Background: Multimodal MRI-based classification may aid early frontotemporal dementia (FTD) diagnosis. Recently, presymptomatic FTD mutation carriers, who have a high risk of developing FTD, were separated beyond chance level from controls using MRI-based classification. However, it is currently unknown how these scores from classification models progress as mutation carriers approach symptom onset. In this longitudinal study, we investigated multimodal MRI-based classification scores between presymptomatic FTD mutation carriers and controls. Furthermore, we contrasted carriers that converted during follow-up ('converters') and non-converting carriers ('non-converters'). Methods: We acquired anatomical MRI, diffusion tensor imaging and resting-state functional MRI in 55 presymptomatic FTD mutation carriers and 48 healthy controls at baseline, and at 2, 4, and 6 years of follow-up as available. At each time point, FTD classification scores were calculated using a behavioural variant FTD classification model. Classification scores were tested in a mixed-effects model for mean differences and differences over time. Results: Presymptomatic mutation carriers did not have higher classification score increase over time than controls (p=0.15), although carriers had higher FTD classification scores than controls on average (p=0.032). However, converters (n=6) showed a stronger classification score increase over time than non-converters (p<0.001). Conclusions: Our findings imply that presymptomatic FTD mutation carriers may remain similar to controls in terms of MRI-based classification scores until they are close to symptom onset. This proof-of-concept study shows the promise of longitudinal MRI data acquisition in combination with machine learning to contribute to early FTD diagnosis.

Additional Metadata
Keywords c9orf72, human, classification, diffusion tensor imaging, frontotemporal dementia, grn protein, human, machine learning, mapt protein, human, multimodal mri, resting-state functional mri
Persistent URL dx.doi.org/10.1136/jnnp-2019-320774, hdl.handle.net/1765/117395
Journal Journal of Neurology, Neurosurgery and Psychiatry: an international peer-reviewed journal for health professionals and researchers in all areas of neurology and neurosurgery
Citation
Feis, R.A, Bouts, M.J.R.J. (Mark J.R.J.), de Vos, F, Schouten, T.M. (Tijn M.), Panman, J.L. (Jessica L.), Jiskoot, L.C, … Rombouts, S.A.R.B. (2019). A multimodal MRI-based classification signature emerges just prior to symptom onset in frontotemporal dementia mutation carriers. Journal of Neurology, Neurosurgery and Psychiatry: an international peer-reviewed journal for health professionals and researchers in all areas of neurology and neurosurgery. doi:10.1136/jnnp-2019-320774