A Machine Learning–Based Approach to Discrimination of Tauopathies Using [18F]PM‐PBB3 PET Images

• Published in: Movement disorders Vol. 37; no. 11; pp. 2236 - 2246
• Main Authors: Endo, Hironobu, Tagai, Kenji, Ono, Maiko, Ikoma, Yoko, Oyama, Asaka, Matsuoka, Kiwamu, Kokubo, Naomi, Hirata, Kosei, Sano, Yasunori, Oya, Masaki, Matsumoto, Hideki, Kurose, Shin, Seki, Chie, Shimizu, Hiroshi, Kakita, Akiyoshi, Takahata, Keisuke, Shinotoh, Hitoshi, Shimada, Hitoshi, Tokuda, Takahiko, Kawamura, Kazunori, Zhang, Ming‐Rong, Oishi, Kenichi, Mori, Susumu, Takado, Yuhei, Higuchi, Makoto
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01.11.2022; Wiley Subscription Services, Inc
• Subjects: Alzheimer Disease - diagnostic imaging; Alzheimer Disease - pathology; Alzheimer's disease; Amygdala; Brain - pathology; Fibrils; Globus pallidus; Humans; Learning algorithms; Machine Learning; Movement Disorders; Neurodegenerative diseases; Paralysis; Patients; Positron emission tomography; Progressive supranuclear palsy; Supranuclear Palsy, Progressive - pathology; tau PET; Tau protein; tau Proteins - metabolism; Tauopathies - diagnostic imaging; Tauopathies - pathology; tauopathy; tauopathy; machine learning; Alzheimer's disease; tau PET; progressive supranuclear palsy
• ISSN: 0885-3185; 1531-8257
• DOI: 10.1002/mds.29173

ABSTRACT Background We recently developed a positron emission tomography (PET) probe, [18F]PM‐PBB3, to detect tau lesions in diverse tauopathies, including mixed three‐repeat and four‐repeat (3R + 4R) tau fibrils in Alzheimer's disease (AD) and 4R tau aggregates in progressive supranuclear palsy (PSP). For wider availability of this technology for clinical settings, bias‐free quantitative evaluation of tau images without a priori disease information is needed. Objective We aimed to establish tau PET pathology indices to characterize PSP and AD using a machine learning approach and test their validity and tracer capabilities. Methods Data were obtained from 50 healthy control subjects, 46 patients with PSP Richardson syndrome, and 37 patients on the AD continuum. Tau PET data from 114 regions of interest were subjected to Elastic Net cross‐validation linear classification analysis with a one‐versus‐the‐rest multiclass strategy to obtain a linear function that discriminates diseases by maximizing the area under the receiver operating characteristic curve. We defined PSP‐ and AD‐tau scores for each participant as values of the functions optimized for differentiating PSP (4R) and AD (3R + 4R), respectively, from others. Results The discriminatory ability of PSP‐ and AD‐tau scores assessed as the area under the receiver operating characteristic curve was 0.98 and 1.00, respectively. PSP‐tau scores correlated with the PSP rating scale in patients with PSP, and AD‐tau scores correlated with Mini‐Mental State Examination scores in healthy control–AD continuum patients. The globus pallidus and amygdala were highlighted as regions with high weight coefficients for determining PSP‐ and AD‐tau scores, respectively. Conclusions These findings highlight our technology's unbiased capability to identify topologies of 3R + 4R versus 4R tau deposits. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society