Expertise

your imaging partner in clinical routine, clinical trials and research studies

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Traumatic brain injury

Quantification of mass effects (midline shift, mass lesion volumetry)

Stroke

Quantification and prediction of core and penumbra

Dementia

Quantification of whole brain volume

MRI

Epilepsy

Quantification of focal cortical dysplasia and mesial temporal sclerosis

multiple sclerosis

Quantification of atrophy and lesions in brain and spinal cord

Brain tumors

Volumetric quantification of brain tumors

Dementia

Quantification of brain atrophy and different cortical subregions

Traumatic brain injury

Quantification of brain atrophy and traumatic axonal injuries

Brain development

Quantification of anatomical structures (cortical and subcortical)

Advanced MRI

Brain diffusion

Diffusion imaging reveals the brain's micro-structure

Brain perfusion

Arterial spin labelling (ASL), dynamic susceptibility contrast (DSC), dynamic contract enhancement (DCE) allow quantification of the cerebral blood flow

Brain function

Functional MRI assesses brain activity during tasks (task-related fMRI) and rest (resting state fMRI)

Brain myelination

Magnetization transfer imaging (MTR) and myelin water imaging provide insights in demyelination processes

Brain metabolites

MR Spectroscopy (MRS) provides a ‘virtual biopsy’ by measuring the concentrations of chemicals in the brain.
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Recent publications

