Sensitivity of multi-shell NODDI to multiple sclerosis white matter changes: a pilot study
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Diffusion tensor imaging (DTI) is sensitive to white matter (WM) damage in multiple sclerosis (MS), not only in focal lesions but also in the normal-appearing WM (NAWM). However, DTI indices can also be affected by natural spatial variation in WM, as seen in crossing and dispersing white matter fibers. Neurite orientation dispersion and density imaging (NODDI) is an advanced diffusion-weighted imaging technique that provides distinct indices of fiber density and dispersion. We performed NODDI of lesion tissue and NAWM in five MS patients and five controls, comparing the technique with traditional DTI. Both DTI and NODDI identified tissue damage in NAWM and in lesions. NODDI was able to detect additional changes and it provided better contrast in MS-NAWM microstructure, because it distinguished orientation dispersion and fiber density better than DTI. We showed that NODDI is viable in MS patients and that it offers, compared with DTI parameters, improved sensitivity and possibly greater specificity to microstructure features such as neurite orientation.
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The results agree well with preliminary findings in vivo, providing confidence that the conclusions will most likely hold true in clinical scenarios.
“Nevertheless, our results agree well with preliminary findings in vivo, 39, 49 providing confidence that the conclusions of this study will most likely hold true in clinical scenarios.”
From Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology? (2017) · cites this paper as [49]
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Jenkinson, M., Beckmann, C. F., Behrens, T. E. J., Woolrich, M. W., & Smith, S. M. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.09.015 · Cited by 11,314 · see citing works
Spin Diffusion Measurements: Spin Echoes in the Presence of a Time-Dependent Field Gradient
Stejskal, E. O., & Tanner, J. E. (1965) · The Journal of Chemical Physics · doi:10.1063/1.1695690 · Cited by 8,397 · see citing works
Ashburner, J., & Friston, K. J. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.02.018 · Cited by 7,507 · see citing works
MR diffusion tensor spectroscopy and imaging
Basser, P. J., Mattiello, J., & LeBihan, D. (1994) · Biophysical Journal · doi:10.1016/s0006-3495(94)80775-1 · Cited by 5,970 · see citing works
Andersson, J., & Sotiropoulos, S. N. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.10.019 · Cited by 3,439 · see citing works
NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain
Zhang, H., Schneider, T., Wheeler-Kingshott, C. A., & Alexander, D. C. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.03.072 · Cited by 3,288 · see citing works
Self-citationSong, S.-K., Sun, S.-W., Ju, W.-K., Lin, S.-J., Cross, A. H., & Neufeld, A. H. (2003) · NeuroImage · doi:10.1016/j.neuroimage.2003.07.005 · Cited by 1,738 · see citing works
Looking into the functional architecture of the brain with diffusion MRI.
Le Bihan, D. (2003) · Nature Reviews Neuroscience · doi:10.1038/nrn1119 · Cited by 1,571 · see citing works
Setsompop, K., Gagoski, B. A., Polimeni, J. R., Witzel, T., Wedeen, V. J., & Wald, L. L. (2012) · Magnetic Resonance in Medicine · doi:10.1002/mrm.23097 · Cited by 1,285 · see citing works
Barkhof, F. (1997) · Brain · doi:10.1093/brain/120.11.2059 · Cited by 1,251 · see citing works
Fast free-form deformation using graphics processing units
Marc Modat, A., Ridgway, G. R., Taylor, Z. A., Lehmann, M., Barnes, J., Hawkes, D. J., Fox, N. C., & Sebastien Ourselin, A. (2009) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2009.09.002 · Cited by 1,087 · see citing works
A longitudinal study of abnormalities on MRI and disability from multiple sclerosis
Brex, P. A., Ciccarelli, O., O'Riordan, J. I., Sailer, M., Thompson, A. J., & Miller, D. H. (2002) · New England Journal of Medicine · doi:10.1056/nejmoa011341 · Cited by 861 · see citing works
Magnetization transfer ratio and myelin in postmortem multiple sclerosis brain
Schmierer, K., Scaravilli, F., Altmann, D. R., Barker, G. J., & Miller, D. H. (2004) · Annals of Neurology · doi:10.1002/ana.20202 · Cited by 777 · see citing works
Analysis of partial volume effects in diffusion‐tensor MRI
Alexander, A. L., Hasan, K. M., Lazar, M., Tsuruda, J. S., & Parker, D. L. (2001) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1105 · Cited by 695 · see citing works
Diffusion tensor imaging of lesions and normal-appearing white matter in multiple sclerosis
Werring, D. J., Clark, C. A., Barker, G. J., Thompson, A. J., & Miller, D. H. (1999) · Neurology · doi:10.1212/wnl.52.8.1626 · Cited by 621 · see citing works
Diffusion tensor magnetic resonance imaging in multiple sclerosis
Filippi, M., Cercignani, M., Inglese, M., Horsfield, M. A., & Comi, G. (2001) · Neurology · doi:10.1212/wnl.56.3.304 · Cited by 545 · see citing works
Detection and modeling of non‐Gaussian apparent diffusion coefficient profiles in human brain data
Alexander, D. C., Barker, G. J., & Arridge, S. (2002) · Magnetic Resonance in Medicine · doi:10.1002/mrm.10209 · Cited by 527 · see citing works
Association between pathological and MRI findings in multiple sclerosis.
