Published October 7, 2025 | Version v1
Dataset Open

Radiomic Features from Structural MRI in First-Episode Psychosis (FEP) and Healthy Controls (HC)

Authors/Creators

  • 1. ROR icon Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana
  • 2. Departamento de Psiquiatría, Hospital Clínico Universitario de Valencia
  • 3. Instituto de Investigación Sanitaria, INCLIVA

Contributors

  • 1. ROR icon Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana
  • 2. ROR icon Hospital Clínico Universitario de Valencia
  • 3. Instituto de Investigación Sanitaria, INCLIVA

Description

This dataset contains radiomic features extracted from structural T1-weighted MRI scans of participants diagnosed with First-Episode Psychosis (FEP) and matched Healthy Controls (HC). A total of 304 subjects were included, comprising 130 FEP and 174 HC cases. Preprocessing and cortical/subcortical segmentation were performed with FreeSurfer v7.4.2, and radiomic features were extracted using PyRadiomics v3.0.1 following IBSI guidelines. 

The dataset includes: 

  • Subject identifiers (anonymized) 
  • Diagnostic labels (FEP vs HC) 
  • Extracted radiomic features across cortical and subcortical regions ( aparc+aseg Freesurfer in first-order, shape, and multiple texture families: GLCM, GLRLM, GLSZM, NGTDM, GLDM). 

This resource can support reproducibility and benchmarking in neuroimaging-based machine learning studies, enabling the exploration of structural MRI biomarkers in psychosis. 

This work was supported by  the Valencian Regional Government (CIPROM/2023/28) and the Carlos III Healthcare Institute (ISCIII), projects PI20/00473 (to M.D. Moltó), PI22/01985 (to O. Rivero) and CP21/00059 (to O. Rivero), co-funded by the European Union. 

Files

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Additional details

Funding

Generalitat Valenciana
CIPROM/2023/28
Instituto de Salud Carlos III
PI20/00473
European Union Satellite Centre
CP21/00059

Software

Repository URL
https://github.com/BIMCV-CSUSP/First-episode_Psychosis_Clasification
Programming language
Python , Jupyter Notebook
Development Status
Active