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Investigating white matter fibre density and morphology using fixel-based analysis.
Open accessAbstract
Voxel-based analysis of diffusion MRI data is increasingly popular. However, most white matter voxels contain contributions from multiple fibre populations (often referred to as crossing fibres), and therefore voxel-averaged quantitative measures (e.g. fractional anisotropy) are not fibre-specific and have poor interpretability. Using higher-order diffusion models, parameters related to fibre density can be extracted for individual fibre populations within each voxel ('fixels'), and recent advances in statistics enable the multi-subject analysis of such data. However, investigating within-voxel microscopic fibre density alone does not account for macroscopic differences in the white matter morphology (e.g. the calibre of a fibre bundle). In this work, we introduce a novel method to investigate the latter, which we call fixel-based morphometry (FBM). To obtain a more complete measure related to the total number of white matter axons, information from both within-voxel microscopic fibre density and macroscopic morphology must be combined. We therefore present the FBM method as an integral piece within a comprehensive fixel-based analysis framework to investigate measures of fibre density, fibre-bundle morphology (cross-section), and a combined measure of fibre density and cross-section. We performed simulations to demonstrate the proposed measures using various transformations of a numerical fibre bundle phantom. Finally, we provide an example of such an analysis by comparing a clinical patient group to a healthy control group, which demonstrates that all three measures provide distinct and complementary information. By capturing information from both sources, the combined fibre density and cross-section measure is likely to be more sensitive to certain pathologies and more directly interpretable.
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“recent fixel-based analysis approaches have been proposed to characterize a specific fiber population within a voxel (i.e., a “fixel”) (Raffelt et al., 2017).”
From Potential Pitfalls of Using Fractional Anisotropy, Axial Diffusivity, and Radial Diffusivity as Biomarkers of Cerebral White Matter Microstructure (2022) · cites this paper as Raffelt et al., 2017
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Self-citationvan den Heuvel, M. P., Mandl, R. C. W., Kahn, R. S., & Hulshoff Pol, H. E. (2009) · Human Brain Mapping · doi:10.1002/hbm.20737 · Cited by 987 · cited 1×
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Water diffusion changes in wallerian degeneration and their dependence on white matter architecture
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Diffusion tensor imaging and beyond
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About “axial” and “radial” diffusivities
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BackgroundThe rises and falls of disconnection syndromes
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BackgroundMethodComposite hindered and restricted model of diffusion (CHARMED) MR imaging of the human brain
Assaf, Y., & Basser, P. J. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.03.042 · Cited by 856 · cited 10×
“Many DWI models assume that diffusion within axons is restricted in the radial orientation (Alexander, 2008; Assaf and Basser, 2005; Barazany et al., 2009; Jespersen et al., 2007; Lu et al., 2006; Raffelt et al., 2012b; Stanisz et al., 1997; Zhang et al., 2012), and that the exchange of water…”
BackgroundMethodInfluentialAxcaliber: A method for measuring axon diameter distribution from diffusion MRI
Assaf, Y., Blumenfeld‐Katzir, T., Yovel, Y., & Basser, P. J. (2008) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21577 · Cited by 849 · cited 5×
“…in the radial orientation (Alexander, 2008; Assaf and Basser, 2005; Barazany et al., 2009; Jespersen et al., 2007; Lu et al., 2006; Raffelt et al., 2012b; Stanisz et al., 1997; Zhang et al., 2012), and that the exchange of water between the intra-axonal and extra-axonal space is negligible on the…”
BackgroundMethodInfluentialA review of diffusion tensor imaging studies in schizophrenia
Kubicki, M., McCarley, R., Westin, C.-F., Park, H.-J., Maier, S., Kikinis, R., Jolesz, F. A., & Shenton, M. E. (2007) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2005.05.005 · Cited by 769
SIFT: Spherical-deconvolution informed filtering of tractograms
Smith, R. E., Tournier, J.-D., Calamante, F., & Connelly, A. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.11.049 · Cited by 752 · cited 2×
“Briefly, FOD lobes are first segmented based on the peaks and troughs of the FOD, and the apparent FD of each lobe is calculated by nonparametric numerical integration using a dense sampling of the FOD over a hemisphere (Smith et al., 2013).”
