Style transfer generative adversarial networks to harmonize multisite MRI to a single reference image to avoid overcorrection

Human Brain Mapping, Journal Year: 2023, Volume and Issue: 44(14), P. 4875 - 4892

Published: July 20, 2023

Abstract Recent work within neuroimaging consortia have aimed to identify reproducible, and often subtle, brain signatures of psychiatric or neurological conditions. To allow for high‐powered imaging analyses, it is necessary pool MR images that were acquired with different protocols across multiple scanners. Current retrospective harmonization techniques shown promise in removing site‐related image variation. However, most statistical approaches may over‐correct technical, scanning‐related, variation as they cannot distinguish between confounded image‐acquisition based variability population variability. Such methods require datasets contain subjects patient groups similar clinical demographic information isolate the acquisition‐based overcome this limitation, we consider magnetic resonance (MR) a style transfer problem rather than domain problem. Using fully unsupervised deep‐learning framework on generative adversarial network (GAN), show can be harmonized by inserting encoded from single reference image, without knowing their site/scanner labels priori. We trained our model using data five large‐scale multisite varied demographics. Results demonstrated style‐encoding harmonize images, match intensity profiles, relying traveling subjects. This also avoids need control clinical, diagnostic, information. highlight effectiveness method research comparing extracted cortical subcortical features, brain‐age estimates, case–control effect sizes before after harmonization. showed removed variances, while preserving anatomical meaningful patterns. further diverse training set, successfully collected unseen scanners protocols, suggesting promising tool ongoing collaborative studies. Source code released USC‐IGC/style_transfer_harmonization (github.com).

Language: Английский

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Multimodal brain connectome-based prediction of suicide risk in people with late-life depression

Nature Mental Health, Journal Year: 2023, Volume and Issue: 1(2), P. 100 - 113

Published: Feb. 17, 2023

Abstract Suicidal ideation, plans and behavior are particularly serious health issues among the older population, resulting in a higher likelihood of deaths than any other age group. The increasing prevalence depression late life reflects urgent need for efficient screening suicide risk people with late-life depression. Employing cross-sectional design, we performed connectome-based predictive modelling using whole-brain resting-state functional connectivity white matter structural data to predict patients ( N = 37 non-suicidal patients, 24 suicidal ideation/plan, 30 who attempted suicide). Suicide was measured three standardized questionnaires. Brain profiles were used classify groups our dataset two independent datasets machine learning. We found that brain patterns could explained variance up 30.34%. improved classification-prediction accuracy compared questionnaire scores alone be applied identify depressed had datasets. Our findings suggest multimodal capture individual differences patients. models might further tested help clinicians detailed assessments interventions. trial registration number this study is ChiCTR2200066356.

Language: Английский

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Associations of bullying perpetration and peer victimization subtypes with preadolescent’s suicidality, non-suicidal self-injury, neurocognition, and brain development

BMC Medicine, Journal Year: 2023, Volume and Issue: 21(1)

Published: April 12, 2023

Although both peer victimization and bullying perpetration negatively impact preadolescents' development, the underlying neurobiological mechanism of this adverse relationship remains unclear. Besides, specific psycho-cognitive patterns different subtypes also need further exploration, warranting large-scale studies on general subtypes.

Language: Английский

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Perception of social inclusion/exclusion and response inhibition in adolescents with past suicide attempt: a multidomain task-based fMRI study

Molecular Psychiatry, Journal Year: 2024, Volume and Issue: 29(7), P. 2135 - 2144

Published: Feb. 29, 2024

Language: Английский

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Brain Correlates of Suicide Attempt in 18,925 Participants Across 18 International Cohorts

Biological Psychiatry, Journal Year: 2021, Volume and Issue: 90(4), P. 243 - 252

Published: March 21, 2021

Language: Английский

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