Filippi, M., Rocca, M., Barkhof, F., Brück, W., Chen, J. T., Comi, G., DeLuca, G., de Stefano, N., Erickson, B., Evangelou, N., et al. (2012) · Lancet Neurology · doi:10.1016/s1474-4422(12)70003-0 · Cited by 495 · see citing works
Budde, M. D., Xie, M., Cross, A. H., & Song, S. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.4605-08.2009 · Cited by 483 · see citing works
Camino: Open-Source Diffusion-MRI Reconstruction and Processing
Cook, P. A., Bai, Y., Nedjati-Gilani, S., Seunarine, K. K., Hall, M. G., Parker, G. J. M., & Alexander, D. C. (2006) · Cited by 453 · see citing works
Compartment models of the diffusion MR signal in brain white matter: A taxonomy and comparison
Panagiotaki, E., Schneider, T., Siow, B., Hall, M. G., Lythgoe, M. F., & Alexander, D. C. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.09.081 · Cited by 422 · see citing works
Self-citationNormal aging in the central nervous system: Quantitative MR diffusion-tensor analysis
Abe, O., Aoki, S., Hayashi, N., Yamada, H., Kunimatsu, A., Mori, H., Yoshikawa, T., Okubo, T., & Ohtomo, K. (2002) · Neurobiology of Aging · doi:10.1016/s0197-4580(01)00318-9 · Cited by 420 · see citing works
Diffusion tensor imaging of post mortem multiple sclerosis brain
Schmierer, K., Wheeler-Kingshott, C. A. M., Boulby, P. A., Scaravilli, F., Altmann, D. R., Barker, G. J., Tofts, P. S., & Miller, D. H. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.12.010 · Cited by 395 · see citing works
Radial diffusivity predicts demyelination in ex vivo multiple sclerosis spinal cords
Klawiter, E. C., Schmidt, R. E., Trinkaus, K., Liang, H.-F., Budde, M. D., Naismith, R. T., Song, S.-K., Cross, A. H., & Benzinger, T. L. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.01.007 · Cited by 364 · see citing works
Cercignani, M. (2001) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.70.3.311 · Cited by 287 · see citing works
Detecting axon damage in spinal cord from a mouse model of multiple sclerosis
Kim, J. H., Budde, M. D., Liang, H.-F., Klein, R. S., Russell, J. H., Cross, A. H., & Song, S.-K. (2006) · Neurobiology of Disease · doi:10.1016/j.nbd.2005.09.009 · Cited by 235 · see citing works
Rovaris, M., Iannucci, G., Falautano, M., Possa, F., Martinelli, V., Comi, G., & Filippi, M. (2002) · Journal of the Neurological Sciences · doi:10.1016/s0022-510x(01)00690-6 · Cited by 216 · see citing works
Camino: Diffusion MRI reconstruction and processing
Cook, P. A., Bai, Y., Hall, M. G., Nedjati-Gilani, S., Seunarine, K. K., & Alexander, D. C. (2005) · The Insight Journal · doi:10.54294/fgfrtv · Cited by 203 · see citing works
Ciccarelli, O., Werring, D. J., Barker, G. J., Griffin, C., Wheeler‐Kingshott, C. A. M. G., Miller, D. H., & Thompson, A. J. (2003) · Journal of Neurology · doi:10.1007/s00415-003-0992-5 · Cited by 174 · see citing works
DTI Measurements in Multiple Sclerosis: Evaluation of Brain Damage and Clinical Implications
Sbardella, E., Tona, F., Petsas, N., & Pantano, P. (2013) · Multiple Sclerosis International · doi:10.1155/2013/671730 · Cited by 172 · see citing works
Kunz, N., Zhang, H. G., Vasung, L., O’Brien, K., Assaf, Y., Lazeyras, F., Alexander, D. C., & Hüppi, P. S. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.03.057 · Cited by 159 · see citing works
Imaging biomarkers in multiple sclerosis
Filippi, M., & Agosta, F. (2010) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.22102 · Cited by 141 · see citing works
Winston, G. P., Micallef, C., Symms, M. R., Alexander, D. C., Duncan, J. S., & Zhang, H. (2014) · Epilepsy Research · doi:10.1016/j.eplepsyres.2013.11.004 · Cited by 137 · see citing works
DWI filtering using joint information for DTI and HARDI
Tristán‐Vega, A., & Aja‐Fernández, S. (2009) · Medical Image Analysis · doi:10.1016/j.media.2009.11.001 · Cited by 108 · see citing works
Gallo, A., Rovaris, M., Riva, R., Ghezzi, A., Benedetti, B., Martinelli, V., Falini, A., Comi, G., & Filippi, M. (2005) · Archives of Neurology · doi:10.1001/archneur.62.5.803 · Cited by 105 · see citing works
A ranking of diffusion MRI compartment models with in vivo human brain data
