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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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MethodVoxel-Based Morphometry—The Methods
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MethodPermutation inference for the general linear model
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MethodSelf-citationProbabilistic diffusion tractography with multiple fibre orientations: What can we gain?
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Scholz, J., Klein, M. C., Behrens, T. E. J., & Johansen-Berg, H. (2009) · Nature Neuroscience · doi:10.1038/nn.2412 · Cited by 1,508 · cited 1×
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BackgroundSelf-citationDiffusion tensor imaging of white matter tract evolution over the lifespan
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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.”
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Items 301–400 of 604
Genc, S., Malpas, C., Gulenc, A., Sciberras, E., Efron, D., Silk, T., & Seal, M. (2019) · bioRxiv · doi:10.1101/607671 · Cited by 9
“The recently introduced fixel-based analysis (FBA) framework (Raffelt et al. 2017) and subsequent longitudinal modifications to this (Genc et al. 2018), allows the quantification of white matter fibre properties such as fibre density and morphology (see Box 1 for detailed interpretations).”
BackgroundMethodInfluentialColaes, R., Schroyen, G., Radwan, A., Laic, R. A. G., Helsper, S., Himmelreich, U., Hatse, S., Smeets, A., Caeyenberghs, K., Sunaert, S. G., et al. (2025) · Cancer · doi:10.1002/cncr.70095 · Cited by 8
“25,26 The use of FBA to study chemotherapy - induced changes in WM structure remains limited.”
Wang, M., Xiaomei, Z., 周鹤同, Chen, Q., Tong, Q., Han, Q., Zhao, X., Wang, D., Lai, J., He, H., et al. (2025) · BMC Medicine · doi:10.1186/s12916-025-04174-z · Cited by 8
“Physiologically, targeting these regions with high white matter fiber density could indicate stronger neural connections [47, 48], thereby offering a novel and potentially more effective method for localizing stimulation sites.”
Maleki, S., Hendrikse, J., Richardson, K., Segrave, R. A., Hughes, S., Kayayan, E., Oldham, S., Syeda, W., Coxon, J., Caeyenberghs, K., et al. (2024) · Translational Psychiatry · doi:10.1038/s41398-024-03150-0 · Cited by 8
“…34]; (2) employ advanced pre-processing such as outlier replacement [35] and slice to volume motion correction [36]; (3) fi lter reconstructed WM streamlines to be more biologically plausible [37]; (4) estimate speci fi c measures of WM microstructure such as fi bre density and cross-section [22].”
MethodHow fiber bundle alterations differ in presumed LATE and amnestic Alzheimer's disease
Lebrun, A., Leprince, Y., Lagarde, J., Olivieri, P., Moussion, M., Noiray, C., Bottlaender, M., & Sarazin, M. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.14156 · Cited by 8
“17,18 This method overcomes a major confound of clas-sicdiffusionMRImodelsinthepresenceofcrossingfibers,bydefininga newbasicelementcalledfixel,representingonefiberpopulationwithin a voxel.”
Tagliaferri, M., Amorosino, G., Voltolini, L., Giampiccolo, D., Avesani, P., & Cattaneo, L. (2024) · Brain Structure and Function · doi:10.1007/s00429-024-02778-4 · Cited by 8
“…we have included in our analysis specific indi - ces for the microstructural characterization of white matter tracts such as the fiber density (FD), the fiber cross-section (FC), and a combined measure of the fiber density and the cross-section (FDC) within the FAT bundles (Raffelt et al. 2017).”
Nkrumah, R., von Schröder, C., Demirakca, T., Schmahl, C., & Ende, G. (2023) · Neurobiology of Stress · doi:10.1016/j.ynstr.2023.100586 · Cited by 8
“Despite these findings, quantitative measures based on averaging voxels are not fibre-specific and may have limited interpretability because most WM voxels contain contributions from multiple fibre populations (commonly referred to as crossing fibres) (Raffelt et al., 2017).”
Fiber‐Specific White Matter Alterations in Parkinson's Disease Patients with GBA Gene Mutations
Andica, C., Kamagata, K., Uchida, W., Saito, Y., Takabayashi, K., Hagiwara, A., Takeshige-Amano, H., Hatano, T., Hattori, N., & Aoki, S. (2023) · Movement Disorders · doi:10.1002/mds.29578 · Cited by 8
“20 Second, FC is a morphological measure of fi ber bundle size calculated as the extent of distortion in the bundle cross section required to warp a participant ’ s fi ber orientation distribution into the template image.”
