Hey #ADPD2025 , I'm happy to present our work on characterizing brain atrophy and cerebrovascular pathology in Frontotemporal Dementia subtypes!

Tomorrow, April 5, 9:40am, Hall F2, session: Mechanisms and Clinical Trials in FTD, ALS, and Neurodegeneration 02

6/ To assess whether our model was adaptable for a clinical setting, we repeated our analyses while only including the CDR scales and one language test in the PLS and our classification model. Using these minimal variables, our model still achieved an accurate FTD subtype classification of 83.62!

4/ Linear regression models assessing the relationship between atrophy and cognition patterns in each participant confirmed that the association between the two differs between FTD subtypes (bvFTD, svPPA, and nfvPPA), allowing us to use these profiles in a machine learning classification algorithm 👍

3/ PLS results highlighted the involvement of frontal and temporal lobes and subcortical structures and linked atrophy in these regions to a decline in global cognitive function, language, and executive function.

2/ We analyzed MRI and cognitive data from 136 participants in the NIFD cohort. (Sub)cortical atrophy 🧠was assessed using deformation-based morphometry. We then applied partial least squares, using resulting atrophy/cognition patterns to determine the most likely FTD subtype of each participant.

Excited to share that the first project of my PhD was published in 🧠 @braincomms.bsky.social 🧠 !!
We showed that machine learning can effectively differentiate frontotemporal dementia subtypes combining brain atrophy and cognition 🎉
doi.org/10.1093/brai... (1/10)