MethodSelf-citationOrientationally invariant indices of axon diameter and density from diffusion MRI
Alexander, D. C., Hubbard, P. L., Hall, M. G., Moore, E. A., Ptito, M., Parker, G. J. M., & Dyrby, T. B. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.05.043 · Cited by 683 · cited 6×
“…volume would provide additional information and potentially more biologically meaningful metrics, however current approaches to estimate axon diameters using DWI are not able to assign estimates to individual fixels in crossing fibre regions (Alexander et al., 2010; Assaf et al., 2008).”
BackgroundMethodInfluentialDeterminants of conduction velocity in myelinated nerve fibers
Waxman, S. G. (1980) · Muscle & Nerve · doi:10.1002/mus.880030207 · Cited by 629 · cited 1×
“Axon diameter plays a role in the ‘ability to relay information’ via modulating transmission speed, timing and firing rate (Perge et al., 2012; Waxman, 1980).”
BackgroundRaffelt, D., Tournier, J.-D., Rose, S., Ridgway, G., Henderson, R., Crozier, S., Salvado, O., & Connelly, A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.10.045 · Cited by 616
Self-citationSpatial transformations of diffusion tensor magnetic resonance images
Alexander, D. C., Pierpaoli, C., Basser, P. J., & Gee, J. C. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.963816 · Cited by 610 · cited 2×
“(4) from Alexander et al. (2001): ^′ = ^ ^ ( ) v Jv Jv 1 f f f where v̂f is the unit vector describing the original direction of the fixel, ^′v f is the reoriented direction, and J is the Jacobian matrix that describes the local affine transformation of the non-linear warp, defined as: ⎡ ⎣ ⎢ ⎢ ⎢ ⎢…”
BackgroundDouaud, G., Jbabdi, S., Behrens, T. E. J., Menke, R. A., Gass, A., Monsch, A. U., Rao, A., Whitcher, B., Kindlmann, G., Matthews, P. M., et al. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.12.008 · Cited by 514
An analytical model of restricted diffusion in bovine optic nerve
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“Many DWI models assume that diffusion within axons is restricted in the radial orientation (Alexander, 2008; Assaf and Basser, 2005; Barazany et al., 2009; Jespersen et al., 2007; Lu et al., 2006; Raffelt et al., 2012b; Stanisz et al., 1997; Zhang et al., 2012), and that the exchange of water between the intra-axonal…”
BackgroundMethodological considerations on tract-based spatial statistics (TBSS)
Bach, M., Laun, F. B., Leemans, A., Tax, C. M. W., Biessels, G. J., Stieltjes, B., & Maier-Hein, K. H. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.06.021 · Cited by 445 · cited 2×
“, 2006), this approach is likely to suffer from inaccurate FA-based projection in regions of crossing fibres (Bach et al., 2014; De Groot et al., 2013; Schwarz et al., 2014), and lack of fibre-specific inference when investigating voxel-wise measures such as FA.”
BackgroundMethodCompartment 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 · cited 1×
“DWI models that estimate parameters related to the volume of intra-axonal restricted water are consequently of biological interest since this volume is influenced by the number of axons.”
