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Quantification of plaque size over time was determined from the area of the YFP-A3L signal using MetaMorph (Molecular Devices Corporation, CA).
For the quantification of plaque levels, the numbers of plaques in each region were measured using the TOMORO ScopeEye 3.6 program (Techsan Community, Seoul, Korea).
Using our novel image analysis algorithm for semi-automatic quantification of plaque burden, we demonstrate an early onset and progressive plaque deposition starting at 3 months of age in homozygous mice with low inter-animal variability and 100%-penetrance of the phenotype.
Results showed that quantification of plaque area was possible.
A significantly strong correlation was found between CCTA and IVUS in the quantification of plaque volumes.
Postprocessing techniques aimed at automated quantification of plaque volume and identification of different plaque components are currently being developed.
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Unlike angiography, which displays only the opacified luminal "silhouette," IVUS provides transmural imaging of the entire arterial wall and permits both detection of early-stage atherosclerosis and accurate cross-sectional and even 3-dimensional quantification of plaques.
Other quantification approaches for measuring integrity or impairment of gray matter such as spectroscopy of synaptic density or recently introduced Positron Emission Tomography methods [42] focussing on the quantification of plaques and tangles in AD might complement the present approach in the future [4].
Early comparisons of CCTA with intravascular ultrasound showed promise for characterization and quantification of plaques, although results were affected by limited scan resolution and reproducibility [ 44– 44].
These findings indicate that TSPO expression in plaque macrophages represents a potential target for the in vivo quantification of carotid plaque inflammation using non-invasive PET scintigraphy.
Brain sections of the animals were stained with Thioflavin S for the histological quantification of Aβ plaque load by applying a computerized image analysis and object recognition algorithm [33].
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Justyna Jupowicz-Kozak
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