BackgroundMethodInfluentialMapping human brain pathways: challenges and opportunities in the integration of scales
Charvet, C. (2023) · Brain, Behavior and Evolution · doi:10.1159/000530317 · Cited by 8
“…AxCaliber, ActiveAx, neurite orientation dispersion and density imaging [NODDI]: NODDI-Watson, NODDI-Bingham, and NODDIDTI models; Assaf et al., 2008; Alexander et al., 2010; Zhang et al., 2011; Xu et al., 2014; Raffelt et al., 2017; Genc et al., 2018; Huang et al., 2020; Dhollander et al., 2021).”
Investigating Tissue-Specific Abnormalities in Alzheimer’s Disease with Multi-Shell Diffusion MRI
Giraldo, D. L., Smith, R. E., Struyfs, H., Niemantsverdriet, E., Roeck, E. E. D., Bjerke, M., Engelborghs, S., Romero, E., Sijbers, J., & Jeurissen, B. (2022) · Journal of Alzheimer s Disease · doi:10.3233/jad-220551 · Cited by 10
“However, the original FBA pipeline [37] explicitly recommends combining AFD with FC to obtain a third measure, called FDC, that reflects ‘the ability to relay information’.”
MethodInfluentialSelf-citationMito, R., Parker, D., Abbott, D., Makdissi, M., Pedersen, M., & Jackson, G. (2022) · Brain Communications · doi:10.1093/braincomms/fcac208 · Cited by 8
“Decreases in this FD metric can be interpreted as a loss of axons.(36,53) In contrast, increases in FD can be in-”
BackgroundMethodInfluentialSelf-citationKirkovski, M., Singh, M., Dhollander, T., Fuelscher, I., Hyde, C., Albein-Urios, N., Donaldson, P., & Enticott, P. (2022) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-023-05980-1 · Cited by 8
“Lastly, fixel-wise metrics of FD, FC and FDC were computed across all template fixels for subsequent inferential analysis (Raffelt et al., 2017 ).”
BackgroundMethodRetinal ganglion cell endowment is correlated with optic tract fiber cross section, not density
Taskin, H. O., Qiao, Y.-C., Sydnor, V., Cieslak, M., Haggerty, E. B., Satterthwaite, T., Morgan, J. I. W., Shi, Y.-G., & Aguirre, G. (2022) · bioRxiv · doi:10.1101/2022.03.30.486288 · Cited by 8
Patterns of white and gray structural abnormality associated with paediatric demyelinating disorders
Bells, S., Longoni, G., Berenbaum, T. S., de Medeiros, C. B., Narayanan, S., Banwell, B., Arnold, D. L., Mabbott, D., & Yeh, E. A. (2022) · NeuroImage Clinical · doi:10.1016/j.nicl.2022.103001 · Cited by 7
“FBA is based on constrained spherical deconvolution (CSD), thus accounting for crossing fibres and is sensitive to structural intra-axonal volume changes (Raffelt et al., 2017).”