BackgroundLu, H., Jensen, J. H., Ramani, A., & Helpern, J. A. (2006) · NMR in Biomedicine · doi:10.1002/nbm.1020 · Cited by 420
In vivo measurement of axon diameter distribution in the corpus callosum of rat brain
Barazany, D., Basser, P. J., & Assaf, Y. (2009) · Brain · doi:10.1093/brain/awp042 · Cited by 400 · cited 2×
“Many DWI models assume that diffusion within axons is restricted in the radial orientation (Alexander, 2008; Assaf and Basser, 2005; Barazany et al., 2009; Jespersen et al., 2007; Lu et al., 2006; Raffelt et al., 2012b; Stanisz et al., 1997; Zhang et al., 2012), and that the exchange of water between the intra-axonal…”
BackgroundAlexander, D. (2008) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21646 · Cited by 394 · cited 2×
“Many DWI models assume that diffusion within axons is restricted in the radial orientation (Alexander, 2008; Assaf and Basser, 2005; Barazany et al., 2009; Jespersen et al., 2007; Lu et al., 2006; Raffelt et al., 2012b; Stanisz et al., 1997; Zhang et al., 2012), and that the exchange of water between the intra-axonal…”
Raffelt, D. A., Smith, R. E., Ridgway, G. R., Tournier, J., Vaughan, D. N., Rose, S., Henderson, R. D., & Connelly, A. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.05.039 · Cited by 394
Self-citationMRI white matter diffusion anisotropy and PET metabolic rate in schizophrenia
Buchsbaum, M., Tang, C. Y., Peled, S., Gudbjartsson, H., Lu, D.-F., Hazlett, E., Downhill, J., Haznedar, M., Fallon, J., & Atlas, S. (1998) · NeuroReport · doi:10.1097/00001756-199802160-00013 · Cited by 369 · cited 1×
“Voxel-based analysis (VBA) of diffusion MRI is a common method for studying white matter, providing evidence of altered brain connectivity by detecting differences at a local level (Buchsbaum et al., 1998).”
Modeling dendrite density from magnetic resonance diffusion measurements
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“Many DWI models assume that diffusion within axons is restricted in the radial orientation (Alexander, 2008; Assaf and Basser, 2005; Barazany et al., 2009; Jespersen et al., 2007; Lu et al., 2006; Raffelt et al., 2012b; Stanisz et al., 1997; Zhang et al., 2012), and that the exchange of water”
BackgroundSymmetric Diffeomorphic Modeling of Longitudinal Structural MRI
Ashburner, J., & Ridgway, G. (2013) · Frontiers in Neuroscience · doi:10.3389/fnins.2012.00197 · Cited by 350 · cited 1×
“3–5 of Ashburner and Ridgway (2013)).”
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“However, most white matter voxels are known to contain crossing fibres (Jeurissen et al., 2012), and voxel-averaged measures such as FA are not fibre-specific (or even erroneous) in such regions, which confounds interpretation of apparent differences (Douaud et al., 2011; Pierpaoli et al., 2001;…”
BackgroundWhy do axons differ in caliber?
Perge, J., Niven, J., Mugnaini, E., Balasubramanian, V., & Sterling, P. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.4254-11.2012 · Cited by 318 · cited 1×
“Voxel-based analysis (VBA) of diffusion MRI is a common method for studying white matter, providing evidence of altered brain connectivity by detecting differences at a local level (Buchsbaum et al., 1998).”
Dell’Acqua, F., Scifo, P., Rizzo, G., Catani, M., Simmons, A., Scotti, G., & Fazio, F. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.09.033 · Cited by 310
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“…so-called mixture models (Tournier et al., 2011) is that quantitative measures can be associated with a single fibre population within a voxel (Assaf and Basser, 2005; De Santis et al., 2016; Dell’Acqua et al., 2013; Raffelt et al., 2012b, 2014; Scherrer et al., 2016; Scherrer and Warfield, 2012).”
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Methods and considerations for longitudinal structural brain imaging analysis across development
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“However, most white matter voxels contain contributions from multiple fibre populations (often referred to as crossing fibres), and therefore voxel-averaged quantitative measures (e.g. fractional anisotropy) are not fibre-specific and have poor interpretability.”
BackgroundInfluentialSymmetric diffeomorphic registration of fibre orientation distributions
Raffelt, D., Tournier, J.-D., Fripp, J., Crozier, S., Connelly, A., & Salvado, O. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.02.014 · Cited by 281 · cited 4×
“While FODs benefit from high angular resolution and high b-value DWI data, FOD registration is best performed using a relatively low spherical harmonic degree of 4 (Raffelt et al., 2011).”
