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                  <mods:namePart>Gil Gregorio, Pedro</mods:namePart>
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                  <mods:namePart>Ramírez Sebastián, José Manuel</mods:namePart>
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               <mods:identifier type="citation">Jáñez Escalada, L., Jáñez García, L., García Martín, E. S. et al. «Spatial Analysis of Thickness Changes in Ten Retinal Layers of Alzheimer’s Disease Patients Based on Optical Coherence Tomography». Scientific Reports, vol. 9, n.o 1, septiembre de 2019, p. 13000. DOI.org (Crossref), https://doi.org/10.1038/s41598-019-49353-0.</mods:identifier>
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               <mods:abstract>The retina is an attractive source of biomarkers since it shares many features with the brain. Thickness differences in 10 retinal layers between 19 patients with mild Alzheimer’s disease (AD) and a control group of 24 volunteers were investigated. Retinal layers were automatically segmented and their thickness at each scanned point was measured, corrected for tilt and spatially normalized. When the mean thickness of entire layers was compared between patients and controls, only the outer segment layer of patients showed statistically significant thinning. However, when the layers were compared point-by point, patients showed statistically significant thinning in irregular regions of total retina and nerve fiber, ganglion cell, inner plexiform, inner nuclear and outer segment layers. Our method, based on random field theory, provides a precise delimitation of regions where total retina and each of its layers show a statistically significant thinning in AD patients. All layers, except inner nuclear and outer segments, showed thickened regions. New analytic methods have shown that thinned regions are interspersed with thickened ones in all layers, except inner nuclear and outer segments. Across different layers we found a statistically significant trend of the thinned regions to overlap and of the thickened ones to avoid overlapping.</mods:abstract>
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                  <mods:title>Spatial analysis of thickness changes in ten retinal layers of Alzheimer’s disease patients based on optical coherence tomography</mods:title>
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