Anterolateral entorhinal cortex thickness as a new biomarker for early detection of Alzheimer's disease

Holbrook, Andrew J.; Tustison, Nicholas J.; Márquez, Freddie; Roberts, Jared M.; Yassa, Michael A.; Gillen, Daniel L.; Initiative§, Alzheimer's Disease Neuroimaging

doi:10.1002/dad2.12068

Cited by 26 publications

(29 citation statements)

References 52 publications

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“…Another factor that might have an effect is the severity of Alzheimer's disease patients in the study population and the size of the study population. The entorhinal cortex thickness in this study has a minimal difference in a study from Holbrook et al (12) , where the mean entorhinal cortex thickness was 1.97±0.19 mm. In another study from Velayudhan et al (13) , the mean entorhinal cortex thickness had a fairly significant difference with of the entorhinal cortex thickness in this study, which 2.6±0.53 mm.…”

Section: Discussioncontrasting

confidence: 72%

Hippocampal Volume and Entorhinal Cortex Thickness in Alzheimer’s Disease

Leon Agung Manurung,

Widiana Ferriastuti,

Bambang Soeprijanto

et al. 2021

Indian Journal of Forensic Medicine & Toxicology

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Magnetic Resonance Imaging (MRI) is the standard imaging evaluations in Alzheimer's Disease (AD). Information regarding hippocampus and entorhinal cortex sizes plays an important role in Alzheimer's disease. This study aims to determine hippocampal volume and entorhinal cortex thickness in Alzheimer's disease obtained from a group of patients who underwent head MRI.This study was an observational study with retrospective approach in patients who were diagnosed with AD and had available head MRI examination results. A total of 14 patients were diagnosed by a neurologist with AD using MMSE, Hachinsky, and NIA-AA criteria.From head MRI measurement in AD patients, we found that the mean volume of right, left, and total hippocampal was 1700±0.395 cm 3 ; 1.670±0.349 cm 3 ; and 3.370±0.725 cm 3 , respectively. The mean thickness of right, left, and total entorhinal cortex was 1.821±0.459 mm; 1.463±0.369 mm; and 3.285±0.791 mm, respectively. There is a possible difference between the early and late stages of AD in the same patient. Further studies with larger cohorts are needed to examine these correlations.

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Section: Discussioncontrasting

confidence: 72%

Hippocampal Volume and Entorhinal Cortex Thickness in Alzheimer’s Disease

Leon Agung Manurung,

Widiana Ferriastuti,

Bambang Soeprijanto

et al. 2021

Indian Journal of Forensic Medicine & Toxicology

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“…Root mean square error (RMSE) between the actual and predicted ages are the quantity used for comparative evaluation. As we have explained previously 20 , we find these evaluation measures to be much more useful than some other commonly applied criteria as they are closer to assessing the actual utility of these thickness measurements as actual biomarkers for disease 46 In addition to the training data listed above, to ensure generalizability, we also compared performance using the SRPB data set 6 comprising over 1600 participants from 12 sites. Note that we recognize that we are processing data through the proposed deep learning-based pipeline that were used to train certain components of this pipeline.…”

Section: Resultsmentioning

confidence: 99%

The ANTsX ecosystem for quantitative biological and medical imaging

Tustison

Holbrook³

et al. 2020

Preprint

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The Advanced Normalizations Tools ecosystem, known as ANTsX, consists of multiple open- source software libraries which house top-performing algorithms used worldwide by scientific and research communities for processing and analyzing biological and medical imaging data. The base software library, ANTs, is built upon, and contributes to, the NIH-sponsored Insight Toolkit. Founded in 2008 with the highly regarded Symmetric Normalization image registration framework, the ANTs library has since grown to include additional functionality. Recent enhancements include statistical, visualization, and deep learning capabilities through interfacing with both the R statistical project (ANTsR) and Python (ANTsPy). Additionally, the corresponding deep learning extensions ANTsRNet and ANTsPyNet (built on the popular TensorFlow/Keras libraries) contain several popular network architectures and trained models for specific applications. One such comprehensive application is a deep learning analog for generating cortical thickness data from structural T1-weighted brain MRI. Not only does this significantly improve computational efficiency and provide comparable-to-superior accuracy over the existing ANTs pipeline but it also illustrates the importance of the comprehensive ANTsX approach as a framework for medical image analysis.

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“…Another limitation is the absence of biomarker data concerning potential AD pathology. The grey matter differences that were observed in the ERC in our at-risk group may provide an indirect marker of potential AD pathology given prior work showing associations between ERC thickness and tau pathology (Holbrook et al, 2019; Velayudhan et al, 2013), but future work employing in vivo biomarkers is needed to address this question. Moreover, it is important to note that not every adult identified as at-risk in our study will move on to develop clinical memory impairment or an AD diagnosis.…”

Section: Discussionmentioning

confidence: 99%

Medial temporal lobe structure, mnemonic and perceptual discrimination in healthy older adults and those at risk for mild cognitive impairment

Gellersen

Trelle

Farrar

et al. 2022

Preprint

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Cognitive tests sensitive to the integrity of the medial temporal lobe (MTL), such as mnemonic discrimination of perceptually similar stimuli, may be useful early markers of risk for cognitive decline in older populations. Perceptual discrimination of stimuli with overlapping features also relies on MTL, but remains relatively unexplored in this context. We assessed mnemonic discrimination in two test formats (Forced Choice, Yes/No) and perceptual discrimination of objects and scenes in 111 community-dwelling older adults at different risk status for cognitive impairment based on neuropsychological screening. We also investigated associations between performance and MTL subregion volume and thickness. The at-risk group exhibited reduced entorhinal thickness and impaired perceptual and mnemonic discrimination. Perceptual discrimination impairment partially explained group differences in mnemonic discrimination and correlated with entorhinal thickness. Executive dysfunction accounted for Yes/No deficits in at-risk adults, demonstrating the importance of test format for the interpretation of memory decline. These results suggest that perceptual discrimination tasks may be useful tools for detecting incipient cognitive impairment related to reduced MTL integrity in non-clinical populations.

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Anterolateral entorhinal cortex thickness as a new biomarker for early detection of Alzheimer's disease

Cited by 26 publications

References 52 publications

Hippocampal Volume and Entorhinal Cortex Thickness in Alzheimer’s Disease

Hippocampal Volume and Entorhinal Cortex Thickness in Alzheimer’s Disease

The ANTsX ecosystem for quantitative biological and medical imaging

Medial temporal lobe structure, mnemonic and perceptual discrimination in healthy older adults and those at risk for mild cognitive impairment

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