A multimodal MRI-based classification signature emerges just prior to symptom onset in frontotemporal dementia mutation carriers. Issue 11 (15th June 2019)

• Record Type: Journal Article
• Authors: Feis, Rogier A; Bouts, Mark J R J; de Vos, Frank; Schouten, Tijn M; Panman, Jessica L; Jiskoot, Lize C; Dopper, Elise G P; van der Grond, Jeroen; van Swieten, John C; Rombouts, Serge A R B
• Is Part Of: Journal of neurology, neurosurgery and psychiatry. Volume 90:Issue 11(2019)
• Page Start: 1207
• Page End: 1214
• Publication Date: 2019-06-15
• Subjects: frontotemporal dementia -- mapt protein, human -- grn protein, human -- c9orf72, human -- diffusion tensor imaging -- resting-state functional mri -- multimodal mri -- classification -- machine learning; Neurology -- Periodicals; Nervous system -- Surgery -- Periodicals; Psychiatry -- Periodicals; 616.8
• DOI: 10.1136/jnnp-2019-320774
• Languages: English
• ISSNs: 0022-3050

Abstract

Abstract : 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.