Published November 3, 2025 | Version v1
Dataset Open

DBM/VBM-derived Atrophy Pattern Maps of Frontotemporal Dementia variants (bvFTD, svPPA, nfvPPA)

  • 1. ROR icon McGill University

Description

The files contain voxel-wise beta estimate and t-statistics maps contrasting deformation based morphometry (DBM) and voxel-based morphometry (VBM), and vertex-wise Cortical Thickness measurements of frontotemporal dementia (FTD) patients, separated by subtype diagnosis, against healthy controls. Age, Sex and Total Intracranial Volume were added as covariates in the model.

regional_results_all.csv contains regional results for the same model, based on regions of the CerebrA atlas. Methods included are DBM = indirect DBM, dirDBM = direct DBM, VBMindir = indirect VBM, VBMdir = direct VBM, CT = Cortical Thickness, Vol = FreeSurfer volumes.

BV = behavioral-variant Frontotemporal Dementia

SV = semantic-variant Primary Progressive Aphasia

PNFA = non-fluent-variant Primary Progressive Aphasia

FTD map is based on NIFD data, available at: https://ida.loni.usc.edu/login.jsp

DBM and VBM measures were derived using the PELICAN pipeline, Cortical Thickness and Volumes were derived using FreeSurfer version 7.4.1.

Maps have been linearly and nonlinearly registered to MNI-ICBM152 space. Nonlinear registration was performed either directly (individual -> ICBM, dirVBM/dirDBM files) or indirectly through a disease-specific template (individual -> FTD template -> ICBM, indirVBM/indirDBM files). 

 

For more information regarding the participants and method details, see:

Quantifying brain atrophy in Frontotemporal Dementia: a head-to-head comparison of neuroimaging techniques
Amelie Metz, Roqaie Moqadam, Yashar Zeighami, Louis Collins, Sylvia Villeneuve, Mahsa Dadar
medRxiv 2025.10.28.25339007; doi: https://doi.org/10.1101/2025.10.28.25339007
(see group differences model 2.4.3)
 
PELICAN: a Longitudinal Image Processing Pipeline for Analyzing Structural Magnetic Resonance Images in Aging and Neurodegenerative Disease Populations
Mahsa Dadar, Roqaie Moqadam, Amelie Metz, Katherine Chadwick, Aliza Brzezinski-Rittner, Yashar Zeighami
bioRxiv 2025.09.20.677546; doi: https://doi.org/10.1101/2025.09.20.677546
 
FreeSurfer. Fischl B.
Neuroimage. 2012 Aug 15;62(2):774-81. doi: 10.1016/j.neuroimage.2012.01.021
 
CerebrA, registration and manual label correction of Mindboggle-101 atlas for MNI-ICBM152 template. 
Manera, A.L., Dadar, M., Fonov, V. et al. Sci Data 7, 237 (2020). https://doi.org/10.1038/s41597-020-0557-9
 
NIFD/FTLDNI dataset: https://memory.ucsf.edu/research/studies/nifd

Files

LMvertex_results_all.csv

Files (347.1 MB)

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Additional details

Related works

Is supplement to
Publication: 10.1101/2025.10.28.25339007 (DOI)