Application of Mass Multivariate Analysis on Neuroimaging Data Sets for Precision Diagnostics of Depression.
Fiche du document
12 février 2022
- doi: 10.3390/diagnostics12020469
- issn: 2075-4418
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/doi/10.3390/diagnostics12020469
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/pmid/35204560
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/pissn/2075-4418
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/urn/urn:nbn:ch:serval-BIB_971EB39527734
info:eu-repo/semantics/openAccess , CC BY 4.0 , https://creativecommons.org/licenses/by/4.0/
Sujets proches
Schizophrenic disorders Dementia praecoxCiter ce document
R. Paunova et al., « Application of Mass Multivariate Analysis on Neuroimaging Data Sets for Precision Diagnostics of Depression. », Serveur académique Lausannois, ID : 10.3390/diagnostics12020469
Métriques
Partage / Export
Résumé
We used the Mass Multivariate Method on structural, resting-state, and task-related fMRI data from two groups of patients with schizophrenia and depression in order to define several regions of significant relevance to the differential diagnosis of those conditions. The regions included the left planum polare (PP), the left opercular part of the inferior frontal gyrus (OpIFG), the medial orbital gyrus (MOrG), the posterior insula (PIns), and the parahippocampal gyrus (PHG). This study delivered evidence that a multimodal neuroimaging approach can potentially enhance the validity of psychiatric diagnoses. Structural, resting-state, or task-related functional MRI modalities cannot provide independent biomarkers. Further studies need to consider and implement a model of incremental validity combining clinical measures with different neuroimaging modalities to discriminate depressive disorders from schizophrenia. Biological signatures of disease on the level of neuroimaging are more likely to underpin broader nosological entities in psychiatry.