BackgroundMethodInfluentialSelf-citationDe Santis, S., Drakesmith, M., Bells, S., Assaf, Y., & Jones, D. K. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.12.003 · Cited by 231
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Crossing fibres in tract-based spatial statistics
Jbabdi, S., Behrens, T. E. J., & Smith, S. M. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.08.039 · Cited by 187 · cited 3×
“, 2013), partial volume fraction (Jbabdi et al., 2010), fibre density (Alexander et al.”
BackgroundBehavioural relevance of variation in white matter microstructure
Johansen‐Berg, H. (2010) · Current Opinion in Neurology · doi:10.1097/wco.0b013e32833b7631 · Cited by 179 · cited 2×
“, 2012), individual differences and brain-behaviour correlations (Johansen-Berg, 2010), genetics (Meyer-Lindenberg, 2009), structural plasticity (Scholz et al.”
BackgroundEquilibrium water exchange between the intra‐ and extracellular spaces of mammalian brain
Quirk, J., Bretthorst, G., Duong, T., Snyder, A., Springer, C., Ackerman, J., & Neil, J. (2003) · Magnetic Resonance in Medicine · doi:10.1002/mrm.10565 · Cited by 177
Schwarz, C. G., Reid, R. I., Gunter, J. L., Senjem, M. L., Przybelski, S. A., Zuk, S. M., Whitwell, J. L., Vemuri, P., Josephs, K. A., Kantarci, K., et al. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.03.026 · Cited by 176
Contrast and stability of the axon diameter index from microstructure imaging with diffusion MRI
Dyrby, T., S⊘gaard, L. V., Hall, M., Ptito, M., & Alexander, D. (2012) · Magnetic Resonance in Medicine · doi:10.1002/mrm.24501 · Cited by 162 · cited 1×
“…Basser, 2005; Barazany et al., 2009; Jespersen et al., 2007; Lu et al., 2006; Raffelt et al., 2012b; Stanisz et al., 1997; Zhang et al., 2012), and that the exchange of water between the intra-axonal and extra-axonal space is negligible on the timescale of a diffusion MRI experiment (Quirk et…”
BackgroundOtte, W., van Eijsden, P., Sander, J. W., Duncan, J., Dijkhuizen, R., & Braun, K. (2012) · Epilepsia · doi:10.1111/j.1528-1167.2012.03426.x · Cited by 157 · cited 1×
“…white matter fibre density and morphology using fixel-based analysis David A. Raffelt a,n, J.-Donald Tournier b,c, Robert E. Smith a, David N. Vaughan a,d,e, Graeme Jackson a,d,f, Gerard R. Ridgway g,h, Alan Connelly a,d,e a Florey Institute of Neuroscience and Mental Health, Melbourne,…”
MethodTractography-based priors for dynamic causal models
Stephan, K. E., Tittgemeyer, M., Knösche, T. R., Moran, R., & Friston, K. J. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.05.096 · Cited by 151 · cited 2×
“…(Johansen-Berg, 2010), genetics (Meyer-Lindenberg, 2009), structural plasticity (Scholz et al., 2009), treatment response (Szeszko et al., 2014) and neuroscientific efforts to relate structural and functional connectivity (Calamante et al., 2013; Stephan et al., 2009; Van Den Heuvel et al., 2009).”
