TY - JOUR
T1 - Hyperspectral Raman imaging of neuritic plaques and neurofibrillary tangles in brain tissue from Alzheimer's disease patients
AU - Michael, Ralph
AU - Lenferink, Aufried
AU - Vrensen, Gijs F.J.M.
AU - Gelpi, Ellen
AU - Barraquer, Rafael I.
AU - Otto, Cees
PY - 2017/12/1
Y1 - 2017/12/1
N2 - Neuritic plaques and neurofibrillary tangles are crucial morphological criteria for the definite diagnosis of Alzheimer's disease. We evaluated 12 unstained frontal cortex and hippocampus samples from 3 brain donors with Alzheimer's disease and 1 control with hyperspectral Raman microscopy on samples of 30 × 30 μm. Data matrices of 64 × 64 pixels were used to quantify different tissue components including proteins, lipids, water and beta-sheets for imaging at 0.47 μm spatial resolution. Hierarchical cluster analysis was performed to visualize regions with high Raman spectral similarities. The Raman images of proteins, lipids, water and beta-sheets matched with classical brain morphology. Protein content was 2.0 times, the beta-sheet content 5.6 times and Raman broad-band autofluorescence was 2.4 times higher inside the plaques and tangles than in the surrounding tissue. The lipid content was practically equal inside and outside. Broad-band autofluorescence showed some correlation with protein content and a better correlation with beta-sheet content. Hyperspectral Raman imaging combined with hierarchical cluster analysis allows for the identification of neuritic plaques and neurofibrillary tangles in unstained, label-free slices of human Alzheimer's disease brain tissue. It permits simultaneous quantification and distinction of several tissue components such as proteins, lipids, water and beta-sheets.
AB - Neuritic plaques and neurofibrillary tangles are crucial morphological criteria for the definite diagnosis of Alzheimer's disease. We evaluated 12 unstained frontal cortex and hippocampus samples from 3 brain donors with Alzheimer's disease and 1 control with hyperspectral Raman microscopy on samples of 30 × 30 μm. Data matrices of 64 × 64 pixels were used to quantify different tissue components including proteins, lipids, water and beta-sheets for imaging at 0.47 μm spatial resolution. Hierarchical cluster analysis was performed to visualize regions with high Raman spectral similarities. The Raman images of proteins, lipids, water and beta-sheets matched with classical brain morphology. Protein content was 2.0 times, the beta-sheet content 5.6 times and Raman broad-band autofluorescence was 2.4 times higher inside the plaques and tangles than in the surrounding tissue. The lipid content was practically equal inside and outside. Broad-band autofluorescence showed some correlation with protein content and a better correlation with beta-sheet content. Hyperspectral Raman imaging combined with hierarchical cluster analysis allows for the identification of neuritic plaques and neurofibrillary tangles in unstained, label-free slices of human Alzheimer's disease brain tissue. It permits simultaneous quantification and distinction of several tissue components such as proteins, lipids, water and beta-sheets.
UR - http://www.scopus.com/inward/record.url?scp=85034425600&partnerID=8YFLogxK
U2 - 10.1038/s41598-017-16002-3
DO - 10.1038/s41598-017-16002-3
M3 - Article
AN - SCOPUS:85034425600
SN - 2045-2322
VL - 7
JO - Scientific reports
JF - Scientific reports
IS - 1
M1 - 15603
ER -