High fidelity fiber orientation density functions from fiber ball imaging
Moss, H., & Jensen, J. (2021) · NMR in Biomedicine · doi:10.1002/nbm.4613 · Cited by 8
Childhood conduct problems are associated with reduced white matter fibre density and morphology
Burley, D. T., Genc, S., & Silk, T. J. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.11.098 · Cited by 11
Richards, K., Jancovski, N., Hanssen, E. G., Connelly, A., & Petrou, S. (2020) · Brain Research · doi:10.1016/j.brainres.2020.147157 · Cited by 9
Self-citationGronemann, D. C., Koch, K., Bantel, C., & Sörös, P. (2020) · medRxiv · doi:10.1101/2020.04.16.20068197 · Cited by 13
Wu, D., Lei, J., Xie, H., Dong, J., & Burd, I. (2020) · Brain Imaging and Behavior · doi:10.1007/s11682-019-00246-w · Cited by 8
Pagnozzi, A., Pannek, K., Boyd, R., van Eijk, L., George, J., Bora, S., Bradford, D., Fahey, M., Ditchfield, M., Malhotra, A., et al. (2025) · Neuroimage: Reports · doi:10.1016/j.ynirp.2025.100262 · Cited by 7
“More advanced diffusion models such as fixel-based analysis (Raffelt et al., 2017) provided advantages over simpler models such as DTI in their ability to resolve crossing fibres, and demonstrated stronger associations with motor and cognitive outcomes compared to DTI on the same cohort (Pannek et…”
Fibre density and cross-section associate with hallmark pathology in early Alzheimer’s disease
Vanderlinden, G., Radwan, A., Christiaens, D., Blommaert, J., Sunaert, S. G., Vandenbulcke, M., Koole, M. J. B., & Laere, K. V. (2025) · Alzheimer s Research & Therapy · doi:10.1186/s13195-025-01710-0 · Cited by 7
“Correspondingly, measures of apparent fibre density (FD), fibre cross-section (FC) or a combination of both apparent fibre density and cross-section (FDC) can be derived from a fixel-based analysis (FBA) to investigate microstructural (FD) and macroscopic (FC) differences in WM bundles [35].”
InfluentialGlymphatic dysfunction and neurodegeneration in ALS: Longitudinal insights from rNLS8 TDP-43 mice
Zamani, A., Walker, A. K., & Wright, D. K. (2025) · Neurobiology of Disease · doi:10.1016/j.nbd.2025.106832 · Cited by 6
“FDC, a value derived for each fixel, represents that white matter fiber ’ s ability to relay information with reduced values reflecting decreased ability (Raffelt et al., 2017).”
Mochel, F., Méneret, A., Adanyeguh, I. M., Giron, C., Hainque, É., Luton, M., Atencio, M., Debs, R., Jacobs, M., Veldkamp, F., et al. (2024) · Neurology · doi:10.1212/wnl.0000000000210194 · Cited by 6
Pontillo, G., Prados, F., Wink, A. M., Kanber, B., Bisecco, A., Broeders, T. A. A., Brunetti, A., Cagol, A., Calabrese, M., Castellaro, M., et al. (2024) · Human Brain Mapping · doi:10.1002/hbm.70107 · Cited by 9
Subtle motor signs in children with ADHD and their white matter correlates
Hyde, C., Fuelscher, I., Rosch, K., Seymour, K., Crocetti, D., Silk, T., Singh, M., & Mostofsky, S. (2024) · Human Brain Mapping · doi:10.1002/hbm.70002 · Cited by 7
“…al., 2021), variability in FC may reflect individual differences myelination or extracellular space between fiber bundles (Genc et al., 2018, 2020), with greater FC reflecting an increased efficiency in transmitting information (Raffelt, Dhollander, et al., 2017; Raffelt, Tournier, et al., 2017).”
BackgroundMethodInfluentialLiu, S., Ma, X., Yu, S., Weng, X., Li, M., Zhu, J., Liu, C.-F., & Hu, H. (2024) · Clinical Interventions in Aging · doi:10.2147/cia.s438782 · Cited by 9
“11 Using nonlinear distortion to calculate the spatial normalization of the subject image to the template image, structural differences can be estimated for each FC (in a plane perpendicular to the fixed direction).”
BackgroundMethodInfluentialXu, R., Wang, X.-M., Zhu, S., Jiang, B., Wan, J.-Y., Ma, J., Yu, Y.-X., Yu, L.-Q., Fang, Q., Hu, C.-H., et al. (2023) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.29171 · Cited by 7
Post-traumatic headache pathophysiology in paediatric concussion: A systematic review.
