个人简介

I received my training as a radiologist at VU University Medical Centre in Amsterdam the Netherlands, where I hold the chair of Neuroradiology since 2001. In 2015, have been appointed as Chair or Neuroradiology at UCL across the institutes of Neurology (Brain Repair & Rehabilitation) and Biomedical Engineering (TIG/CMIC) to translate novel brain images analysis techniques to clinical applications and trial outcomes.

研究领域

CNS disorders including Dementia and Multiple Sclerosis emphasis on novel imaging approaches to diagnose and prognosticate patients understanding disease mechanisms and their modification by treatment

My research focuses on CNS disorders including Dementia and Multiple Sclerosis with an emphasis on novel imaging approaches to diagnose and prognosticate patients, but equelly to understand disease mechanisms and their modification by treatment. Ongoing projects and activities include

近期论文

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Vijverberg, E.G.B., Tijms, B.M., Dopp, J., Hong, Y.J., Teunissen, C.E., Barkhof, F., ...Pijnenburg, Y.A.L. (2017). Gray matter network differences between behavioral variant frontotemporal dementia and Alzheimer's disease.. Neurobiology of Aging, 50 77-86. doi:10.1016/j.neurobiolaging.2016.11.005 Salome, M., Barkhof, F., Visser, L. (2017). Hirayama disease; an atypical clinical manifestation of a cervical myelopathy with typical MRI features.. BMJ Case Rep, 2017 doi:10.1136/bcr-2016-217780 Hafkemeijer, A., Möller, C., Dopper, E.G., Jiskoot, L.C., van den Berg-Huysmans, A.A., van Swieten, J.C., ...Barkhof, F. (2016). A Longitudinal Study on Resting State Functional Connectivity in Behavioral Variant Frontotemporal Dementia and Alzheimer's Disease.. Journal of Alzheimer's disease : JAD, Cohn-Hokke, P.E., Holstege, H., Weiss, M.M., van der Flier, W.M., Barkhof, F., Sistermans, E.A., ...Scheltens, P. (2016). A novel CCM2 variant in a family with non-progressive cognitive complaints and cerebral microbleeds. American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics, doi:10.1002/ajmg.b.32468 Qin, C., Moreno, R.G., Bowles, C., Ledig, C., Scheltens, P., Barkhof, F., ...Van Der Flier, W.M. (2016). A semi-supervised large margin algorithm for white matter hyperintensity segmentation. Verburg, N., Pouwels, P.J.W., Boellaard, R., Barkhof, F., Hoekstra, O.S., Reijneveld, J.C., ...De Witt Hamer, P.C. (2016). Accurate Delineation of Glioma Infiltration by Advanced PET/MR Neuro-Imaging (FRONTIER Study): A Diagnostic Study Protocol. Neurosurgery, 79 (4), 535-540. doi:10.1227/NEU.0000000000001355 van Bloemendaal, L., Ijzerman, R.G., ten Kulve, J.S., Barkhof, F., Diamant, M., Veltman, D.J., van Duinkerken, E. (2016). Alterations in white matter volume and integrity in obesity and type 2 diabetes. Metabolic Brain Disease, 31 (3), 621-629. doi:10.1007/s11011-016-9792-3 Möller, C., Pijnenburg, Y.A., van der Flier, W.M., Versteeg, A., Tijms, B., de Munck, J.C., ...van Swieten, J. (2016). Alzheimer Disease and Behavioral Variant Frontotemporal Dementia: Automatic Classification Based on Cortical Atrophy for Single-Subject Diagnosis.. Radiology, 279 (3), 838-848. Arrighi, H.M., Barakos, J., Barkhof, F., Tampieri, D., Jack, C., Melançon, D., ...Brashear, H.R. (2016). Amyloid-related imaging abnormalities-haemosiderin (ARIA-H) in patients with Alzheimer's disease treated with bapineuzumab: A historical, prospective secondary analysis. Journal of Neurology, Neurosurgery and Psychiatry, 87 (1), 106-112. doi:10.1136/jnnp-2014-309493 Collij, L.E., Heeman, F., Kuijer, J.P., Ossenkoppele, R., Benedictus, M.R., Möller, C., ...van der Flier, W.M. (2016). Application of Machine Learning to Arterial Spin Labeling in Mild Cognitive Impairment and Alzheimer Disease.. Radiology, 152703. Haller, S., Zaharchuk, G., Thomas, D.L., Lovblad, K.O., Barkhof, F., Golay, X. (2016). Arterial