Discriminant analysis using MRI asymmetry indices and cognitive scores of women with temporal lobe epilepsy or schizophrenia.

Purpose: This study aims to assess the diagnostic power of brain asymmetry indices and neuropsychological tests for differentiating mesial temporal lobe epilepsy (MTLE) and schizophrenia (SCZ). Methods: We studied a total of 39 women including 13 MTLE, 13 SCZ, and 13 healthy individuals (HC). A neur...

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Publicado en:Neuroradiology Vol. 66; no. 7; pp. 1083 - 1093
Autores principales: Fırat, Zeynep, Er, Füsun, Noyan, Handan, Ekinci, Gazanfer, Üçok, Alp, Uluğ, Aziz M., Aktekin, Berrin
Formato: diagnostic images research tables/charts Journal Article
Publicado: Springer Nature Jul2024
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jul2024
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      pub: Springer Nature
      place: New York, New York
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        atl: Discriminant analysis using MRI asymmetry indices and cognitive scores of women with temporal lobe epilepsy or schizophrenia.
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          Fırat, Zeynep
          Er, Füsun
          Noyan, Handan
          Ekinci, Gazanfer
          Üçok, Alp
          Uluğ, Aziz M.
          Aktekin, Berrin
        affil: https://ror.org/025mx2575 Department of Radiology, Yeditepe University Hospitals, 34718, Kosuyolu, Istanbul, Turkey
      sug:
        subj:
          Magnetic Resonance Imaging
          Cognition Evaluation
          Women Psychosocial Factors
          Epilepsy, Temporal Lobe
          Schizophrenia
          Neuropsychological Tests
          Human
          Discriminant Analysis
          Female
          Biological Markers
          Female
      ab: Purpose: This study aims to assess the diagnostic power of brain asymmetry indices and neuropsychological tests for differentiating mesial temporal lobe epilepsy (MTLE) and schizophrenia (SCZ). Methods: We studied a total of 39 women including 13 MTLE, 13 SCZ, and 13 healthy individuals (HC). A neuropsychological test battery (NPT) was administered and scored by an experienced neuropsychologist, and NeuroQuant (CorTechs Labs Inc., San Diego, California) software was used to calculate brain asymmetry indices (ASI) for 71 different anatomical regions of all participants based on their 3D T1 MR imaging scans. Results: Asymmetry indices measured from 10 regions showed statistically significant differences between the three groups. In this study, a multi-class linear discriminant analysis (LDA) model was built based on a total of fifteen variables composed of the most five significantly informative NPT scores and ten significant asymmetry indices, and the model achieved an accuracy of 87.2%. In pairwise classification, the accuracy for distinguishing MTLE from either SCZ or HC was 94.8%, while the accuracy for distinguishing SCZ from either MTLE or HC was 92.3%. Conclusion: The ability to differentiate MTLE from SCZ using neuroradiological and neuropsychological biomarkers, even within a limited patient cohort, could make a substantial contribution to research in larger patient groups using different machine learning techniques.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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