{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Shi L"],"funding":["Leon Levy Foundation","Stavros Niarchos Foundation","Key Technology Research and Development Program of Shandong","Ministry of Health of the People's Republic of China","NIMH NIH HHS","Autism Speaks","National Natural Science Foundation of China","National Institute of Mental Health"],"pagination":["7654-7667"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9089236"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["54(10)"],"pubmed_abstract":["Attention-deficit/hyperactivity disorder (ADHD) is diagnosed subjectively based on an individual's behaviour and performance. The clinical community has no objective biomarker to inform the diagnosis and subtyping of ADHD. This study aimed to explore the potential diagnostic biomarkers of ADHD among surface values, volumetric metrics and radiomic features that were extracted from structural MRI images. Public data of New York University and Peking University were downloaded from the ADHD-200 Consortium. MRI T1-weighted images were pre-processed using CAT12. We calculated surface values based on the Desikan-Killiany atlas. The volumetric metrics (mean grey matter volume and mean white matter volume) and radiomic features within each automated anatomical labelling (AAL) brain area were calcu"],"journal":["The European journal of neuroscience"],"pubmed_title":["Surface values, volumetric measurements and radiomics of structural MRI for the diagnosis and subtyping of attention-deficit/hyperactivity disorder."],"pmcid":["PMC9089236"],"funding_grant_id":["R01 MH083246","R01MH083246","2017GSF218075","200802073","30970802","8100059"],"pubmed_authors":["Liu X","Wu K","Shi L","Li Z","Fan X","Lin C","Zhao S","Sun K"],"additional_accession":[]},"is_claimable":false,"name":"Surface values, volumetric measurements and radiomics of structural MRI for the diagnosis and subtyping of attention-deficit/hyperactivity disorder.","description":"Attention-deficit/hyperactivity disorder (ADHD) is diagnosed subjectively based on an individual's behaviour and performance. The clinical community has no objective biomarker to inform the diagnosis and subtyping of ADHD. This study aimed to explore the potential diagnostic biomarkers of ADHD among surface values, volumetric metrics and radiomic features that were extracted from structural MRI images. Public data of New York University and Peking University were downloaded from the ADHD-200 Consortium. MRI T1-weighted images were pre-processed using CAT12. We calculated surface values based on the Desikan-Killiany atlas. The volumetric metrics (mean grey matter volume and mean white matter volume) and radiomic features within each automated anatomical labelling (AAL) brain area were calcu","dates":{"release":"2021-01-01T00:00:00Z","publication":"2021 Nov","modification":"2025-04-05T12:31:57.389Z","creation":"2025-04-05T12:31:57.389Z"},"accession":"S-EPMC9089236","cross_references":{"pubmed":["34614247"],"doi":["10.1111/ejn.15485"]}}