Fan, F., Anderson, V., Morawakage, T., Khan, N., Shapiro, J., Ignjatović, V., & Takagi, M. (2023) · Neuroscience and Biobehavioral Reviews · doi:10.1016/j.neubiorev.2023.105498 · Cited by 7
ModelArray: An R package for statistical analysis of fixel-wise data
Zhao, C., Tapera, T. M., Bagautdinova, J., Bourque, J., Covitz, S. C., Gur, R. E., Gur, R. C., Larsen, B., Mehta, K. P., Meisler, S. L., et al. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120037 · Cited by 11
Hsu, C., Chong, S., Kung, Y.-C., Kuo, K.-T., Huang, C.-C., & Lin, C.-P. (2023) · Human Brain Mapping · doi:10.1002/hbm.26239 · Cited by 7
Bartoňová, M., Tournier, J.-D., Barton, M., Říha, P., Vojtíšek, L., Mareček, R., Doležalová, I., & Rektor, I. (2023) · Scientific Reports · doi:10.1038/s41598-022-27233-4 · Cited by 7
Self-citationVanes, L. D., Tye, C., Tournier, J.-D., Combes, A. J. E., Shephard, E., Liang, H.-L., Barker, G., Nosarti, C., & Bolton, P. (2022) · NeuroImage: Clinical · doi:10.1016/j.nicl.2022.103163 · Cited by 7
Self-citationGrazioplene, R. G., DeYoung, C., Hampson, M., Anticevic, A., & Pittenger, C. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-02013-w · Cited by 7
“FD captures the volume of the intraaxonal restricted compartment, while FC is a more macrostructural approximation of the relative white-matter bundle size (relative to the study population); FDC is simply, a combined measure that modulates density by cross-section [27].”
BackgroundMethodStructural connectome-based prediction of trait anxiety
Yoo, C., Park, S., & Kim, M. J. (2022) · Brain Imaging and Behavior · doi:10.1007/s11682-022-00700-2 · Cited by 9
“Then the fiber orientation density (FOD) data were normalized in order to enable valid comparisons across subjects (Raffelt et al., 2017; Dhollander et al., 2021).”
MethodBlack, S. R., Janson, A. P., Mahan, M. A., Anderson, J. S., & Butson, C. R. (2021) · Neuromodulation Technology at the Neural Interface · doi:10.1111/ner.13399 · Cited by 9
“We used MRtrix3 (29) for bias field corrections, intensity normalization, and all other analysis steps.”
MethodHuynh, V., Stämpfli, P., Lütolf, R., Luechinger, R., Curt, A. E. P., Kollias, S., Hubli, M., & Michels, L. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.598336 · Cited by 7
“This marker is related to the volume of the intraaxonal compartment per unit of tissue volume, and is therefore sensitive to the volume of a fiber bundle (26, 27).”
BackgroundAge-related differences in white matter: Comparing fixel based and tensor based analysesPreprint
Kelley, S., Plass, J., Bender, A. R., & Polk, T. (2019) · bioRxiv · doi:10.1101/751628 · Cited by 7
“Additionally, FBA can be used to analyze the morphometrically-estimated cross-sectional size of fiber pathways, allowing for independent analysis of microstructural measures of fiber density (FD) and macrostructural measures of fiber cross-section (FC) (Raffelt et al., 2017).”
MethodThe Discriminative Power of White Matter Microstructures for Autism Diagnosis
Zhang, Z., & Zheng, W. (2020) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2021.04.121 · Cited by 7
Singh, M., Skippen, P., He, J. L., Thomson, P., Fuelscher, I. T., Caeyenberghs, K., Anderson, V. A., Hyde, C. E., & Silk, T. J. (2024) · Human Brain Mapping · doi:10.1002/hbm.70010 · Cited by 5
“The FBA framework is robust to intra-voxel changes in fibre orientation (Dhollander et al., 2021; Raffelt et al., 2017), thus providing a more biologically specific approach with which to quantify changes in WM properties compared to tensor-based models.”
BackgroundKristensen, T. D., Ambrosen, K., Raghava, J., Syeda, W., Dhollander, T., Lemvigh, C., Bojesen, K., Barber, A. D., Nielsen, M. O., Rostrup, E., et al. (2024) · Schizophrenia · doi:10.1038/s41537-024-00487-9 · Cited by 6
“Our results indicate that increased FC is associated with more cognitive fl exibility in patients, which correspond with previous associations of reduced FC with brain atrophy and degeneration 10 .”
BackgroundMethodResultInfluentialUnsupervised Dimensionality Reduction Techniques for the Assessment of ASD Biomarkers
Jacokes, Z., Adoremos, I., Hussain, A., Newman, B., Pelphrey, K., & Horn, J. V. V. (2024) · medRxiv · doi:10.1142/9789819807024_0044 · Cited by 6
“…spherical deconvolution (CSD) to obtain 3 tissue CSD (3T-CSD) microstructure compartments (intra-and extra-cellular isotropic signal, and intra-cellular anisotropic signal) and a fixel-based analysis was used to measure axonal fiber density and cross-section on a voxel-wise basis 11,26,29,30 .”