Ferizi, U., Schneider, T., Panagiotaki, E., Nedjati-Gilani, G. L., Zhang, H. G., Wheeler‐Kingshott, C. A. M. G., & Alexander, D. C. (2013) · Magnetic Resonance in Medicine · doi:10.1002/mrm.25080 · Cited by 86 · see citing works
Self-citationPreziosa, P., Rocca, M. A., Mesaroš, Š., Pagani, E., Stošić-Opinćal, T., Kačar, K., Absinta, M., Caputo, D., Drulovic, J. S., Comı, G., et al. (2011) · Radiology · doi:10.1148/radiol.11110315 · Cited by 74 · see citing works
White matter compartment models for in vivo diffusion MRI at 300 mT/m
Ferizi, U., Schneider, T., Witzel, T., Wald, L. L., Zhang, H. G., Wheeler‐Kingshott, C. A. M. G., & Alexander, D. C. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.06.027 · Cited by 57 · see citing works
Self-citationYaldizli, Ö., Pardini, M., Sethi, V., Muhlert, N., Liu, Z., Tozer, D., Samson, R., Wheeler-Kingshott, C., Yousry, T., Miller, D. H., et al. (2016) · Multiple Sclerosis · doi:10.1177/1352458515586085 · Cited by 31 · see citing works
Structural brain indices and executive functioning in multiple sclerosis: A review
Román, C. A. F., & Arnett, P. A. (2016) · Journal of Clinical and Experimental Neuropsychology · doi:10.1080/13803395.2015.1105199 · Cited by 18 · see citing works
Imaging biomarkers in multiple sclerosis
(2010) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.22168 · Cited by 4 · see citing works
Basser (2000) · doi:10.1002/1522-2594(200010)44:4
Flagged first, then by citations
1 of the 43 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology?
Grussu, F., Schneider, T., Tur, C., Yates, R. L., Tachrount, M., Ianuş, A., Yiannakas, M. C., Newcombe, J., Zhang, H., Alexander, D. C., et al. (2017) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.445 · Cited by 291 · see citing works
Self-citationKamiya, K., Hori, M., & Aoki, S. (2020) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2020.108908 · Cited by 283 · see citing works
“In clinical research of MS, NODDI has been applied to the study of both the brain (Collorone et al., 2019; De Santis et al., 2019; Granberg et al., 2017; Hagiwara et al., 2019; Mustafi et al., 2019; Schneider et al., 2017; Spanò et al., 2018) and the spinal cord (By et al.”
MethodDesign and Validation of Diffusion MRI Models of White Matter
Jelescu, I. O., & Budde, M. D. (2017) · Frontiers in Physics · doi:10.3389/fphy.2017.00061 · Cited by 240 · see citing works
Palacios, E. M., Owen, J. P., Yuh, E. L., Wang, M. B., Vassar, M. J., Ferguson, A. R., Diaz-Arrastia, R., Giacino, J. T., Okonkwo, D. O., Robertson, C. S., et al. (2020) · Science Advances · doi:10.1126/sciadv.aaz6892 · Cited by 194 · see citing works
Histological validation of diffusion MRI fiber orientation distributions and dispersion
Schilling, K. G., Janve, V., Gao, Y., Stepniewska, I., Landman, B. A., & Anderson, A. W. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2017.10.046 · Cited by 195 · see citing works
Challenges for biophysical modeling of microstructure
Jelescu, I., Palombo, M., Bagnato, F. R., & Schilling, K. G. (2020) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2020.108861 · Cited by 165 · see citing works
Application and evaluation of NODDI in the cervical spinal cord of multiple sclerosis patients
By, S., Xu, J., Box, B. A., Bagnato, F. R., & Smith, S. A. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.05.010 · Cited by 108 · see citing works
Diffusion-Weighted Imaging: Recent Advances and Applications
Martínez‐Heras, E., Grussu, F., Prados, F., Solana, E., & Llufriú, S. (2021) · Seminars in Ultrasound CT and MRI · doi:10.1053/j.sult.2021.07.006 · Cited by 104 · see citing works
Advances in brain imaging in multiple sclerosis
Cortese, R., Collorone, S., Ciccarelli, O., & Toosy, A. (2019) · Therapeutic Advances in Neurological Disorders · doi:10.1177/1756286419859722 · Cited by 75 · see citing works
Role of artificial intelligence in MS clinical practice
Bonacchi, R., Filippi, M., & Rocca, M. A. (2022) · NeuroImage Clinical · doi:10.1016/j.nicl.2022.103065 · Cited by 74 · see citing works
