Neurofibrillary Tangles Prediction Based On MRI

Abstract Background Neurofibrillary tangles, one of the hallmark pathologies of Alzheimer’s disease, are closely related to brain atrophy and cognitive decline. The purpose of this work was to develop an MRI‐based classifier of neurofibrillary tangles by combining ex‐vivo MRI and neuropathology in brain autopsies from a large number of community‐based older adults. Method Cerebral hemispheres from 878 older adults participating in three longitudinal, clinical pathologic cohort studies of aging: the Rush Memory and Aging Project (MAP), the Religious Orders Study (ROS), and the Minority Aging Research Study (MARS) (Fig. 1) were included in this work. All hemispheres were imaged at room temperature while immersed in 4% formaldehyde solution using clinical 3T MRI scanners, once within 24 hours postmortem and a second time approximately 30 days postmortem followed by detailed neuropathologic examination. An SVM classifier with l2 regularization was trained to distinguish participants at a Braak stage of V‐VI from those at a Braak stage of 0‐IV, based on features extracted from ex‐vivo MRI as well as demographic information (age, sex). The MRI features included volumetric, cortical thickness, subcortical shape, diffusion, and R2 measurements. When a feature contained multiple measurements per person, they were used to train a separate model that generated a separate risk score which was used as a feature in the final model. Because different groupings of features were available on different subgroups of the participants, the performance of the classifier was tested in a total of 74 participants (Fig. 2) that had measurements on all features. Result The average AUC of the classifier based on all MRI and demographic features was 0.87 with 82% mean sensitivity and 77% mean specificity (Fig. 3). In comparison, recently published work combining in‐vivo MRI and pathology data trained an MRI‐based classifier of people at Braak stage V‐VI vs. 0‐II and achieved an AUC=0.69 [1]. Conclusion Successful completion of ex‐vivo to in‐vivo translation of our work may result in a non‐invasive classifier of neurofibrillary tangles aiding in refined participant selection and targeted therapies. Reference: [1] Dallaire‐Théroux, Caroline et al., Braak neurofibrillary tangle staging prediction from in vivo MRI metrics, Alzheimer's & dementia, vol. 11, 2019.