Automatic segmentation and volumetry of multiple sclerosis brain lesions from MR images, NeuroImage Clinical, 2015 May 16;8:367-75
Jain S., Sima D., Ribbens A., Cambron M., Maertens A., Van Hecke W., Vrenken H., De Mey J., Maes F., Van Huffel S., Barkhof F., Smeets D.
CENTER-TBI Participants and Investigators. Collaborative European NeuroTrauma Effectiveness Research in traumatic brain injury (CENTER-TBI): A Prospective Longitudinal Observational Study, Neurosurgery. 2015 Jan;76(1):67-80
Maas A.I., Menon D.K., Steyerberg E.W., Citerio G., Lecky F., Manley G.T., Hill S., Legrand V., Sorgner A.
Image registration using mutual information, Handbook of Biomedical Imaging, 2015, 295-308
Maes F., Loeckx D., Vandermeulen D., Suetens P.
Stability of resting state networks in the female brain during hormonal changes and their relation to premenstrual symptoms, Brain Res. 2015 Oct 22;1624:275-285
De Bondt T., Smeets D., Pullens P., Van Hecke W., Jacquemyn Y., Parizel P.M..
Mindfulness Training among Individuals with Parkinson’s Disease: Neurobehavioral Effects, Parkinson’s Disease, 2015:816404
Pickut B., Vanneste S., Hirsch M.A., Van Hecke W., Kerckhofs E., Mariën P., Parizel P.M., Crosiers D., Cras P.
Diffusion Kurtosis Imaging: A Possible MRI Biomarker for AD Diagnosis? J Alzheimers Dis. 2015;48(4):937-48
Struyfs H., Van Hecke W., Veraart J., Sijbers J., Slaets S., De Belder M., Wuyts L., Peters B., Sleegers K., Robberecht C., Van Broeckhoven C., De Belder F., Parizel P.M., Engelborghs S.
Two Time Point MS Lesion Segmentation in Brain MRI: An Expectation-Maximization Framework, Frontiers in Neuroscience: Brain Imaging Methods, 2016 Dec 19;10:576
Jain S., Ribbens A., Sima D., Cambron M., De Keyser J., Wang C., Barnett M., Van Huffel S., Maes F., Smeets D.
Reliable measurements of brain atrophy in individual patients with multiple sclerosis, Brain and Behavior 2016 Jul 19;6(9):e00518Psychopathology, Biological Psychiatry, volume 77, issue 9, pages 388S-388S, 2015.
Smeets D., Ribbens A., Sima D., Cambron M., Horakova D., Jain S., Maertens A., Van Vlierberghe E., Popescu V., Terzopoulos V., Van Binst A., Vaneckova M., Krasensky J., Uher T., Seidl Z., De Keyser J., Nagels G., De Mey J., Havrdova E., Van Hecke W.
Reliability of measuring regional callosal atrophy in neurodegenerative diseases, NeuroImage Clinical 2016, Oct 15;12:825-831
Van Schependom J., Jain S., Cambron M. Vanbinst A., De Mey J., Smeets D., Nagels G.
Quantifying brain volumes for multiple sclerosis patients follow‐up in clinical practice – comparison of 1.5 and 3 Tesla magnetic resonance imaging. Brain and Behavior. 2016;6(2):e00422. doi:10.1002/brb3.422
Lysandropoulos A.P., Absil J., Metens T., Mavroudakis N., Guisset F., Van Vlierberghe E., Smeets D., David P., Maertens A., Van Hecke W.
Cerebral and cerebellar language organization in a right-handed subject with a left temporal porencephalic cyst: An fMRI study, Journal of Neurolinguistics, 2016 Feb;37,41-4
De Coninck M., Van Hecke W., Crols R., Van Dun K., Van Dam D., De Deyn P., Brysbaert M., Mariën P.
Ter Haar Romeny B.M., Goraj B.M., Platel B., Automated detection of cerebral microbleeds in patients with traumatic brain injury, NeuroImage: Clinical 2016 Jul 2;12:241-51.
van den Heuvel T.L., van der Eerden A.W., Manniesing R., Ghafoorian M., Tan T., Andriessen T.M., Vande Vyvere T., van den Hauwe L.
Diffusion tensor imaging: a practical handbook, 2016
Van Hecke W., Emsell L., Sunaert S.
Use Case I: Imaging Biomarkers in Neurological Disease. Focus on multiple sclerosis, Imaging Biomarkers, 2016, pp 169-180
Sima D., Loeckx D., Smeets D., Jain S., Parizel P. M., Van Hecke W.
Patch-based super-resolution of MR spectroscopic images: Application to multiple sclerosis, Frontiers in Neuroscience 2017 Jan 31;11:13
Jain, S., Sima, D.M., Sanaei Nezhad, F., Hangel, G., Bogner, W., Williams, S., Van Huffel, S., Maes, F. and Smeets, D.
Processing of structural neuroimaging data in young children: bridging the gap between current practice and state-of-the-art methods, Developmental Cognitive Neuroscience, 2017 Aug 24. pii: S1878-9293(16)30242-0
Phan, V., Smeets, D., Talcott, J., and Vandermosten, M.
The effect of morphological and microstructural integrity of the corpus callosum on cognition, fatigue and depression in mildly disabled MS patients, Magn Reson Imaging. 2017 Jul;40:109-114
Van Schependom J., Gielen J., Laton J., Sotiropoulos G., Vanbinst A.M., De Mey J., Smeets D., Nagels G.
Longitudinal multiple sclerosis lesion segmentation: resource & challenge, NeuroImage 2017 Mar 1;148:77-102
Carassa, A., Roy, S., Jog, A., Cuzzocreo, J.L., Magrath, E., Gherman, A., Button, J., Nguyen, J., Prados, F., Sudre, C.H., Cardoso, M.J., Cawley, N., Ciccarelli, O., Wheeler-Kingshott, C.A.M., Ourselin, S.,Catanesei, L., Deshpande, H., Maureli, P., Commowick, O., Barillot, C., Tomas-Fernandez, X., Warfield, S.K., Vaidya, S., Chunduru, A., Muthuganapathy, R., Krishnamurthi, G., Jesson, A., Arbel, T., Maier, O., Handels H., Iheme, L.O., Unay, D., Jain, S., Sima, D.M., Smeets, D., Ghafoorian, M., Platel, B., Birenbaum, A., Greenspan, H., Bazin, P-L., Calabresi,P.A., Crainiceanu, C.M., Ellingsena, L.M., Reichd, D.S., Prince, J.L., and Pham D.L.
HLA genotype as a marker of multiple sclerosis prognosis: A pilot study, J Neurol Sci. 2017 Apr 15;375:348-354
Lysandropoulos A.P., Mavroudakis N., Pandolfo M., El Hafsi K., Van Hecke W., Maertens A., Billiet T., Ribbens A.
The effect of task modality and stimulus frequency in paced serial addition tests on functional brain activity, PLoS One. 2018 Mar 15;13(3):e0194388
Gielen J., Wiels W., Van Schependom J., Laton J., Van Hecke W., Parizel P.M., D'hooghe M.B., Nagels G.
InTBIR Participants and Investigators, Traumatic brain injury: integrated approaches to improve prevention, clinical care, and research, Lancet Neurol. 2017 Dec;16(12):987-1048
Maas AIR, Menon DK, Adelson PD, Andelic N, Bell MJ, Belli A, Bragge P, Brazinova A, Büki A, Chesnut RM, Citerio G, Coburn M, Cooper DJ, Crowder AT, Czeiter E, Czosnyka M, Diaz-Arrastia R, Dreier JP, Duhaime AC, Ercole A, van Essen TA, Feigin VL, Gao G, Giacino J, Gonzalez-Lara LE, Gruen RL, Gupta D, Hartings JA, Hill S, Jiang JY, Ketharanathan N, Kompanje EJO, Lanyon L, Laureys S, Lecky F, Levin H, Lingsma HF, Maegele M, Majdan M, Manley G, Marsteller J, Mascia L, McFadyen C, Mondello S, Newcombe V, Palotie A, Parizel PM, Peul W, Piercy J, Polinder S, Puybasset L, Rasmussen TE, Rossaint R, Smielewski P, Söderberg J, Stanworth SJ, Stein MB, von Steinbüchel N, Stewart W, Steyerberg EW, Stocchetti N, Synnot A, Te Ao B, Tenovuo O, Theadom A, Tibboel D, Videtta W, Wang KKW, Williams WH, Wilson L, Yaffe K

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