Very high interrater reliability for manual segmentation of the medial perirhinal cortex. (1st February 2022)

• Record Type: Journal Article
• Authors: Henzen, Nicolas A.; Reinhardt, Julia; Blatow, Maria; Kressig, Reto W.; Krumm, Sabine
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 4
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-02-01
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.052922
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Intracellular neurofibrillary tangles (NFT) belong to the main characteristics of Alzheimer's disease (AD) pathology and occur first in the medial perirhinal cortex (mPRC; also referred to as "transentorhinal region"). Adjacent regions such as lateral perirhinal cortex (lPRC), entorhinal cortex (ERC), and hippocampus are affected at a later stage of NFT progression. Therefore, mPRC integrity potentially serves as a promising imaging biomarker in early AD. Due to the high anatomic variability of the collateral sulcus, which defines mPRC boundaries, it is important to evaluate the interrater reliability of manual segmentation. Today, automated segmentation protocols only exist for the whole PRC (i.e. mPRC and lPRC together). However, discrete analysis of mPRC integrity is crucial to detect AD related pathology as early as possible. Method: Forty‐four adults (20 men; mean age = 69.2 ± 10.4 years) from different diagnostic groups (e.g. normal controls, mild cognitive impairment, Alzheimer's dementia or major depression) were included in the analyses. All subjects received structural magnetic resonance imaging in a 3‐Tesla scanner (MAGNETOM Verio, Siemens). Regions of interest (mPRC, lPRC, and ERC) were drawn by‐hand by two raters (SK, NAH) blinded for diagnoses. Bilateral cortical thickness estimates were extracted using FreeSurfer. Intraclass correlation coefficients (ICC) were calculated in SPSS based on a single‐rating, absolute‐agreement, 2‐way mixed‐effects model. Result: A high degree of reliability was found between both raters with an average measure ICC of .876 for the left mPRC ( F [43, 43]=14.954, p <.001, 95% confidence interval [CI] =.784 ‐ .930) and .873 for the right mPRC ( F [43, 43]=14.472, p <.001, 95% CI=.779 ‐ .929). Similar results were found for lPRC (left: ICC=.984; F [43, 43]=118.834, p <.001, 95% CI=.970 ‐ .991; right: ICC=.953; F [43, 43]=40.344, p <.001, 95% CI=.915 ‐ .974) and ERC (left: ICC=.969; F [43, 43]=62.657, p <.001, 95% CI=.944 ‐ .983; right: ICC=.961; F [43, 43]=49.390, p <.001, 95% CI=.930 ‐ .979). Conclusion: The ICC analysis showed a very high interrater reliability for manual mPRC segmentation as well as for lPRC and ERC. These results indicate that the applied segmentation protocol, which considers collateral sulcus variability, allows different raters to achieve highly similar results and may serve as a reference to establish future automated segmentation protocols.