2019
A multimodal MRI-based classification signature emerges just prior to symptom onset in frontotemporal dementia mutation carriers
Publication
Publication
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.
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doi.org/10.1136/jnnp-2019-320774, hdl.handle.net/1765/117395 | |
VSNU Open Access deal | |
Journal of Neurology, Neurosurgery and Psychiatry: an international peer-reviewed journal for health professionals and researchers in all areas of neurology and neurosurgery | |
Organisation | Department of Neurology |
Feis, R. A., Bouts, M.J.R.J. (Mark J.R.J.), de Vos, F., Schouten, T. M., Panman, J., Jiskoot, L., … Rombouts, S. (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 |