Background: Data from neuro-imaging techniques allow us to estimate a brain's age. Brain age is easily interpretable as “how old the brain looks”, and could therefore be an attractive communication tool for brain health in clinical practice. This study aimed to investigate its clinical utility by investigating the relationship between brain age and the main cognitive deficit in MS, i.e. information processing speed. Methods: A linear regression model was trained to predict age from brain MRI volumetric features and sex in a healthy control dataset (HC-train, n=1690). This model was used to predict brain age in two test sets: HC-test (n=50) and MS-test (n=201). Brain-Predicted Age Difference (BPAD) was calculated as BPAD=brain age minus chronological age. Information processing speed was assessed by the Symbol Digit Modalities Test (SDMT). Results: Brain age was significantly related to SDMT scores in the MS-test dataset (r=-0.45, p
Denissen, S, Engemann, DA, De Cock, A, Costers, L, Baijot, J, Laton, J, Penner, IK, Grothe, M, Kirsch, M, D'hooghe, MB, D'haeseleer, M, Dive, D, De Mey, J, Van Schependom, J, Sima, D & Nagels, G 2022, 'Brain age as a surrogate marker for IPS in MS', Multiple Sclerosis Journal, vol. 28, no. 2, O2, pp. 1-2. https://doi.org/10.1177/13524585221100731
Denissen, S., Engemann, D. A., De Cock, A., Costers, L., Baijot, J., Laton, J., Penner, I. K., Grothe, M., Kirsch, M., D'hooghe, M. B., D'haeseleer, M., Dive, D., De Mey, J., Van Schependom, J., Sima, D., & Nagels, G. (2022). Brain age as a surrogate marker for IPS in MS. Multiple Sclerosis Journal, 28(2), 1-2. Article O2. https://doi.org/10.1177/13524585221100731
@article{02c5b4928e434ad48065fff68331a37b,
title = "Brain age as a surrogate marker for IPS in MS",
abstract = "Background: Data from neuro-imaging techniques allow us to estimate a brain's age. Brain age is easily interpretable as “how old the brain looks”, and could therefore be an attractive communication tool for brain health in clinical practice. This study aimed to investigate its clinical utility by investigating the relationship between brain age and the main cognitive deficit in MS, i.e. information processing speed. Methods: A linear regression model was trained to predict age from brain MRI volumetric features and sex in a healthy control dataset (HC-train, n=1690). This model was used to predict brain age in two test sets: HC-test (n=50) and MS-test (n=201). Brain-Predicted Age Difference (BPAD) was calculated as BPAD=brain age minus chronological age. Information processing speed was assessed by the Symbol Digit Modalities Test (SDMT). Results: Brain age was significantly related to SDMT scores in the MS-test dataset (r=-0.45, p",
keywords = "biological marker, adult, age, brain, cognitive defect, conference abstract, controlled study, linear regression analysis, major clinical study, neuroimaging, nuclear magnetic resonance imaging, symbol digit modalities test, velocity",
author = "S. Denissen and D.A. Engemann and {De Cock}, A. and L. Costers and J. Baijot and J. Laton and I.K. Penner and M. Grothe and M. Kirsch and M.B. D'hooghe and M. D'haeseleer and D. Dive and {De Mey}, J. and {Van Schependom}, J. and D. Sima and G. Nagels",
year = "2022",
month = may,
day = "18",
doi = "10.1177/13524585221100731",
language = "English",
volume = "28",
pages = "1--2",
journal = "Multiple Sclerosis Journal",
issn = "1352-4585",
publisher = "SAGE Publications Ltd",
number = "2",
}