BackgroundAxonal Damage in Multiple Sclerosis
Haines, J. D., Inglese, M., & Casaccia, P. (2011) · Mount Sinai Journal of Medicine A Journal of Translational and Personalized Medicine · doi:10.1002/msj.20246 · Cited by 151 · cited 4×
“Furthermore, many neurological disorders (including Motor Neurone Disease (Kassubek et al., 2012), Multiple Sclerosis (Haines et al., 2011), Epilepsy (Otte et al., 2012), and Alzheimer's disease (Radanovic et al., 2013)) involve reduction or disruption of brain ‘connectivity’ due to pathological…”
BackgroundMethodInfluentialWhite Matter Changes Associated with Antipsychotic Treatment in First-Episode Psychosis
Szeszko, P. R., Robinson, D. G., Ikuta, T., Peters, B. D., Gallego, J. A., Kane, J. M., & Malhotra, A. K. (2013) · Neuropsychopharmacology · doi:10.1038/npp.2013.288 · Cited by 142 · cited 2×
“…correlations (Johansen-Berg, 2010), genetics (Meyer-Lindenberg, 2009), structural plasticity (Scholz et al., 2009), treatment response (Szeszko et al., 2014) and neuroscientific efforts to relate structural and functional connectivity (Calamante et al., 2013; Stephan et al., 2009; Van…”
BackgroundThe CONNECT project: Combining macro- and micro-structure
Assaf, Y., Alexander, D. C., Jones, D. K., Bizzi, A., Behrens, T. E. J., Clark, C. A., Cohen, Y., Dyrby, T. B., Hüppi, P. S., Knoesche, T. R., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.055 · Cited by 139
Scherrer, B., Schwartzman, A., Taquet, M., Sahin, M., Prabhu, S., & Warfield, S. (2015) · Magnetic Resonance in Medicine · doi:10.1002/mrm.25912 · Cited by 137 · cited 5×
“It is therefore reasonable to consider that the intra-axonal volume (of axons within a given fixel) is a quantity related to the white matter's local ‘ability to relay information’.”
BackgroundMethodInfluentialReorientation of fiber orientation distributions using apodized point spread functions
Raffelt, D., Tournier, J.-D., Crozier, S., Connelly, A., & Salvado, O. (2012) · Magnetic Resonance in Medicine · doi:10.1002/mrm.23058 · Cited by 132 · cited 26×
“While FODs benefit from high angular resolution and high b-value DWI data, FOD registration is best performed using a relatively low spherical harmonic degree of 4 (Raffelt et al., 2011).”
BackgroundMethodInfluentialSelf-citationPGSE , OGSE , and sensitivity to axon diameter in diffusion MRI : Insight from a simulation study
Drobnjak, I., Zhang, H. G., Ianuș, A., Kaden, E., & Alexander, D. C. (2015) · Magnetic Resonance in Medicine · doi:10.1002/mrm.25631 · Cited by 128 · cited 1×
“However, most white matter voxels are known to contain crossing fibres (Jeurissen et al., 2012), and voxel-averaged measures such as FA are not fibre-specific (or even erroneous) in such regions, which confounds interpretation of apparent differences (Douaud et al., 2011; Pierpaoli et al., 2001;…”
BackgroundValidity of modulation and optimal settings for advanced voxel-based morphometry
Raduà, J., Canales-Rodríguez, E. J., Pomarol-Clotet, E., & Salvador, R. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.07.084 · Cited by 122 · cited 1×
“…note that the combined FDC analysis may not always be more sensitive if the effect of interest is predominantly in either FD or FC, since combining FD and FC also combines the variance from each source (see also the argument that modulation in VBM can increase variability, Radua et al. (2014)).”
