Quantitative neuropathological assessment to investigate cerebral multi-morbidity

Abstract

The aging brain is characterized by the simultaneous presence of multiple pathologies, and the prevalence of cerebral multi-morbidity increases with age. To understand the impact of each subtype of pathology and the combined effects of cerebral multi-morbidity on clinical signs and symptoms, large clinico-pathological correlative studies have been performed. However, such studies are often based on semi-quantitative assessment of neuropathological hallmark lesions. Here, we discuss some of the new methods for high-throughput quantitative neuropathological assessment. These methods combine increased quantitative rigor with the added technical capacity of computers and networked analyses. There are abundant new opportunities - with specific techniques that include slide scanners, automated microscopes, and tissue microarrays - and also potential pitfalls. We conclude that quantitative and digital neuropathologic approaches will be key resources to further elucidate cerebral multi-morbidity in the aged brain and also hold the potential for changing routine neuropathologic diagnoses.

Figure 1

Digital quantification of tau pathologies. (A) Analyses are performed on a paired helical filament-1 immunostained section. (B) After the crafted Genie neurofibrillary tangle/neuritic plaque (NFT/NP) algorithm was used to isolate the NFTs, the NFT density (NFTs/mm²) is determined by a modified nuclear algorithm, with NFT pseudo-colored yellow. (C) In a similar manner, the NP burden is calculated by first using the same crafted Genie algorithm to isolate the NPs, here pseudocolored orange. (D) An overall tau burden is also calculated: red: positive immunohistochemical (IHC) staining; blue: negative IHC staining. Scale bar, 25 μm. (E) A sample of the data that are provided in each pathology report from the University of Kentucky for a quantitative description of Alzheimer’s disease (AD) pathology. ADNC, Alzheimer’s disease neuropathologic change; CA1, hippocampus sector CA1; CERAD, Consortium to Establish a Registry for Alzheimer’s Disease; Inf, inferior; SMTG, superior and middle temporal gyri.

Figure 2

Digital quantification in a brain section using alpha-smooth muscle actin (α -SMA) immunohistochemistry which labels arterioles. Actual immunohistochemical stain is brown (A) whereas the digital detection of those markers is pseudocolored green (B) after digital analyses were run. This is the basis for further in silico analyses of the blood vessel morphology. Scale bars, 100 μm. (C) A sample of the data that are collected from each analysis. Note that aspects of the blood vessel lumen, in addition to the lumen wall, are measured in a systematic way.