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Excellent Interrater Reliability for Manual Segmentation of the Medial Perirhinal Cortex.
Henzen, Nicolas A; Reinhardt, Julia; Blatow, Maria; Kressig, Reto W; Krumm, Sabine.
Afiliación
  • Henzen NA; University Department of Geriatric Medicine FELIX PLATTER, 4055 Basel, Switzerland.
  • Reinhardt J; Faculty of Psychology, University of Basel, 4001 Basel, Switzerland.
  • Blatow M; Division of Diagnostic and Interventional Neuroradiology, Department of Radiology, University Hospital Basel, University of Basel, 4031 Basel, Switzerland.
  • Kressig RW; Department of Cardiology and Cardiovascular Research Institute Basel (CRIB), University Hospital Basel, University of Basel, 4031 Basel, Switzerland.
  • Krumm S; Department of Orthopedic Surgery and Traumatology, University Hospital of Basel, University of Basel, 4031 Basel, Switzerland.
Brain Sci ; 13(6)2023 May 24.
Article en En | MEDLINE | ID: mdl-37371329
Objective: Evaluation of interrater reliability for manual segmentation of brain structures that are affected first by neurofibrillary tau pathology in Alzheimer's disease. Method: Medial perirhinal cortex, lateral perirhinal cortex, and entorhinal cortex were manually segmented by two raters on structural magnetic resonance images of 44 adults (20 men; mean age = 69.2 ± 10.4 years). Intraclass correlation coefficients (ICC) of cortical thickness and volumes were calculated. Results: Very high ICC values of manual segmentation for the cortical thickness of all regions (0.953-0.986) and consistently lower ICC values for volume estimates of the medial and lateral perirhinal cortex (0.705-0.874). Conclusions: The applied manual segmentation protocol allows different raters to achieve remarkably similar cortical thickness estimates for regions of the parahippocampal gyrus. In addition, the results suggest a preference for cortical thickness over volume as a reliable measure of atrophy, especially for regions affected by collateral sulcus variability (i.e., medial and lateral perirhinal cortex). The results provide a basis for future automated segmentation and collection of normative data.
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Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Brain Sci Año: 2023 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Brain Sci Año: 2023 Tipo del documento: Article