BackgroundNeural connectivity as an intermediate phenotype: Brain networks under genetic control
Meyer‐Lindenberg, A. (2009) · Human Brain Mapping · doi:10.1002/hbm.20639 · Cited by 118 · cited 1×
“…(Mills and Tamnes, 2014), aging (Lebel et al., 2012), individual differences and brain-behaviour correlations (Johansen-Berg, 2010), genetics (Meyer-Lindenberg, 2009), structural plasticity (Scholz et al., 2009), treatment response (Szeszko et al., 2014) and neuroscientific efforts to relate…”
BackgroundNeuroimaging of motor neuron diseases
Kassubek, J., Ludolph, A., & Müller, H.-P. (2012) · Therapeutic Advances in Neurological Disorders · doi:10.1177/1756285612437562 · Cited by 94 · cited 1×
“…Corr Melbou E-m journal homepage: www.elsevier.com/locate/neuroimage Investigating white matter fibre density and morphology using fixel-based analysis David A. Raffelt a,n, J.-Donald Tournier b,c, Robert E. Smith a, David N. Vaughan a,d,e, Graeme Jackson a,d,f, Gerard R. Ridgway g,h, Alan…”
MethodGroeschel, S., Tournier, J., Northam, G. B., Baldeweg, T., Wyatt, J. S., Vollmer, B., & Connelly, A. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.10.034 · Cited by 93
Self-citationEvaluating the Accuracy of Diffusion MRI Models in White Matter
Rokem, A., Yeatman, J. D., Pestilli, F., Kay, K. N., Mezer, A., van der Walt, S., & Wandell, B. (2015) · PLoS ONE · doi:10.1371/journal.pone.0123272 · Cited by 91 · cited 1×
“1 Previous publications have used the word ‘fibre’ (Assaf and Basser, 2005), ‘fascicle’ (Rokem et al., 2015; Scherrer and Warfield, 2012) or ‘fibre population’ (Behrens et al.”
Parametric Representation of Multiple White Matter Fascicles from Cube and Sphere Diffusion MRI
Scherrer, B., & Warfield, S. (2012) · PLoS ONE · doi:10.1371/journal.pone.0048232 · Cited by 86 · cited 2×
“However, we note that the proposed fixel-based analysis framework can be used to investigate other measures of interest, such as fixel-specific diffusivity measures (Scherrer et al., 2016; Scherrer and Warfield, 2012), or relaxometry (De Santis et al.”
MethodGee, J. (1999) · Pattern Recognition · doi:10.1016/s0031-3203(98)00093-4 · Cited by 85 · cited 5×
“To investigate white matter morphology, many previous studies have used VBM (Mechelli et al., 2005), which can be thought of as a TBM analysis weighted/masked by the tissue segmentation (note this is only true for modern VBM methods where images are registered as accurately as possible and modulated by the Jacobian de…”
MethodInfluentialRadanovic, M., Pereira, F., Stella, F., Aprahamian, I., Ferreira, L. K., Forlenza, O. V., & Busatto, G. F. (2013) · Expert Review of Neurotherapeutics · doi:10.1586/ern.13.45 · Cited by 85 · cited 3×
“Contents lists available at ScienceDirect NeuroImage http://d 1053-81 Abbre restricte DWI, di section; populat metry; width a ratio; SP voxel-b n Corr Melbou E-m journal homepage: www.elsevier.com/locate/neuroimage Investigating white matter fibre density and morphology using fixel-based analysis David A. Raffelt a,n,…”
BackgroundMethodInfluentialRiffert, T. W., Schreiber, J., Anwander, A., & Knösche, T. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.06.015 · Cited by 74
Zhang, H., Awatea, S. P., Das, S. R., Woo, J., Melhem, E., Gee, J., & Yushkevich, P. (2010) · Medical Image Anal. · doi:10.1016/j.media.2010.05.002 · Cited by 69 · cited 1×
“In related work, Zhang et al. (2010) also proposed a combined analysis of microscopic measures with macroscopic morphology.”
BackgroundThe effect of template selection on diffusion tensor voxel-based analysis results
van Hecke, W., Leemans, A., Sage, C., Emsell, L., Veraart, J., Sijbers, J., Sunaert, S., & Parizel, P. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.12.005 · Cited by 67 · cited 3×
“In vivo methods to quantify white matter changes that alter connectivity are also of interest in relation to psychiatric disorders (Kubicki under the CC BY license (http://creativecommons.org/licenses/by/4.0/). et al., 2007), development (Mills and Tamnes, 2014), aging (Lebel et al., 2012), individual differences and…”
BackgroundInfluentialT1 relaxometry of crossing fibres in the human brain
Santis, S. D., Assaf, Y., Jeurissen, B., Jones, D., & Roebroeck, A. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.07.037 · Cited by 55
Santis, S. D., Assaf, Y., Evans, C. J., & Jones, D. (2014) · Magnetic Resonance in Medicine · doi:10.1002/mrm.24717 · Cited by 53
Calamante, F., Masterton, R. A. J., Tournier, J., Smith, R. E., Willats, L., Raffelt, D. A., & Connelly, A. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.12.054 · Cited by 49 · cited 1×
“, 2014) and neuroscientific efforts to relate structural and functional connectivity (Calamante et al., 2013; Stephan et al., 2009; Van Den Heuvel et al., 2009).”