Neurite orientation dispersion and density imaging of mouse brain microstructure
Wang, N., Zhang, J., Cofer, G., Qi, Y., Anderson, R. J., White, L. E., & Allan Johnson, G. (2019) · Brain Structure and Function · doi:10.1007/s00429-019-01877-x · Cited by 69 · see citing works
Neurite density is reduced in the presymptomatic phase ofC9orf72disease
Wen, J., Zhang, H. G., Alexander, D. C., Durrleman, S., Routier, A., Rinaldi, D., Houot, M., Couratier, P., Hannequin, D., Pasquier, F., et al. (2018) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2018-318994 · Cited by 65 · see citing works
Collorone, S., Cawley, N., Grussu, F., Prados, F., Tona, F., Calvi, A., Kanber, B., Schneider, T., Kipp, L., Zhang, H., et al. (2020) · Multiple Sclerosis Journal · doi:10.1177/1352458519885107 · Cited by 64 · see citing works
Self-citationHagiwara, A., Kamagata, K., Shimoji, K., Yokoyama, K., Andica, C., Hori, M., Fujita, S., Maekawa, T., Irie, R., Akashi, T., et al. (2019) · American Journal of Neuroradiology · doi:10.3174/ajnr.a6209 · Cited by 61 · see citing works
Disruption of neurite morphology parallels MS progression
Spanò, B., Giulietti, G., Pisani, V., Morreale, M., Tuzzi, E., Nocentini, U., Francia, A., Caltagirone, C., Bozzali, M., & Cercignani, M. (2018) · Neurology Neuroimmunology & Neuroinflammation · doi:10.1212/nxi.0000000000000502 · Cited by 58 · see citing works
Abnormal brain white matter microstructure is associated with both pre-hypertension and hypertension
Suzuki, H., Gao, H., Bai, W., Εvangelou, Ε., Glocker, B., O’Regan, D. P., Elliott, P., & Matthews, P. M. (2017) · PLoS ONE · doi:10.1371/journal.pone.0187600 · Cited by 58 · see citing works
De Santis, S., Bastiani, M., Droby, A., Kolber, P., Zipp, F., Pracht, E., Stoecker, T., Groppa, S., & Roebroeck, A. (2019) · Neuroscience · doi:10.1016/j.neuroscience.2018.03.048 · Cited by 56 · see citing works
Andica, C., Kamagata, K., Kirino, E., Uchida, W., Irie, R., Murata, S., & Aoki, S. (2021) · Molecular Autism · doi:10.1186/s13229-021-00456-4 · Cited by 50 · see citing works
Crombe, A., Planche, V., Raffard, G., Bourel, J., Dubourdieu, N., Panatier, A., Fukutomi, H., Dousset, V., Oliet, S., Hiba, B., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.01.061 · Cited by 49 · see citing works
Metzler‐Baddeley, C., Mole, J. P., Sims, R., Fasano, F., Evans, J., Jones, D. K., Aggleton, J. P., & Baddeley, R. (2019) · Scientific Reports · doi:10.1038/s41598-018-37658-5 · Cited by 47 · see citing works
Advanced Multicompartment Diffusion MRI Models and Their Application in Multiple Sclerosis
Lakhani, D. A., Schilling, K. G., Xu, J., & Bagnato, F. R. (2020) · American Journal of Neuroradiology · doi:10.3174/ajnr.a6484 · Cited by 46 · see citing works
Caranova, M., Soares, J. F., Batista, S., Castelo-Branco, M. S., & Duarte, J. V. (2023) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2023.09.010 · Cited by 47 · see citing works
Santis, S. D., Granberg, T., Ouellette, R., Treaba, C. A., Herranz, E., Fan, Q., Mainero, C., & Toschi, N. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101699 · Cited by 45 · see citing works
Andica, C., Kamagata, K., Hayashi, T., Hagiwara, A., Uchida, W., Saito, Y., Kamiya, K., Fujita, S., Akashi, T., Wada, A., et al. (2019) · Neuroradiology · doi:10.1007/s00234-019-02350-6 · Cited by 37 · see citing works
Collorone, S., Prados, F., Kanber, B., Cawley, N., Tur, C., Grussu, F., Solanky, B., Yiannakas, M. C., Davagnanam, I., Wheeler‐Kingshott, C. A. M. G., et al. (2021) · Brain · doi:10.1093/brain/awab043 · Cited by 37 · see citing works
Preziosa, P., Pagani, E., Meani, A., Marchesi, O., Conti, L., Falini, A., Rocca, M. A., & Filippi, M. (2022) · Journal of Neurology · doi:10.1007/s00415-022-11415-1 · Cited by 36 · see citing works
Estimating axial diffusivity in the NODDI model
Howard, A. F. D., Cottaar, M., Drakesmith, M., Fan, Q., Huang, S. Y., Jones, D. K., Lange, F., Mollink, J., Rudrapatna, S. U., Tian, Q., et al. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119535 · Cited by 34 · see citing works
MRI in multiple sclerosis: what is changing?