Spin Labeling Perfusion of the Brain: Emerging Clinical Applications.. Radiology, 281 (2), 337-356. doi:10.1148/radiol.2016150789 Chételat, G., Ossenkoppele, R., Villemagne, V.L., Perrotin, A., Landeau, B., Mézenge, F., ...Egret, S. (2016). Atrophy, hypometabolism and clinical trajectories in patients with amyloid-negative Alzheimer's disease.. Brain : a journal of neurology, Barkhof, F. (2016). Brain atrophy measurements should be used to guide therapy monitoring in MS - NO. MULTIPLE SCLEROSIS JOURNAL, 22 (12), 1524-1526. doi:10.1177/1352458516649452 Rimkus, C.D.M., Steenwijk, M.D., Barkhof, F. (2016). Causes, effects and connectivity changes in MS-related cognitive decline. Dementia e Neuropsychologia, 10 (1), 2-11. Binnewijzend, M.A.A., Benedictus, M.R., Kuijer, J.P.A., van der Flier, W.M., Teunissen, C.E., Prins, N.D., ...Barkhof, F. (2016). Cerebral perfusion in the predementia stages of Alzheimer’s disease. European Radiology, 26 (2), 506-514. doi:10.1007/s00330-015-3834-9 Jokinen-Salmela, H., Melkas, S., Madureira, S., Verdelho, A., Ferro, J.M., Fazekas, F., ...Wardlaw, J.M. (2016). Cognitive reserve moderates long-term cognitive and functional outcome in cerebral small vessel disease. Journal of Neurology, Neurosurgery and Psychiatry, doi:10.1136/jnnp-2016-313914 Steenwijk, M.D., Geurts, J.J.G., Daams, M., Tijms, B.M., Wink, A.M., Balk, L.J., ...Vrenken, H. (2016). Cortical atrophy patterns in multiple sclerosis are non-random and clinically relevant. Brain, 139 (1), 115-126. doi:10.1093/brain/awv337 Sormani, M.P., Kappos, L., Radue, E.W., Cohen, J., Barkhof, F., Sprenger, T., ...De Stefano, N. (2016). Defining brain volume cutoffs to identify clinically relevant atrophy in RRMS.. Multiple sclerosis (Houndmills, Basingstoke, England), Scheltens, N.M.E., Kuyper, I.S., Boellaard, R., Barkhof, F., Teunissen, C.E., Broersen, L.M., ...Scheltens, P. (2016). Design of the NL-ENIGMA study: Exploring the effect of Souvenaid on cerebral glucose metabolism in early Alzheimer's disease. Alzheimer's and Dementia: Translational Research and Clinical Interventions, 2 (4), 233-240. doi:10.1016/j.trci.2016.07.004 Vijverberg, E.G.B., Wattjes, M.P., Dols, A., Krudop, W.A., Möller, C., Peters, A., ...Stek, M.L. (2016). Diagnostic Accuracy of MRI and Additional [18F]FDG-PET for Behavioral Variant Frontotemporal Dementia in Patients with Late Onset Behavioral Changes. Journal of Alzheimer's Disease, 53 (4), 1287-1297. doi:10.3233/JAD-160285 Vijverberg, E.G.B., Dols, A., Krudop, W.A., Peters, A., Kerssens, C.J., Van Berckel, B.N.M., ...Prins, N.D. (2016). Diagnostic accuracy of the frontotemporal dementia consensus criteria in the late-onset frontal lobe syndrome. Dementia and Geriatric Cognitive Disorders, 41 (3-4), 210-219. doi:10.1159/000444849 Gardeniers, M., Wattjes, M.P., Meulen, E.F.J., Barkhof, F., Bakker, J. (2016). Diagnostic imaging in dementia: use of imaging modalities in Dutch memory clinics. Tijdschrift voor Gerontologie en Geriatrie, 47 (1), 2-8. doi:10.1007/s12439-015-0154-0 Hafkemeijer, A., Möller, C., Dopper, E.G.P., Jiskoot, L.C., van den Berg-Huysmans, A.A., van Swieten, J.C., ...Barkhof, F. (2016). Differences in structural covariance brain networks between behavioral variant frontotemporal dementia and Alzheimer's disease. Human Brain Mapping, 37 (3), 978-988. doi:10.1002/hbm.23081 Ledig, C., Kaltwang, S., Tolonen, A., Koikkalainen, J., Scheltens, P., Barkhof, F., ...van der Flier, W. (2016). Differential dementia diagnosis on incomplete data with latent trees. Koikkalainen, J., Rhodius-Meester, H., Tolonen, A., Barkhof, F., Tijms, B., Lemstra, A.W., ...Ledig, C. (2016). Differential diagnosis of neurodegenerative diseases using structural MRI data. NeuroImage: Clinical, 11 435-449. doi:10.1016/j.nicl.2016.02.019