Spatola, G., Triebkorn, P., Richieri, R., Baunez, C., Farisse, J., Cretol, A., Guedj, E., Jirsa, V., & Régis, J. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e34699 · Cited by 6
“More recent approaches, such as constrained spherical deconvolution, can identify multiple fibres within a voxel [22], which enables fixel based analysis (FBA) to test for fibre specific changes in white matter [23].”
BackgroundMethodInfluentialMills, E. P., Bosma, R., Rogachov, A., Cheng, J. C., Osborne, N., Kim, J. A., Besik, A., Bhatia, A., & Davis, K. D. (2024) · Journal of Pain · doi:10.1016/j.jpain.2024.104536 · Cited by 6
Zhang, J., Li, L., Ji, R., Shang, D., Wen, X., Hu, J., Wang, Y., Wu, D., Zhang, L., He, F., et al. (2023) · Translational Stroke Research · doi:10.1007/s12975-023-01221-w · Cited by 3
“The subsequent steps for obtaining fixel-wise metrics, with “fixel” being a term defined in Raffelt’s study [27], included segmenting fixels of the FOD template, estimating apparent fiber density (FD), reorienting fixels, assigning fixels to the template, and generating FD and fiber cross-section…”
Progressive white matter degeneration in patients with spinocerebellar ataxia type 2
Tu, Y., Li, Z., Xiong, F., & Gao, F. (2023) · Neuroradiology · doi:10.1007/s00234-023-03260-4 · Cited by 6
“FBA can evaluate the micro-structure and macrostructure of brain white matter via three metrics: fiber density (FD) for microstructure, fiber-bundle cross-section (FC) for macro-structure), and a combination of them (fiber density and cross-section, FDC) [9].”
InfluentialGlobally altered microstructural properties and network topology in Rasmussen’s encephalitis
Held, N. R., Bauer, T., Reiter, J. T., Hoppe, C., Keil, V. C. W., Radbruch, A., Helmstaedter, C., Surges, R., & Rüber, T. (2023) · Brain Communications · doi:10.1093/braincomms/fcad290 · Cited by 6
“13 For network-based statistics on structural connectomes, we performed non-parametric permutation testing over 5000 permutations using the threshold-free network-based statistics algorithm 26 if not indicated otherwise to compute FWE-corrected P -values for each connectome edge.”
BackgroundMethodInfluentialNelson, M. C., Royer, J., Lu, W. D., Leppert, I. R., Campbell, J. S. W., Schiavi, S., Jin, H., Tavakol, S., de Wael, R. V., Rodríguez‐Cruces, R., et al. (2023) · Network Neuroscience · doi:10.1162/netn_a_00330 · Cited by 17
“In particular, track-weighted imaging (Calamante, 2017; Calamante et al., 2010, 2012) and fixel-based analysis (Dhollander et al., 2021; Raffelt et al., 2015, 2017) provide state-of-the-art solutions to the challenge of quantifying white matter structural features in the presence of crossing fibers.”