Filippi, M., Preziosa, P., & Rocca, M. A. (2018) · Current Opinion in Neurology · doi:10.1097/wco.0000000000000572 · Cited by 33 · see citing works
Mustafi, S., Harezlak, J., Kodiweera, C., Randolph, J. S., Ford, J. C., Wishart, H., & Wu, Y.-C. (2019) · Neural Regeneration Research · doi:10.4103/1673-5374.243716 · Cited by 33 · see citing works
The Role of Advanced Magnetic Resonance Imaging Techniques in Multiple Sclerosis Clinical Trials
Mahajan, K., & Ontaneda, D. (2017) · Neurotherapeutics · doi:10.1007/s13311-017-0561-8 · Cited by 29 · see citing works
Sacco, S., Caverzasi, E., Papinutto, N., Cordano, C., Bischof, A., Gundel, T. J., Cheng, S., Asteggiano, C., Kirkish, G., Mallott, J. M., et al. (2020) · American Journal of Neuroradiology · doi:10.3174/ajnr.a6862 · Cited by 31 · see citing works
Breit, S., Mazza, E. A., Poletti, S., & Benedetti, F. (2023) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2022.12.009 · Cited by 30 · see citing works
Neurite Orientation Dispersion and Density Imaging in Multiple Sclerosis: A Systematic Review
Seyedmirzaei, H., Nabizadeh, F., Aarabi, M. H., & Pini, L. (2023) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.28727 · Cited by 30 · see citing works
Nemanich, S. T., Mueller, B. A., & Gillick, B. T. (2019) · Human Brain Mapping · doi:10.1002/hbm.24744 · Cited by 29 · see citing works
(2018) · PubMed · Cited by 29 · see citing works
By, S., Xu, J., Box, B. A., Bagnato, F. R., & Smith, S. A. (2018) · NMR in Biomedicine · doi:10.1002/nbm.3894 · Cited by 26 · see citing works
Developing therapeutic strategies to promote myelin repair in multiple sclerosis
Baldassari, L. E., Feng, J. J., Clayton, B. L. L., Oh, S., Sakaie, K., Tesar, P. J., Wang, Y., & Cohen, J. A. (2019) · Expert Review of Neurotherapeutics · doi:10.1080/14737175.2019.1632192 · Cited by 28 · see citing works
Parvathaneni, P., Nath, V., Blaber, J. A., Schilling, K. G., Hainline, A. E., Mojahed, E., Anderson, A. W., & Landman, B. A. (2018) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2018.03.004 · Cited by 25 · see citing works
Reliability on multiband diffusion NODDI models: A test retest study on children and adults
Lucignani, M., Breschi, L., Rossi‐Espagnet, M. C., Longo, D., Talamanca, L. F., Placidi, E., & Napolitano, A. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118234 · Cited by 23 · see citing works
Callow, D. D., Purcell, J. J., Won, J., & Smith, J. C. (2022) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2022.108207 · Cited by 23 · see citing works
A study of neurite orientation dispersion and density imaging in wilson's disease
Song, Y., Li, X., Huang, X., Zhao, J., Zhou, X., Wang, Y., Yan, X., Wang, J., & Chu, J. (2017) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.25930 · Cited by 23 · see citing works
Changes in structural network are associated with cortical demyelination in early multiple sclerosis
Mangeat, G., Badji, A., Ouellette, R., Treabă, C., Herranz, E., Granberg, T., Louapre, C., Stikov, N., Sloane, J., Bellec, L. P., et al. (2018) · Human Brain Mapping · doi:10.1002/hbm.23993 · Cited by 21 · see citing works
Schneider, R., Genç, E., Ahlborn, C., Gold, R., Lukas, C., & Bellenberg, B. (2019) · Frontiers in Neurology · doi:10.3389/fneur.2019.01165 · Cited by 22 · see citing works
York, E. N., Meijboom, R., Thrippleton, M. J., Bastin, M. E., Kampaite, A., White, N., Chandran, S., & Waldman, A. D. (2022) · NeuroImage Clinical · doi:10.1016/j.nicl.2022.103228 · Cited by 21 · see citing works
Zeicu, C., Legouhy, A., Scott, C. A., Oliveira, J. F. A., Winston, G. P., Duncan, J. S., Vos, S. B., Thom, M., Lhatoo, S. D., Zhang, H. G., et al. (2023) · Epilepsia · doi:10.1111/epi.17804 · Cited by 20 · see citing works
Ananthavarathan, P., Sahi, N., & Chard, D. (2024) · Expert Review of Neurotherapeutics · doi:10.1080/14737175.2024.2304116 · Cited by 22 · see citing works
A Spherical Convolutional Neural Network for White Matter Structure Imaging via dMRI
