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Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium
X. Zhu, Y. Kim, O. Ravid, X. He, B. Suarez-Jimenez, S. Zilcha-Mano, A. Lazarov, S. Lee, CG. Abdallah, M. Angstadt, CL. Averill, CL. Baird, LA. Baugh, JU. Blackford, J. Bomyea, SE. Bruce, RA. Bryant, Z. Cao, K. Choi, J. Cisler, AS. Cotton, JK....
Jazyk angličtina Země Spojené státy americké
Typ dokumentu časopisecké články
Grantová podpora
R01 MH111671
NIMH NIH HHS - United States
R01 MH119227
NIMH NIH HHS - United States
R01 AT011267
NCCIH NIH HHS - United States
R61 NS120249
NINDS NIH HHS - United States
R01 MH129832
NIMH NIH HHS - United States
U54 EB020403
NIBIB NIH HHS - United States
R01 MH117601
NIMH NIH HHS - United States
NLK
Directory of Open Access Journals
od 2020
ProQuest Central
od 1998-05-01 do Před 2 měsíci
Health & Medicine (ProQuest)
od 2002-08-01 do Před 2 měsíci
Psychology Database (ProQuest)
od 2002-08-01 do Před 2 měsíci
ROAD: Directory of Open Access Scholarly Resources
- MeSH
- big data MeSH
- lidé MeSH
- magnetická rezonanční tomografie metody MeSH
- mozek diagnostické zobrazování MeSH
- neurozobrazování MeSH
- posttraumatická stresová porucha * diagnostické zobrazování MeSH
- reprodukovatelnost výsledků MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.
Baylor College of Medicine Houston TX USA
Brain Health Research Centre Department of Anatomy University of Otago Dunedin New Zealand
Brain Research and Innovation Centre Ministry of Defence Utrecht The Netherlands
Center of Excellence for Stress and Mental Health VA San Diego Healthcare System San Diego CA USA
Civil Aerospace Medical Institute US Federal Aviation Administration Oklahoma City OK USA
Cognitive and Clinical Neuroimaging Core McLean Hospital Belmont MA USA
Department of Neuroscience Western University London ON Canada
Department of Pediatrics University of Minnesota Minneapolis MN USA
Department of Psychiatry and Behavioral Health Ohio State University Columbus OH USA
Department of Psychiatry Columbia University Medical Center New York NY USA
Department of Psychiatry University of Texas at Austin Austin TX USA
Department of Psychology and Neuroscience Baylor University Waco TX USA
Department of Psychology University of British Columbia Okanagan Kelowna British Columbia Canada
Department of Psychology University of Chinese Academy of Sciences Beijing China
Department of Psychology Vanderbilt University Nashville TN USA
Department of Radiology The Affiliated Yixing Hospital of Jiangsu University Yixing Jiangsu China
Department of Radiology Washington University School of Medicine St Louis MO USA
Departments of Psychology and Psychiatry Neuroscience Program Western University London ON Canada
Division of Neuroradiology Brigham and Women's Hospital Boston MA USA
Division of Women's Mental Health McLean Hospital Belmont MA USA
Emory University Department of Psychiatry and Behavioral Sciences Atlanta GA USA
Ghent University Ghent Belgium
Harvard Medical School Boston MA USA
Harvard University Boston MA USA
Heidelberg University Heidelberg Germany
Institute of Psychology Chinese Academy of Sciences Beijing China
Leiden University Medical Center Leiden The Netherlands
Marquette University Milwaukee WI USA
Masaryk University Brno Czechia
McLean Hospital Belmont MA USA
Medical College of Wisconsin Milwaukee WI USA
Minneapolis VA Health Care System Minneapolis MN USA
Munroe Meyer Institute University of Nebraska Medical Center Omaha NE USA
Neuroscience Research Australia Randwick NSW Australia
New York State Psychiatric Institute New York NY USA
Psychiatry Neuroimaging Laboratory Brigham and Women's Hospital Boston MA USA
Sanford School of Medicine University of South Dakota Vermillion SD USA
School of Medicine and Public Health University of Wisconsin Madison Madison WI USA
School of Psychology University of New South Wales Sydney NSW Australia
Stanford University Stanford CA USA
Tel Aviv University Tel Aviv Israel
UMR 1253 CIC 1415 University of Tours CHRU de Tours INSERM France
University of California Irvine Irvine CA USA
University of California San Diego La Jolla CA USA
University of Cape Town Cape Town South Africa
University of Groningen Groningen The Netherlands
University of Haifa Haifa Israel
University of Illinois at Chicago Chicago IL USA
University of Iowa Iowa City IA USA
University of Michigan Ann Arbor MI USA
University of Minnesota Minneapolis MN USA
University of Münster Münster Germany
University of North Carolina at Chapel Hill Chapel Hill NC USA
University of Rochester Rochester NY USA
University of South Dakota Vermillion SD USA
University of Toledo Toledo OH USA
University of Utah School of Medicine Salt Lake City UT USA
University of Washington Seattle WA USA
University of Wisconsin Madison Madison WI USA
University of Wisconsin Milwaukee Milwaukee WI USA
VISN 17 Center of Excellence for Research on Returning War Veterans Waco TX USA
Wayne State University School of Medicine Detroit MI USA
Westmead Institute for Medical Research Westmead NSW Australia
Citace poskytuje Crossref.org
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- BAS __
- $a 3
- BAS __
- $a PreBMC-MEDLINE
- BMC __
- $a 2023 $b 283 $c - $d 120412 $e 20231018 $i 1095-9572 $m NeuroImage $n Neuroimage $x MED00006575
- GRA __
- $a R01 MH111671 $p NIMH NIH HHS $2 United States
- GRA __
- $a R01 MH119227 $p NIMH NIH HHS $2 United States
- GRA __
- $a R01 AT011267 $p NCCIH NIH HHS $2 United States
- GRA __
- $a R61 NS120249 $p NINDS NIH HHS $2 United States
- GRA __
- $a R01 MH129832 $p NIMH NIH HHS $2 United States
- GRA __
- $a U54 EB020403 $p NIBIB NIH HHS $2 United States
- GRA __
- $a R01 MH117601 $p NIMH NIH HHS $2 United States
- LZP __
- $a Pubmed-20240109