BackgroundFixel‐Based Analysis Reveals Whole‐Brain White Matter Abnormalities in Cervical Dystonia
Zito, G., Tarrano, C., Ouarab, S., Jegatheesan, P., Ekmen, A., Béranger, B., Valabrègue, R., Hubsch, C., Sangla, S., Bonnet, C., et al. (2023) · Movement Disorders · doi:10.1002/mds.29425 · Cited by 6
Rasooli, A., Adab, H. Z., van Ruitenbeek, P., Weerasekera, A., Chalavi, S., Cuypers, K., Levin, O., Dhollander, T., Peeters, R. R., Sunaert, S. G., et al. (2023) · iScience · doi:10.1016/j.isci.2023.106794 · Cited by 6
“Moreover, it has been widely used to study FD in a fiber population-specific approach.(21,22) Reduced FD can indicate shrinkage or loss of axons in WM-related neurodegenerative diseases such as multiple sclerosis(23)while increased FD can designate an increased number of axons or diameter of the fibers in the process…”
MethodChary, K., Manninen, E., Claessens, J., Ramírez-Manzanares, A., Gröhn, O. H. J., & Sierra, A. (2023) · Scientific Reports · doi:10.1038/s41598-023-29010-3 · Cited by 10
A unified global tractography framework for automatic visual pathway reconstruction
He, J., Yao, S., Zeng, Q., Chen, J., Sang, T., Xie, L., Pan, Y., & Feng, Y. (2023) · NMR in Biomedicine · doi:10.1002/nbm.4904 · Cited by 7
Singh, M., Skippen, P., He, J. L., Thomson, P., Fuelscher, I. T., Caeyenberghs, K., Anderson, V. A., Nicholson, J. M., Hyde, C. E., & Silk, T. J. (2022) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2022.101171 · Cited by 7
Ali, T., Lv, J., & Calamante, F. (2022) · Magnetic Resonance in Medicine · doi:10.1002/mrm.29413 · Cited by 8
“cortex; (43): primary gustatory cortex; (44): pars opercularis; (45): pars triangularis; (46): dorsolateral prefrontal cortex; (47): pars orbitalis;”
Symptoms reported by Canadians posted in Havana are linked with reduced white matter fibre density
Aristi, G., Kamintsky, L., Ross, M., Bowen, C. V., Calkin, C., Friedman, A., & Hashmi, J. A. (2022) · Brain Communications · doi:10.1093/braincomms/fcac053 · Cited by 5
“This technique uses constrained spherical deconvolution (CSD) to provide micro- and macro-structure estimations for individual WM tracts in a voxel, modelled as ‘fixels’, which refers to a specific fibre population within a single voxel.(11,12) FBA uses the metrics fibre density (FD) and fibre cross-section (FC) to ca…”
MethodInfluentialOptimized rectification of fiber orientation density function
Moss, H., & Jensen, J. (2020) · Magnetic Resonance in Medicine · doi:10.1002/mrm.28406 · Cited by 6
“For the mathematical model with Gibbs ringing, the original fODF was taken to be the approximation of Equation 16, whereas the optimized fODF was determined from (9) ∫ dΩn [|F (n)− |−F (n)− ]=0.”
MethodEvaluation of cerebellar function scores in relation to cerebellar axonal loss in multiple sclerosisPreprint
Boonstra, F., Gajamange, S., Noffs, G., Perera, T., Strik, M., Vogel, A. P., Butzkueven, H., Evans, A., van der Walt, A., & Kolbe, S. (2020) · bioRxiv · doi:10.1101/2020.05.15.094938 · Cited by 6
“In addition, the use of the combined measure also allows for a less biased and more sensitive measure compared to fibre density and crosssection separately as it does not suffer from inherent inter-dependency (18).”
BackgroundMethodInfluentialDiscriminating VCID subgroups: A diffusion MRI multi-model fusion approach
Raja, R., Caprihan, A., Rosenberg, G., Rachakonda, S., & Calhoun, V. (2020) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2020.108598 · Cited by 6
“Fiber specific metrics such as track density imaging and average pathlength maps can be calculated based on CSD model [15, 16].”
MethodAdvances in Neuroimaging for Neurodegenerative Disease
Veldsman, M., & Egorova, N. (2017) · Advances in neurobiology · doi:10.1007/978-3-319-57193-5_18 · Cited by 9
Developmental xenocortication using human-derived organoids in mice
Kaganovsky, K., Kelley, K. W., Gschwind, T., Harary, P. M., Kochalka, J., White, A. D., Lerma‐Usabiaga, G., Chen, X., Revah, O., Gore, F., et al. (2026) · Nature · doi:10.1038/s41586-026-11032-2 · Cited by 6
“Intensity normalization was performed using mtnormalise 69 with WM and CSF compartments only (three-tissue normalization including GM was unstable for mouse brain data).”