Sedlar, S., Alimi, A., Papadopoulo, T., Rachid Deriche, B., & Deslauriers‐Gauthier, S. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-87199-4_50 · Cited by 20 · see citing works
Reproducibility of Neurite Orientation Dispersion and Density Imaging (NODDI) in rats at 9.4 Tesla
McCunn, P., Gilbert, K. M., Zeman, P. R., Li, A. X., Strong, M. J., KHAN, A. R., & Bartha, R. (2019) · PLoS ONE · doi:10.1371/journal.pone.0215974 · Cited by 20 · see citing works
Luo, T., Oladosu, O., Rawji, K. S., Zhai, P., Pridham, G., Hossain, S., & Zhang, Y. (2018) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.26328 · Cited by 19 · see citing works
Johnson, D. A., Ricciardi, A., Brownlee, W. J., Kanber, B., Prados, F., Collorone, S., Kaden, E., Toosy, A., Alexander, D. C., Wheeler‐Kingshott, C. A. M. G., et al. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.662855 · Cited by 19 · see citing works
Zachariou, V., Bauer, C. E., Pappas, C. A., & Gold, B. T. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac382 · Cited by 18 · see citing works
Alotaibi, A., Podlasek, A., AlTokhis, A. I., Aldhebaib, A., Dineen, R. A., & Constantinescu, C. S. (2021) · Brain Sciences · doi:10.3390/brainsci11091151 · Cited by 17 · see citing works
Koo, D. L., Cabeen, R. P., Yook, S., Cen, S., Joo, E. Y., & Kim, H. (2023) · Human Brain Mapping · doi:10.1002/hbm.26261 · Cited by 16 · see citing works
Linking Microstructural Integrity and Motor Cortex Excitability in Multiple Sclerosis
Radetz, A., Mladenova, K., Ciolac, D., González‐Escamilla, G., Fleischer, V., Ellwardt, E., Krämer, J., Bittner, S., Meuth, S. G., Muthuraman, M., et al. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.748357 · Cited by 15 · see citing works
Edde, M., Theaud, G., Dumont, M., Théberge, A., Caron, A. V., Gilbert, G., Houde, J., Maltais, L., Rheault, F., Spagnolo, F., et al. (2023) · Human Brain Mapping · doi:10.1002/hbm.26310 · Cited by 15 · see citing works
The Evolution of White Matter Changes After Mild Traumatic Brain Injury: A DTI and NODDI Study
Palacios, E. M., Owen, J. P., Yuh, E. L., Wang, M. B., Vassar, M. J., Ferguson, A. R., Diaz-Arrastia, R., Giacino, J. T., Okonkwo, D. O., Robertson, C. S., et al. (2018) · doi:10.1101/345629 · Cited by 15 · see citing works
Advanced MRI Methods for Diagnosis and Monitoring of Multiple Sclerosis ( MS )
Elahi, R., Taremi, S., Najafi, A., Karimi, H., Asadollahzadeh, E., Sajedi, S. A., Rad, H. S., & Sahraian, M. A. (2025) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.29817 · Cited by 14 · see citing works
Toschi, N., Santis, S. D., Granberg, T., Ouellette, R., Treaba, C. A., Herranz, E., & Mainero, C. (2019) · Neuroscience · doi:10.1016/j.neuroscience.2019.01.022 · Cited by 13 · see citing works
Atkinson, K. C., Lee, J. B., Hasselmann, J., Kim, S. H., Drew, A., Soto, J. S., Katzenellenbogen, J. A., Harris, N. G., Obenaus, A., & Tiwari-Woodruff, S. K. (2019) · Neurobiology of Disease · doi:10.1016/j.nbd.2019.104501 · Cited by 13 · see citing works
Storelli, L., Pagani, E., Meani, A., Preziosa, P., Filippi, M., & Rocca, M. A. (2022) · Journal of Neurology · doi:10.1007/s00415-022-11104-z · Cited by 12 · see citing works
Uddin, M. N., Singh, M. V., Faiyaz, A., Szczepankiewicz, F., Nilsson, M., Boodoo, Z. D., Sutton, K. R., Tivarus, M. E., Zhong, J., Wang, L., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-80372-8 · Cited by 13 · see citing works
Devan, S. P., Jiang, X., Bagnato, F. R., & Xu, J. (2020) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2020.09.002 · Cited by 12 · see citing works
Oladosu, O., Liu, W., Pike, G. B., Koch, M. W., Metz, L. M., & Zhang, Y. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.634063 · Cited by 11 · see citing works
Widespread Disruptions of White Matter in Familial Multiple Sclerosis: DTI and NODDI Study
Gharaylou, Z., Sahraian, M. A., Hadjighassem, M., Kohanpour, M., Doosti, R., Nahardani, S., & Moghadasi, A. N. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.678245 · Cited by 11 · see citing works
Oladosu, O., Liu, W., Brown, L., Pike, G. B., Metz, L. M., & Zhang, Y. (2022) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2022.944908 · Cited by 9 · see citing works
