Data For Scalco et al. Clinicopathological correlates of quantitative Amyloid-B Pathology in the Temporal Cortex: Machine learning analysis of 131 cases from an ADRC

Dataset containing 131 de-identified whole slide images (WSIs) with a respective data dictionary. 

Paper: Scalco, R., Oliveira, L.C., Lai, Z. et al. Machine learning quantification of Amyloid-β deposits in the temporal lobe of 131 brain bank cases. acta neuropathol commun 12, 134 (2024). https://doi.org/10.1186/s40478-024-01827-7

Details: A total of 131 .svs. WSIs, de-identified using svs-deidentifier v 0.9.1-beta (https://github.com/pearcetm/svs-deidentifier/releases). Dataset is uploaded in batches due to Zenodo data upload limitations.

Slide curation/preparation: All samples were retrieved from archives of the University of California, Davis Alzheimer’s Disease Center Brain Bank (https://www.ucdmc.ucdavis.edu/alzheimers/). Archival samples analyzed in this study were 5 μm formalin fixed, paraffin embedded sections of the superior and middle temporal gyrus from human brain. The tissue had been previously stained with an amyloid-β antibody (4G8, recognizing residues 17-24, BioLegend, formerly Covance) that were first pretreated with formic acid to rid samples of endogenous protein. All slides were digitized using an Aperio AT2 between 20x and 40x magnification.

Code: Please refer to https://github.com/ucdrubinet/BrainSec and https://github.com/keiserlab/plaquebox-paper