3D Mapping of TAU Neurofibrillary Tangle Pathology in the Human Medial Temporal Lobe

• Published in: 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI) pp. 1312 - 1316
• Main Authors: Yushkevich, Paul A., de Onzono Martin, Maria Mercedes Iniguez, Ittyerah, Ranjit, Lim, Sydney, Lavery, Madigan, Wang, Jiancong, Hung, Ling Yu, Vergnet, Nicolas, Ravikumar, Sadhana, Xie, Long, Dong, Mengjin, DeFlores, Robin, Cui, Salena, McCollum, Lauren, Ohm, Daniel T., Robinson, John L., Schuck, Theresa, Grossman, Murray, Tisdall, M. Dylan, Prabhakaran, Karthik, Mizsei, Gabor, Das, Sandhitsu R., Artacho-Perula, Emilio, del Mar Arroyo Jimenez, Maria, Lopez, Monica Munoz, Rabal, Maria Pilar Marcos, Romero, Francisco Javier Molina, Lee, Edward B., Trojanowski, John Q., Wisse, Laura E.M., Wolk, David A., Irwin, David J., Insausti, Ricardo
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-04-2020
• ISSN: 1945-8452
• DOI: 10.1109/ISBI45749.2020.9098462

Tau protein neurofibrillary tangles (NFT) are linked to neuronal and synaptic loss and cognitive decline in Alzheimer's disease (AD) and related dementias. In AD, NFT pathology is known to spread through the cortex in a characteristic pattern, starting in the medial temporal lobe. However, the exact 3D pattern of NFT progression has not been described, and capturing this pattern quantitatively can help inform in vivo AD imaging biomarkers. We present a computational framework for generating 3D maps of NFT load from ex vivo MRI and serial histology. Weakly supervised deep learning is used to detect NFTs on histology slides prepared with an anti-tau immunohistochemistry stain, and a multi-stage registration pipeline that leverages 3D printing is used for histology-MRI alignment. Derived maps of NFT density are strongly concordant with manual NFT counting, as well as categorical NFT severity ratings used for clinical diagnosis.