| Literature DB >> 30364998 |
Juan Eugenio Iglesias1, Shauna Crampsie2, Catherine Strand2, Mohamed Tachrount3, David L Thomas3,4, Janice L Holton2.
Abstract
Fluorinert (perfluorocarbon) represents an inexpensive option for minimizing susceptibility artifacts in ex vivo brain MRI scanning, and provides an alternative to Fomblin. However, its impact on fixed tissue and histological analysis has not been rigorously and quantitatively validated. In this study, we excised tissue blocks from 2 brain regions (frontal pole and cerebellum) of 5 formalin-fixed specimens (2 progressive supranuclear palsy cases, 3 controls). We excised 2 blocks per region per case (20 blocks in total), one of which was subsequently immersed in Fluorinert for a week and then returned to a container with formalin. The other block from each region was kept in formalin for use as control. The tissue blocks were then sectioned and histological analysis was performed on each, including routine stains and immunohistochemistry. Visual inspection of the stained histological sections by an experienced neuropathologist through the microscope did not reveal any discernible differences between any of the samples. Moreover, quantitative analysis based on automated image patch classification showed that the samples were almost indistinguishable for a state-of-the-art classifier based on a deep convolutional neural network. The results showed that Fluorinert has no effect on subsequent histological analysis of the tissue even after a long (1 week) period of immersion, which is sufficient for even the lengthiest scanning protocols.Entities:
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Year: 2018 PMID: 30364998 PMCID: PMC6234979 DOI: 10.1093/jnen/nly098
Source DB: PubMed Journal: J Neuropathol Exp Neurol ISSN: 0022-3069 Impact factor: 3.685
FIGURE 2.Zero vs 7-day exposure to Fluorinert in H&E and LFB-Nissl (objective ×20); and immunohistochemistry (MBP; objective ×20; AT8, SMI-31, GFAP; objective ×40). The H&E, LFB, MBP, SMI-31, and GFAP images represent a neurologically normal case. The AT8 images represent a PSP case; note that the tau inclusions are well delineated after 7 days of exposure to Fluorinert.
Demographics of the Cases Used in This Study
| Case | Gender | Age of Death | Post Mortem Interval | Fixation Time at Sample Collection | Findings From Histological Examination |
|---|---|---|---|---|---|
| Neurologically normal | Female | 84 | 41 hours | 546 days | Small vessel disease (mild) Low level AD Cerebral amyloid angiopathy (mild leptomeningeal and cortical) |
| Neurologically normal | Male | 80 | 12 hours | 545 days | Small vessel disease Atheroma Cerebral infarct Low level AD |
| Neurologically normal | Female | 94 | 27 hours | 617 days | Small vessel disease (moderate) Leptomeningeal vessel atheroma Low level AD |
| PSP | Male | 72 | 43 hours | 469 days | Small vessel disease TDP-43 proteinopathy |
| PSP | Male | 61 | 39 hours | 440 days | Lewy body pathology (limbic) Small vessel disease (mild) Argyrophilic grain disease |
AD, Alzheimer disease; PSP, progressive supranuclear palsy.
FIGURE 1.Experimental setup. The low-magnification images are interactively segmented by feeding brushstrokes to the Random Walker algorithm. The foreground mask is used to compute a min-max normalizing transform. Patches are then randomly sampled from the foreground and classified into exposed to Fluorinert vs not, by a deep convolutional neural network based on the widespread VGG-16 architecture.
Accuracy at Elbow and Area Under the Curve (AUC) for Classification of Image Patches From Day 0 vs Day 7 Using a Deep Convolutional Network Based on the Widespread VGG-16 Architecture
| Stain/Antibody and Objective Lens | Acc. Day 0 vs 7 (Same Stain) | AUC Day 0 vs 7 (Same Stain) | Average Accuracy vs Other Stains | Average AUC vs Other Stains |
|---|---|---|---|---|
| H&E | 55.12% | 0.569 | 99.84% (±0.06%) | 1.000 (±0.000) |
| LFB | 65.50% | 0.674 | 98.44% (±1.58%) | 0.998 (±0.002) |
| MBP | 50.09% | 0.451 | 90.83% (±9.81%) | 0.949 (±0.073) |
| AT8 | 50.06% | 0.410 | 91.74% (±10.05%) | 0.953 (±0.048) |
| SMI-31 | 50.38% | 0.453 | 94.98% (±6.63%) | 0.974 (±0.047) |
| GFAP | 51.84% | 0.500 | 92.21% (±7.09%) | 0.954 (±0.047) |
| H&E | 52.72% | 0.496 | 99.59% (±0.06%) | 1.000 (±0.000) |
| LFB | 59.85% | 0.605 | 96.57% (±3.15%) | 0.994 (±0.009) |
| MBP | 50.17% | 0.432 | 90.50% (±9.43%) | 0.943 (±0.077) |
| AT8 | 50.10% | 0.443 | 90.14% (±9.51%) | 0.940 (±0.076) |
| SMI-31 | 50.00% | 0.429 | 94.24% (±7.77%) | 0.971 (±0.053) |
| GFAP | 56.28% | 0.558 | 90.51% (±8.08%) | 0.940 (±0.056) |
The average classification accuracy and AUC across other stains (at the same magnification level) are given as a reference.