Staging of progressive supranuclear palsy-Richardson syndrome using MRI brain charts for the human lifespan.
Vincent PlancheBoris MansencalJose V ManjonWassilios G MeissnerThomas TourdiasPierrick CoupéPublished in: Brain communications (2024)
Brain charts for the human lifespan have been recently proposed to build dynamic models of brain anatomy in normal aging and various neurological conditions. They offer new possibilities to quantify neuroanatomical changes from preclinical stages to death, where longitudinal MRI data are not available. In this study, we used brain charts to model the progression of brain atrophy in progressive supranuclear palsy-Richardson syndrome. We combined multiple datasets ( n = 8170 quality controlled MRI of healthy subjects from 22 cohorts covering the entire lifespan, and n = 62 MRI of progressive supranuclear palsy-Richardson syndrome patients from the Four Repeat Tauopathy Neuroimaging Initiative (4RTNI)) to extrapolate lifetime volumetric models of healthy and progressive supranuclear palsy-Richardson syndrome brain structures. We then mapped in time and space the sequential divergence between healthy and progressive supranuclear palsy-Richardson syndrome charts. We found six major consecutive stages of atrophy progression: (i) ventral diencephalon (including subthalamic nuclei, substantia nigra, and red nuclei), (ii) pallidum, (iii) brainstem, striatum and amygdala, (iv) thalamus, (v) frontal lobe, and (vi) occipital lobe. The three structures with the most severe atrophy over time were the thalamus, followed by the pallidum and the brainstem. These results match the neuropathological staging of tauopathy progression in progressive supranuclear palsy-Richardson syndrome, where the pathology is supposed to start in the pallido-nigro-luysian system and spreads rostrally via the striatum and the amygdala to the cerebral cortex, and caudally to the brainstem. This study supports the use of brain charts for the human lifespan to study the progression of neurodegenerative diseases, especially in the absence of specific biomarkers as in PSP.
Keyphrases
- resting state
- functional connectivity
- white matter
- multiple sclerosis
- endothelial cells
- cerebral ischemia
- magnetic resonance imaging
- case report
- contrast enhanced
- high resolution
- newly diagnosed
- pluripotent stem cells
- magnetic resonance
- mass spectrometry
- parkinson disease
- big data
- computed tomography
- ejection fraction
- brain injury
- induced pluripotent stem cells
- deep learning
- machine learning
- cross sectional
- early onset
- artificial intelligence
- stress induced
- rna seq