BackgroundSelf-citationMohammadi, S., Keller, S. S., Glauche, V., Kugel, H., Jansen, A., Hutton, C., Flöel, A., & Deppe, M. (2012) · PLoS ONE · doi:10.1371/journal.pone.0036851 · Cited by 41
Kernel regression estimation of fiber orientation mixtures in diffusion MRI
Cabeen, R. P., Bastin, M. E., & Laidlaw, D. H. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.11.061 · Cited by 37 · cited 2×
“…2014), apparent fibre density (Dell’acqua et al., 2010; Raffelt et al., 2012b), neurite density (Jespersen et al., 2010; Zhang et al., 2012), intra-axonal volume fraction (Panagiotaki et al., 2012) fibre volume fraction (Cabeen et al., 2015), fascicle fraction of occupancy (Scherrer et al., 2016)).”
BackgroundCorrection: Evaluating the Accuracy of Diffusion MRI Models in White Matter
Rokem, A., Yeatman, J. D., Pestilli, F., Kay, K. N., Mezer, A., van der Walt, S., & Wandell, B. (2014) · PLoS ONE · doi:10.1371/journal.pone.0139150 · Cited by 19 · cited 1×
“1 Previous publications have used the word ‘fibre’ (Assaf and Basser, 2005), ‘fascicle’ (Rokem et al., 2015; Scherrer and Warfield, 2012) or ‘fibre population’ (Behrens et al., 2007; Raffelt et al., 2012b) to refer to a specific population of fibres within a single voxel.”
MethodFiber density estimation from single q-shell diffusion imaging by tensor divergence
Reisert, M., Mader, I., Umarova, R., Maier, S., van Elst, L. V., & Kiselev, V. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.03.032 · Cited by 19 · cited 1×
“…2005; Barazany et al., 2009; Jespersen et al., 2007; Lu et al., 2006; Raffelt et al., 2012b; Stanisz et al., 1997; Zhang et al., 2012), and that the exchange of water between the intra-axonal and extra-axonal space is negligible on the timescale of a diffusion MRI experiment (Quirk et al., 2003).”
BackgroundRibeiro, L. C. D. Q., & Ribeiro, M. G. (2017) · doi:10.1007/978-3-319-51899-2_3 · Cited by 18 · cited 2×
“…known to contain crossing fibres (Jeurissen et al., 2012), and voxel-averaged measures such as FA are not fibre-specific (or even erroneous) in such regions, which confounds interpretation of apparent differences (Douaud et al., 2011; Pierpaoli et al., 2001; Wheeler-Kingshott and Cercignani, 2009).”
BackgroundTensor-Based Morphometry of Fibrous Structures with Application to Human Brain White Matter
Zhang, H., Yushkevich, P., Rueckert, D., & Gee, J. (2009) · International Conference on Medical Image Computing and Computer-Assisted Intervention · doi:10.1007/978-3-642-04271-3_57 · Cited by 6 · cited 8×
“(3) (derived independently in Raffelt et al. (2010)) is mathematically equivalent to the method for computing the change in fibre cross-section in Zhang et al. (2009).”
BackgroundMethodInfluential
Flagged first, then by citations
10 of the 91 references couldn’t be matched to a known paper.
Research works printed but not linked: 3
- Jackson, 1993, Optimizing the diagnosis of hippocampal sclerosis using MR imaging, Am. J. Neuroradiol., 14, 753
- Raffelt, D., Crozier, S., Connelly, A., Salvado, O., Tournier, J.-D., 2010. Apparent fibre density: a new measure for high angular resolution diffusion-weighted image analysis. In: Proceedings of the International Society for Magnetic Resonance in Medicine. Presented at the International Society for Magnetic Resonance in Medicine, Stockholm. Sweden, p. 575.
