Anatomical MRI staging of frontotemporal dementia variants

Planche, Vincent; Mansencal, Boris; Manjón, José V.; Tourdias, Thomas; Catheline, Gwénaëlle; Coupé, Pierrick

doi:10.1002/alz.12975

Cited by 12 publications

(16 citation statements)

References 51 publications

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“…One significant contribution of our study lies in utilizing over 700 core volumes, all coregistered within the same standard space, to infer longitudinal profiles of untreated stroke progression, drawing inspiration from methodologies applied in other domains (15)(16)(17)(18). In contrast to previous efforts that employed linear fitting (32), which simplifies the complex biological processes at play, we employed smooth curve fitting.…”

Section: Discussionmentioning

confidence: 99%

“…Only few data reported two imaging sessions prior to recanalization (14). An alternative method would consist of inferring pseudo-longitudinal profiles from the concatenation of a large number of homogeneous cross-sectional data collected before recanalization akin to strategies used recently to map the typical evolution of brain volume across the lifespan (15, 16) or in neurodegenerative diseases (17, 18). Indeed, if we could objectively attribute stroke patients presenting the same clot location to a specific growth phenotype, then, we could reconstruct stereotypical growth curves from such homogeneous cluster of patients explored at different time points after the onset of symptoms.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic evolution of infarct volumes at MRI in ischemic stroke due to large vessel occlusion

Munsch,

Planes,

Fukutomi

et al. 2023

Preprint

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Background and ObjectivesThe typical infarct volume trajectories in stroke patients, categorized as slow or fast progressors, remain largely unknown. This study aimed to reveal the characteristic spatiotemporal evolutions of infarct volumes caused by large vessel occlusion (LVO) and show that such growth charts help anticipate clinical outcomes.MethodsWe conducted a secondary analysis from prospectively collected databases (FRAME, 2017– 2019; ETIS, 2015–2022). We selected acute MRI data from anterior LVO stroke patients with witnessed onset which were divided into training- and independent validation-datasets. In the training-dataset, using Gaussian mixture analysis, we classified the patients into three growth groups based on their rate of infarct growth (diffusion volume / time-to-imaging). Subsequently, we extrapolated pseudo-longitudinal models of infarct growth for each group and generated sequential frequency maps to highlight the spatial distribution of infarct growth. We used these charts to attribute a growth group to the independent patients from the validation-dataset. We compared their 3-month modified Rankin scale (mRS) with the predicted values based on a multivariable regression model from the training-dataset that used growth group as independent variable.ResultsWe included 804 patients (median age, 73.0 years [IQR, 61.2-82.0 years]; 409 men). The training-dataset revealed non-supervised clustering into 11% (74/703) slow, 62% (437/703) intermediate, and 27% (192/703) fast progressors. Infarct volume evolutions were best fitted with a linear (r=0.809;P<.001), cubic (r=0.471;P<.001), and power (r=0.63;P<.001) functions for the slow, intermediate and fast progressors, respectively. Notably, the deep nuclei and insular cortex were rapidly affected in the intermediate and fast groups with further cortical involvement in the fast group. The variable “growth group” significantly predicted 3-month mRS (multivariate OR, 0.51; 95% CI: 0.37-0.72,P<.0001) in the training-dataset, yielding a mean AUC of 0.78 (95% CI: 0.66-0.88) in the independent validation-dataset.ConclusionsWe revealed spatiotemporal archetype dynamic evolutions following large vessel occlusion stroke according to three growth phenotypes called slow, intermediate and fast progressors, providing insight into anticipating clinical outcome. We expect this could help in designing neuroprotective trials aiming at modulating infarct growth prior EVT.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic evolution of infarct volumes at MRI in ischemic stroke due to large vessel occlusion

