2023 American Academy of Neurology Abstract Website

Edoardo Spinelli¹, Alma Ghirelli⁶, Ilaria Bottale⁷, Silvia Basaia², Camilla Cividini², M. Antonietta Volonte³, Sebastiano Galantucci³, Giuseppe Magnani³, Francesca Caso³, Elisa Canu¹, Veronica Castelnovo¹, Paola Caroppo⁸, Sara Prioni⁹, Cristina Villa⁸, Keith Josephs¹⁰, Jennifer Whitwell¹⁰, Federica Agosta⁵, Massimo Filippi⁴
¹Neuroimaging Research Unit, Division of Neuroscience and Neurology Unit, ²Neuroimaging Research Unit, Division of Neuroscience, ³Neurology Unit, ⁴Neurology Unit, Neuroimaging Research Unit, Division of Neuroscience, Neurophysiology Service and Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, ⁵IRCCS San Raffaele Scientific Institute, ⁶Neuroimaging Research Unit, Division of Neuroscience, Neurology Unit, IRCCS San Raffaele Scientific Institute and Vita-Salute San Raffaele University, ⁷Vita - Salute San Raffaele University, ⁸Unit of Neurology 5 - Neuropathology, Fondazione IRCCS Istituto Neurologico Carlo Besta, ⁹Fondazione IRCCS Istituto Neurologico Carlo Besta, ¹⁰Mayo Clinic

Objective:

This study applied SFC to test the hypothesis that topological stepwise architecture propagating from the disease epicenter would shape patterns of grey matter (GM) atrophy in a cohort of patients with progressive supranuclear palsy (PSP).

Background:

MRI connectomics is an ideal tool to test the model of network-based spread of pathological protein aggregates in neurodegenerative disorders. Stepwise functional connectivity (SFC) is a graph-theory-based neuroimaging method, which detects whole-brain functional couplings of a selected region of interest, at increasing link-step topological distances.

Design/Methods:

Twenty-eight patients with PSP and 50 healthy controls underwent brain magnetic resonance imaging (MRI) on a 3T scanner, including 3D-T1 weighted and resting-state functional MRI sequences. GM was parcellated into 90 regions using the Automated Anatomical Labeling (AAL) atlas. Correlations between SFC architecture in controls and atrophy patterns in PSP patients were tested. The disease epicenter was identified as the peak of atrophy observed in an independent cohort of 13 cases with post mortem confirmation of PSP pathology, and used as seed region for SFC analysis.

Results:

The disease epicenter was identified in the left midbrain tegmental region. Compared with controls, PSP patients showed prevalent atrophy in the subcortical GM (mostly, in the thalami and caudate nuclei), but also in frontal, parietal and cerebellar cortical regions. For each region of the AAL atlas, a strong correlation was found between average link-step distance from the left midbrain in controls and mean normalized GM volume in PSP patients (r=0.37, p<0.001).

Conclusions:

Our findings demonstrate that the brain architectural topology, as described by SFC propagating from the disease epicenter, shapes the pattern of atrophic changes in PSP, supporting the view of a network-based pathology propagation in this disease and holding the promise to be used to model disease progression in future longitudinal studies.