Neurite orientation and dispersion density imaging: clinical utility, efficacy, and role in therapy
Sone, D. (2019) · Reports in Medical Imaging · doi:10.2147/rmi.s194083 · Cited by 9 · see citing works
Margoni, M., Villani, U., Silvestri, E., Franciotta, S., Anglani, M. G., Causin, F., Rinaldi, F., Perini, P., Bertoldo, A., & Gallo, P. (2021) · Multiple Sclerosis and Related Disorders · doi:10.1016/j.msard.2021.103396 · Cited by 9 · see citing works
Chen, A., Wen, S., Lakhani, D., Gao, S., Yoon, K., Smith, S. A., Dortch, R., Xu, J.-Z., & Bagnato, F. (2021) · Journal of Neuroimaging · doi:10.1111/jon.12876 · Cited by 6 · see citing works
Current and future applications of artificial intelligence in multiple sclerosis
Cacciaguerra, L., Storelli, L., Rocca, M. A., & Filippi, M. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-90037-9.00012-6 · Cited by 8 · see citing works
Alghamdi, A. J. (2023) · Brain Sciences · doi:10.3390/brainsci13040622 · Cited by 8 · see citing works
Cacciaguerra, L., Rocca, M. A., & Filippi, M. (2023) · Korean Journal of Radiology · doi:10.3348/kjr.2023.0360 · Cited by 8 · see citing works
Stellingwerff, M. D., Al‐Saady, M. L., Chan, K., Dvorak, A. V., Marques, J. P., Kolind, S., Roosendaal, S. D., Wolf, N. I., Barkhof, F., van der Knaap, M. S., et al. (2023) · Journal of Neuroimaging · doi:10.1111/jon.13167 · Cited by 7 · see citing works
Brain microstructural abnormalities correlate with KCC2 downregulation in refractory epilepsy
Gharaylou, Z., Oghabian, M. A., Azizi, Z., & Hadjighassem, M. (2019) · Neuroreport · doi:10.1097/wnr.0000000000001216 · Cited by 7 · see citing works
Caron, B., Bullock, D., Kitchell, L., McPherson, B., Kellar, D. A., Cheng, H., Newman, S. D., Port, N. L., & Pestilli, F. (2020) · doi:10.31234/osf.io/dxaqp · Cited by 9 · see citing works
Fu, Y., Sun, Y., Wang, Z., Zhang, D., Tan, L., Feng, J., Cheng, W., & Yu, J. (2023) · European Journal of Neurology · doi:10.1111/ene.15750 · Cited by 6 · see citing works
Multimodal brain imaging study of 36,678 participants reveals adverse effects of moderate drinkingPreprint
Daviet, R., Aydogan, G., Jagannathan, K., Spilka, N. H., Koellinger, P., Kranzler, H. R., Nave, G., & Wetherill, R. R. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.03.27.011791 · Cited by 5 · see citing works
Tiss, A., Michaelson, N. M., Russo, A. W., Ramos‐Torres, K. M., Sun, Y., DaSilva, N., Noel, J., Liu, F., Gong, K., Huang, S. Y., et al. (2025) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-025-07454-1 · Cited by 4 · see citing works
Comparison of NODDI and spherical mean signal for measuring intra-neurite volume fraction
Li, H., Nikam, R. M., Kandula, V. V. R., Chow, H. M., & Choudhary, A. K. (2018) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2018.11.021 · Cited by 4 · see citing works
Lu, P., Baraković, M., Weigel, M., Rahmanzadeh, R., Galbusera, R., Schiavi, S., Daducci, A., Rosa, F. L., Cuadra, M. B., Sandkühler, R., et al. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.647535 · Cited by 4 · see citing works
Yoon, K., Archer, D., Clarke, M., Smith, S. A., Oguz, I., Cutter, G., Xu, J.-Z., & Bagnato, F. (2022) · Frontiers in Neurology · doi:10.3389/fneur.2022.811315 · Cited by 3 · see citing works
Diffusion Kurtosis Imaging maps neural damage in the EAE model of multiple sclerosis
Chuhutin, A., Hansen, B., Wlodarczyk, A., Owens, T., Shemesh, N., & Jespersen, S. N. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2019.116406 · Cited by 3 · see citing works
Rapid Diffusion Magnetic Resonance Imaging Using Slice-Interleaved Encoding
Xu, T., Wu, Y., Hong, Y., Ahmad, S., Huynh, K. M., Wang, Z., Lin, W., Chang, W., & Yap, P. (2022) · Medical Image Analysis · doi:10.1016/j.media.2022.102548 · Cited by 3 · see citing works
Detecting glioblastoma infiltration beyond conventional imaging tumour margins using MTE-NODDI
Karamched, S. R., Gorup, D., Tolomeo, D., Brooks, L. J., Gong, T., Jørgensen, A. C. S., Hill, C. S., Clements, M., Kalber, T. L., Wells, J. A., et al. (2025) · Imaging Neuroscience · doi:10.1162/imag_a_00472 · Cited by 3 · see citing works