Munsch,

Planes,

Fukutomi

et al. 2023

Preprint

Self Cite

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“…To study brain volumetric trajectories of PSP-RS across the entire lifespan and to extrapolate the early stages of PSP-RS, we followed the strategy we have previously proposed for Alzheimer’s disease and FTD. 18 , 19 Our framework was based on the assumption that neurodegeneration is a continuous and progressive process along disease progression. Therefore, to constrain the volumetric trajectories over the entire lifespan, we built our PSP-RS models using control MRIs taken before the age of the youngest patient.…”

Section: Methodsmentioning

confidence: 99%

“…Thanks to this methodology and its validation using ‘truly’ longitudinal data, we have recently proposed the anatomical MRI staging of Alzheimer’s disease 18 and the three clinical variants of frontotemporal dementia (FTD). 19 Here, we describe the progressive pattern of neuroanatomical variations between PSP-RS and normal aging.…”

Section: Introductionmentioning

confidence: 99%

Staging of progressive supranuclear palsy-Richardson syndrome using MRI brain charts for the human lifespan

Planche,

Mansencal,

Manjon

et al. 2024

Brain Communications

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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 (PSP-RS). We combined multiple datasets (n = 8170 quality controlled MRI of healthy subjects from 22 cohorts covering the entire lifespan, and n = 62 MRI of PSP-RS patients from the 4 Repeat Tauopathy Neuroimaging Initiative) to extrapolate lifetime volumetric models of healthy and PSP-RS brain structures. We then mapped in time and space the sequential divergence between healthy and PSP-RS 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 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 PSP-RS, 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.

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“…It has been reported that the peak atrophy in SD at baseline was in the TPOsup, extending to the left middle temporal and ITG, fusiform, AMYG, and anterior cingulate cortex; With disease progression, atrophy becomes more distributed to the middle and inferior frontal lobes, posterior temporal gyrus, and inferior parietal areas (Collins et al, 2017;Peet et al, 2021;Planche et al, 2023). Although it has been widely accepted that SD is associated with predominant atrophy of ATL, limited evidence is available regarding both the structural and functional network abnormalities, especially the changes with disease progression.…”

Section: Disrupted Organization Of Structural and Functional Network ...mentioning

confidence: 99%

Functional and structural network changes related with cognition in semantic dementia longitudinally

Lin

Cui

Chen

et al. 2023

Human Brain Mapping

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Longitudinal changes in the white matter/functional brain networks of semantic dementia (SD), as well as their relations with cognition remain unclear. Using a graph‐theoretic method, we examined the neuroimaging (T1, diffusion tensor imaging, functional MRI) network properties and cognitive performance in processing semantic knowledge of general and six modalities (i.e., object form, color, motion, sound, manipulation and function) from 31 patients (at two time points with an interval of 2 years) and 20 controls (only at baseline). Partial correlation analyses were carried out to explore the relationships between the network changes and the declines of semantic performance. SD exhibited aberrant general and modality‐specific semantic impairment, and gradually worsened over time. Overall, the brain networks showed a decreased global and local efficiency in the functional network organization but a preserved structural network organization with a 2‐year follow‐up. With disease progression, both structural and functional alterations were found to be extended to the temporal and frontal lobes. The regional topological alteration in the left inferior temporal gyrus (ITG.L) was significantly correlated with general semantic processing. Meanwhile, the right superior temporal gyrus and right supplementary motor area were identified to be associated with color and motor‐related semantic attributes. SD manifested disrupted structural and functional network pattern longitudinally. We proposed a hub region (i.e., ITG.L) of semantic network and distributed modality‐specific semantic‐related regions. These findings support the hub‐and‐spoke semantic theory and provide targets for future therapy.

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Anatomical MRI staging of frontotemporal dementia variants

Cited by 12 publications

References 51 publications

Dynamic evolution of infarct volumes at MRI in ischemic stroke due to large vessel occlusion

Dynamic evolution of infarct volumes at MRI in ischemic stroke due to large vessel occlusion

Staging of progressive supranuclear palsy-Richardson syndrome using MRI brain charts for the human lifespan

Functional and structural network changes related with cognition in semantic dementia longitudinally

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