnostics (Basel, Switzerland) · 2026Article
- Neuroanatomical Subtypes of Callous-Unemotional Traits in a Community Sample of Youth.bioRxiv : the preprint server for biology · 2026Article
- Biomarker Variability Limits Individualized Amyloid Time Estimation in Alzheimer Disease.bioRxiv : the preprint server for biology · 2026Article
- Characterizing progressive cortical thinning in multiple system atrophy: a longitudinal MRI study.NPJ Parkinson's disease · 2026Article
- Genetic architecture of the limbic white matter microstructure in aging and Alzheimer's Disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Convergent and Divergent Cerebellar Alterations in 22q11.2 Copy Number Variants.Biological psychiatry global open science · 2026Article
169 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
While aggregation of neuroimaging datasets from multiple sites and scanners can yield increased statistical power, it also presents challenges due to systematic scanner effects. This unwanted technical variability can introduce noise and bias into estimation of biological variability of interest. We propose a method for harmonizing longitudinal multi-scanner imaging data based on ComBat, a method originally developed for genomics and later adapted to cross-sectional neuroimaging data. Using longitudinal cortical thickness measurements from 663 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, we demonstrate the presence of additive and multiplicative scanner effects in various brain regions. We compare estimates of the association between diagnosis and change in cortical thickness over time using three versions of the ADNI data: unharmonized data, data harmonized using cross-sectional ComBat, and data harmonized using longitudinal ComBat. In simulation studies, we show that longitudinal ComBat is more powerful for detecting longitudinal change than cross-sectional ComBat and controls the type I error rate better than unharmonized data with scanner included as a covariate. The proposed method would be useful for other types of longitudinal data requiring harmonization, such as genomic data, or neuroimaging studies of neurodevelopment, psychiatric disorders, or other neurological diseases.
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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.