Canonical neurodevelopmental trajectories of structural and functional manifoldsPreprint
Monaghan, A., Bethlehem, R., Akarca, D., Margulies, D., & Astle, D. (2025) · bioRxiv · doi:10.7554/elife.103097 · Cited by 5
Lewandowska, P., Bajada, C., Mysak, Y., Domagalik, A., Kossowski, B., Baumbach, C., Kaczmarek-Majer, K., Degórska, A., Skotak, K., Sitnik-Warchulska, K., et al. (2025) · Human Brain Mapping · doi:10.1002/hbm.70306 · Cited by 5
Ackom, D., Beardsley, S., Meylor, J., Butler, K., Vega, R., Crow, A. J. D., Patel, H., Schmit, B. D., & Javarayee, P. (2025) · Seizure · doi:10.1016/j.seizure.2025.06.001 · Cited by 5
Mills, E. P., Bosma, R., Rogachov, A., Cheng, J. C., Osborne, N., Kim, J. A., Besik, A., El-Sayed, R., Bhatia, A., & Davis, K. D. (2025) · Human Brain Mapping · doi:10.1002/hbm.70135 · Cited by 5
“A detailed description of the computation of these metrics has been previously described (Dhollander et al. 2021; Raffelt et al. 2017).”
InfluentialEquivariant spatio-hemispherical networks for diffusion MRI deconvolution
Elaldi, A., Gerig, G., & Dey, N. (2024) · Neural Information Processing Systems · doi:10.48550/arxiv.2411.11819 · Cited by 5
“1, this yields spatio-spherical images living on 3 × S 2 that are used to map neuronal organization in vivo [7, 44] alongside several other biomedical use cases [35, 37, 56, 65, 71].”
Perdue, M. V., Geeraert, B., Manning, K. Y., Dewey, D., & Lebel, C. A. (2025) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2025.101537 · Cited by 3
“Further, the metrics derived from DTI are not specific to microstructural features of white matter, which leads to vague or ambiguous interpretation (Raffelt et al., 2012; Raffelt, Tournier, et al., 2017).”
Billaud, C., & Yu, J.-H. (2024) · GeroScience · doi:10.1007/s11357-024-01340-8 · Cited by 5
“…proportional to the intra-axonal volume [8], which reflects micro-structural alterations; the fibre-bundle cross-section (FC), estimating the macrostructural alteration of the fibre bundle along the fixel’s orientation; and a metric combination of both independent measures (FDC) [6, 7].”
InfluentialWhite matter structural bases for phase accuracy during tapping synchronization
García-Saldivar, P., de León, C., Salcido, F. A. M., Concha, L., & Merchant, H. (2024) · eLife · doi:10.7554/elife.83838 · Cited by 8
“FBA provides three fiber-specific indices (fiber density, fiber cross-section, and fiber density and cross-section; FD, FC, and FDC, respectively) ( Raffelt et al., 2017 ).”
BackgroundMethodInfluentialBauer, T., von Wrede, R., Pujar, S., Rácz, A., Hoppe, C., Baumgartner, T., Varadkar, S. M., Held, N. R., Reiter, J. T., Enders, S., et al. (2024) · Journal of Neurology · doi:10.1007/s00415-024-12607-7 · Cited by 5
“0.4, https:// www. mrtrix. org /) [16, 17] were performed as described previously [18].”
MethodInfluentialTremblay, S. A., Alasmar, Z., Pirhadi, A., Carbonell, F., Iturria‐Medina, Y., Gauthier, C. J., & Steele, C. J. (2024) · Aperture Neuro · doi:10.52294/001c.118427 · Cited by 8
Hierarchical modelling of crossing fibres in the white matter
Rafipoor, H., Lange, F., Arthofer, C., Cottaar, M., & Jbabdi, S. (2023) · bioRxiv · doi:10.1101/2023.05.24.542138 · Cited by 5
Liao, T.-W., Wang, J.-J., Tsai, C.-C., Wang, P.-N., Chen, Y.-L., Wu, Y.-M., & Wu, Y.-R. (2023) · Biomedical Journal · doi:10.1016/j.bj.2023.100678 · Cited by 5
“Fixel-specific measures, including FD, FC, and FDC, were computed within each voxel of the imaging data [8].”
