A multimodal MRI-based classification signature emerges just prior to symptom onset in frontotemporal dementia mutation carriers.

Autor:	Feis RA; Department of Radiology, Leiden University Medical Centre, Leiden, The Netherlands r.a.feis@lumc.nl.; Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands.; Institute of Psychology, Leiden University, Leiden, The Netherlands., Bouts MJRJ; Department of Radiology, Leiden University Medical Centre, Leiden, The Netherlands.; Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands.; Institute of Psychology, Leiden University, Leiden, The Netherlands., de Vos F; Department of Radiology, Leiden University Medical Centre, Leiden, The Netherlands.; Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands.; Institute of Psychology, Leiden University, Leiden, The Netherlands., Schouten TM; Department of Radiology, Leiden University Medical Centre, Leiden, The Netherlands.; Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands.; Institute of Psychology, Leiden University, Leiden, The Netherlands., Panman JL; Department of Radiology, Leiden University Medical Centre, Leiden, The Netherlands.; Department of Neurology, Erasmus Medical Centre, Rotterdam, The Netherlands., Jiskoot LC; Department of Radiology, Leiden University Medical Centre, Leiden, The Netherlands.; Department of Neurology, Erasmus Medical Centre, Rotterdam, The Netherlands., Dopper EGP; Department of Neurology, Erasmus Medical Centre, Rotterdam, The Netherlands., van der Grond J; Department of Radiology, Leiden University Medical Centre, Leiden, The Netherlands., van Swieten JC; Department of Neurology, Erasmus Medical Centre, Rotterdam, The Netherlands.; Department of Clinical Genetics, VU University Medical Centre, Amsterdam, The Netherlands., Rombouts SARB; Department of Radiology, Leiden University Medical Centre, Leiden, The Netherlands.; Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands.; Institute of Psychology, Leiden University, Leiden, The Netherlands.
Jazyk:	angličtina
Zdroj:	Journal of neurology, neurosurgery, and psychiatry [J Neurol Neurosurg Psychiatry] 2019 Nov; Vol. 90 (11), pp. 1207-1214. Date of Electronic Publication: 2019 Jun 15.
DOI:	10.1136/jnnp-2019-320774
Abstrakt:	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. Competing Interests: Competing interests: None declared. (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)
Databáze:	MEDLINE
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