ArticleNature neuroscience2025
Addressing artifactual bias in large, automated MRI analyses of brain development.
Article in Nature neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Perinatal Factors and Neuroimaging Changes for Brain Maturation Among Adolescents.JAMA network open · 2026Article
- Validation of five automated structural MRI quality assessment tools against expert ratings.Neuroradiology · 2026Article
- FairGen: preference-aligned diffusion for demographically equitable medical image synthesis.NPJ digital medicine · 2026Article
- Task and Resting-State Functional Magnetic Resonance Imaging Modeling of Brain-Behavior Relationships in Developmental Cohorts.Biological psychiatry · 2026Review
- Pregistered movie-fMRI analyses reveal altered visual feature encoding in autism in pSTS.bioRxiv : the preprint server for biology · 2026Article
- Prenatal Adversities and Risk of Persistent Youth Psychopathology and Altered Cortical Thinning.JAMA psychiatry · 2026Article
- Bias in Structural MRI Correlates of Delay Discounting due to Head Motion.Human brain mapping · 2026Article
- Understanding the robustness of vision-language models to medical image artefacts.NPJ digital medicine · 2025Article
- Article
- An Open, Fully-processed, Longitudinal Data Resource to Study Brain Development and Transdiagnostic Executive Function.bioRxiv : the preprint server for biology · 2025Article
- Social Determinants of Health Influence Brain and Cognitive Function in Youth.Biological psychiatry global open science · 2025Article
- Association of Adverse Prenatal Exposure Burden with Persistent Psychopathology and Accelerated Cortical Thinning in Youth.medRxiv : the preprint server for health sciences · 2025Article
- Reporting checklists in neuroimaging: promoting transparency, replicability, and reproducibility.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024Review
- A (sub)field guide to quality control in hippocampal subfield segmentation on high-resolution THuman brain mapping · 2024Review
- Functional connectome through the human life span.bioRxiv : the preprint server for biology · 2024Article
- Parental education and income are linked to offspring cortical brain structure and psychopathology at 9-11 years.JCPP advances · 2024Article
- A (Sub)field Guide to Quality Control in Hippocampal Subfield Segmentation on Highresolution TbioRxiv : the preprint server for biology · 2023Article
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18 authors.
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Abstract
Large, population-based magnetic resonance imaging (MRI) studies of adolescents promise transformational insights into neurodevelopment and mental illness risk. However, youth MRI studies are especially susceptible to motion and other artifacts that introduce non-random noise. After visual quality control of 11,263 T1 MRI scans obtained at age 9-10 years through the Adolescent Brain Cognitive Development study, we uncovered bias in measurements of cortical thickness and surface area in 55.1% of the samples with suboptimal image quality. These biases impacted analyses relating structural MRI and clinical measures, resulting in both false-positive and false-negative associations. Surface hole number, an automated index of topological complexity, reproducibly identified lower-quality scans with good specificity, and its inclusion as a covariate partially mitigated quality-related bias. Closer examination of high-quality scans revealed additional topological errors introduced during image preprocessing. Correction with manual edits reproducibly altered thickness measurements and strengthened age-thickness associations. We demonstrate here that inadequate quality control undermines advantages of large sample size to detect meaningful associations. These biases can be mitigated through additional automated and manual interventions.
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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.