- Tournier, J.-D., Calamante, F., Connelly, A., 2013. A robust spherical deconvolution method for the analysis of low SNR or low angular resolution diffusion data. In: Proceedings of the International Society for Magnetic Resonance in Medicine. Salt Lake City, Utah, USA.
Cited by
Sorted by citations
MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation
Tournier, J.-D., Smith, R., Raffelt, D., Tabbara, R., Dhollander, T., Pietsch, M., Christiaens, D., Jeurissen, B., Yeh, C.-H., & Connelly, A. (2019) · bioRxiv · doi:10.1101/551739 · Cited by 3,043
Self-citationMRtrix3: A fast, flexible and open software framework for medical image processing and visualisation
Tournier, J.-D., Smith, R., Raffelt, D., Tabbara, R., Dhollander, T., Pietsch, M., Christiaens, D., Jeurissen, B., Yeh, C.-H., & Connelly, A. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116137 · Cited by 2,974
Self-citationGorgolewski, K. J., Alfaro-Almagro, F., Auer, T., Bellec, P., Capotă, M., Chakravarty, M. M., Churchill, N. W., Cohen, A. L., Craddock, R. C., Devenyi, G. A., et al. (2017) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1005209 · Cited by 311
Self-citationFibre-specific white matter reductions in Alzheimer’s disease and mild cognitive impairment
Mito, R., Raffelt, D., Dhollander, T., Vaughan, D. N., Tournier, J.-D., Salvado, O., Brodtmann, A., Rowe, C. C., Villemagne, V. L., & Connelly, A. (2018) · Brain · doi:10.1093/brain/awx355 · Cited by 309
“…for both microstructural changes in density (with the fibre density metric), and macrostructural, morphometric changes (with the fibre bundle cross-section metric) enables a more comprehensive analysis of total intra-axonal volume changes within a fibre pathway (FDC metric) (Raffelt et al., 2017).”
BackgroundMethodInfluentialSelf-citationFixel-based Analysis of Diffusion MRI: Methods, Applications, Challenges and Opportunities
Dhollander, T., Clemente, A., Singh, M., Boonstra, F., Civier, O., Duque, J. D., Egorova, N., Enticott, P., Fuelscher, I., Gajamange, S., et al. (2020) · NeuroImage · doi:10.31219/osf.io/zu8fv · Cited by 271
Self-citation
Metadata
- Authors
- Raffelt, D. A., Tournier, J.-D., Smith, R. E., Vaughan, D. N., Jackson, G., Ridgway, G. R., & Connelly, A.
- Affiliations
- Florey Institute of Neuroscience and Mental Health (AU)
- King's College London (GB)
- The University of Melbourne (AU)
- Wellcome Centre for Human Neuroimaging (GB)
- Corresponding author
- Raffelt, David A.
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2017-01
- Volume
- 144
- Issue
- Pt A
- Pages
- 58-73
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC5182031
- OpenAlex
- W2520744072
- Cited by
- 620
- References
- 91
- Citations by year
- 2026: 74 · 2025: 79 · 2024: 78 · 2023: 76 · 2022: 84 · 2021: 91 · 2020: 71 · 2019: 30 · 2018: 26 · 2017: 9
- FWCI
- 19.39
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- NeuroImage (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Research Portal (King's College London) (submittedVersion, cc-by)
- Funders
- National Health and Medical Research Council (NHMRC)
- Victorian Government’s Operational Infrastructure
- UK Medical Research Council (MR/J014257/2)
- Wellcome Trust (091593/Z/10/Z)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- fixel-based analysis, crossing fibers, axon number
- MeSH terms
- Humans, Nerve Fibers, Myelinated, Diffusion Magnetic Resonance Imaging, White Matter
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