Carvalho, V., Soares, C., Gomes, I. D. M. E. S., Carvalho, A., Serrazina, F., Rodrigues, S. G., Pinheiro, J., Marques, I. B., Correia, F., Correia, A. S., et al. (2021) · Multiple Sclerosis and Related Disorders · doi:10.1016/j.msard.2021.102832 · Cited by 2 · see citing works
Magnetic resonance imaging approaches for studying mouse models of multiple sclerosis: A mini review
Gilli, F., & Ceccarelli, A. (2023) · Journal of Neuroscience Research · doi:10.1002/jnr.25193 · Cited by 2 · see citing works
A cross-sectional multicentre study of multishell diffusion MRI in multiple sclerosis
Høgestøl, E. A., Rinker, D. A., Maximov, I. I., Sowa, P., Celius, E. G., Hope, T. R., Bjørnerud, A., Sofia, F., Heras, E. M. D. L., Solana, E., et al. (2025) · Multiple Sclerosis and Related Disorders · doi:10.1016/j.msard.2025.106435 · Cited by 1 · see citing works
Li, Z., Li, H., Tian, B., Liu, H., Jiang, Y., Yang, P., Fan, G., & Liu, H. (2025) · Neural Regeneration Research · doi:10.4103/nrr.nrr-d-25-00730 · Cited by 1 · see citing works
Li, Z., Li, H., Tian, B., Liu, H., Jiang, Y., Yang, P., Fan, G., & Liu, H. (2026) · Journal of Autoimmunity · doi:10.1016/j.jaut.2026.103560 · Cited by 1 · see citing works
Karahan, E., Costigan, A. G., Graham, K., Lawrence, A., & Zhang, J.-X. (2018) · bioRxiv · doi:10.1101/473660 · Cited by 3 · see citing works
Zeicu, C., Legouhy, A., Scott, C. A., Oliveira, J. F. A., Winston, G. P., Duncan, J. S., Vos, S. B., Thom, M., Lhatoo, S. D., Zhang, H. G., et al. (2023) · medRxiv · doi:10.1101/2023.03.16.23287369 · Cited by 1 · see citing works
Applications of Neuroimaging Biomarkers in CNS Drug Development
Cole, P. E., & Einstein, S. G. (2019) · Handbook of behavioral neuroscience · doi:10.1016/b978-0-12-803161-2.00009-6 · Cited by 1 · see citing works
Advanced Diffusion Imaging in Neuroradiology
Middleton, D. M., & Conklin, C. J. (2023) · Springer eBooks · doi:10.1007/978-3-031-10909-6_40
Al‐Saady, M. L. (2024) · doi:10.5463/thesis.775
Models: Signal Representation vs. Microstructural Models
Luca, A. D., Froeling, M., & Leemans, A. (2024) · Springer eBooks · doi:10.1007/978-3-031-70337-9_4
Joseph, T. S., Liu, H., Kolind, S., Zhao, G., Sun, P., Carruthers, R. L., Schabas, A. J., Sayao, A., Devonshire, V. A., Tam, R. C., et al. (2025) · Multiple Sclerosis and Related Disorders · doi:10.1016/j.msard.2025.106696
Li, J., Ma, X., Liu, J., Xu, W., Zhang, X., Liang, F., & Dou, Y. (2026) · Psychoradiology · doi:10.1093/psyrad/kkag023
Advances in diffusion MRI in multiple sclerosis
Martínez‐Heras, E., Solana, E., Vivó, F., Calvi, A., Pareto, D., Prados, F., & Llufriú, S. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-23812-3.00008-4
- Authors
- Schneider, T.
- Affiliations
- National Hospital for Neurology and Neurosurgery (GB)
- Corresponding author
- Schneider, Torben
- ORCID
- Schneider, Torben
- Venue
- Functional Neurology
- Publisher
- Edikta s.r.l.
- Published
- 2017
- Volume
- 32
- Issue
- 2
- Pages
- 97
- ISSN
- 0393-5264 (ISSN-L)
- PMC
- PMC5507159
- OpenAlex
- W2734984108
- Cited by
- 104
- References
- 43
- Citations by year
- 2026: 6 · 2025: 6 · 2024: 4 · 2023: 13 · 2022: 11 · 2021: 14 · 2020: 9 · 2019: 20 · 2018: 14 · 2017: 7
- FWCI
- 10.49
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Functional Neurology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Pathology and Forensic Medicine › Multiple Sclerosis Research Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- multiple sclerosis, NODDI, normal-appearing white matter, white matter microstructure, diffusion tensor imaging, fiber density, neurite orientation dispersion, white matter lesions, diffusion-weighted imaging
- MeSH terms
- Adult, Female, Humans, Image Processing, Computer-Assisted, Male, Middle Aged, Multiple Sclerosis, Pilot Projects, Neurites, Diffusion Magnetic Resonance Imaging, White Matter
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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