BackgroundMethodInfluentialSleep Differentially and Profoundly Impairs Recall Memory in a Patient with Fornix Damage
Matorina, N., Tseng, J., Ladyka-Wojcik, N., Olsen, R., Mabbott, D., & Barense, M. D. (2023) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_02038 · Cited by 5
Li, H.-T., Zu, T., Chen, R., Ba, R.-C., Hsu, Y.-C., Sun, Y., Zhang, Y., & Wu, D. (2023) · Magnetic Resonance in Medicine · doi:10.1002/mrm.29769 · Cited by 5
Josev, E., Chen, J., Seal, M., Scheinberg, A., Cole, R. C., Rowe, K., Lubitz, L., & Knight, S. (2023) · Journal of Neuroscience Research · doi:10.1002/jnr.25223 · Cited by 5
Unraveling multi-fixel microstructure with tractography and angular weighting
Delinte, N., Dricot, L., Macq, B. M. M., Gosse, C., Reybroeck, M. V., & Rensonnet, G. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1199568 · Cited by 5
“Abbreviations: AF, arcuate fasciculus; ang, angular weighting; CFE, connectivity-based fixel enhancement; cfo, closest-fixel-only; CSD, constrained sperical deconvolution; CSF, cerebrospinal fluid; DMD, DIAMOND; dMRI, di usion MRI; DTI, di usion tensor imaging; FA, fractional anisotropy; FAT, frontal aslant tract; FBA…”
BackgroundMethodInfluentialWang, C.-C., Tishler, T., Oughourlian, T., Nuechterlein, K., de la Fuente-Sandoval, C., & Ellingson, B. (2023) · Schizophrenia Research · doi:10.1016/j.schres.2023.03.040 · Cited by 5
“Probabilistic tractography using the MRtrix3 software package was performed to calculate the fiber population per voxel, or fixel (Raffelt et al., 2017).”
MethodVerrall, C., Chen, J., Yeh, C.-H., Mackay, M., d'Udekem, Y., Winlaw, D., Iyengar, A., Ayer, J., Gentles, T., Cordina, R., et al. (2022) · NeuroImage: Clinical · doi:10.1016/j.nicl.2022.103151 · Cited by 5
Assessing quantitative MRI techniques using multimodal comparisons
Carter, F., Anwander, A., Johnson, M., Goucha, T., Adamson, H., Friederici, A., Lutti, A., Gauthier, C., Weiskopf, N., Bazin, P., et al. (2022) · bioRxiv · doi:10.1371/journal.pone.0327828 · Cited by 5
“It may be necessary to combine more fibre-specific parameters from multishell DWI [77] with fibre-specific T1/R1 estimates from inversion-recovery DWI [78,79] to more accurately specify this relationship.”
Maturity of white matter tracts is associated with episodic memory recall during development
Bouyeure, A., Bekha, D., Patil, S., Hertz-Pannier, L., & Noulhiane, M. (2022) · Cerebral Cortex Communications · doi:10.1093/texcom/tgac004 · Cited by 5
“…benefit from multishell data to estimate fiber microstructure in a way that overcomes some of the traditional limitations associated to tensor estimation, such as estimation of neurite orientation dispersion and density imaging (NODDI), or fiber density and crosssection (Raffelt et al. 2012, 2017).”
BackgroundFinkelstein, A., Faiyaz, A., Weber, M. T., Qiu, X., Uddin, M., Zhong, J., & Schifitto, G. (2021) · bioRxiv · doi:10.1101/2021.05.06.443022 · Cited by 5
“Fixel-based analysis (FBA) is a recent technique that models individual fibers at the sub-voxel level, termed fixels, which allow tract-specific comparisons (Raffelt et al., 2017).”
BackgroundMethodInfluentialCrystallinity characterization of white matter in the human brain
Teich, E., Cieslak, M., Giesbrecht, B., Vettel, J., Grafton, S. T., Satterthwaite, T., & Bassett, D. (2020) · New Journal of Physics · doi:10.1088/1367-2630/ac1286 · Cited by 5
Arpin, D. J., Subramony, S., Vaillancourt, D., Ashizawa, T., Durr, A., Mareci, T., Klockgether, T., Faber, J., Paulson, H. L., Öz, G., et al. (2025) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.70116 · Cited by 4
“Apparent FD maps were computed by segmenting each fixel of the FOD images, and log-transformed fiber cross-section (FC) maps were calculated from the distortion required when warping the FOD image to the template [22, 35].”
InfluentialTinney, E., Warren, A. E. L., O'Brien, A., Odom, H., Ai, M., Sutton, B., Jain, S., Kang, C., Huang, H.-Q., Wan, L., et al. (2025) · Alzheimer's & Dementia · doi:10.1002/trc2.70125 · Cited by 4
“10,11 This is a critical drawback as it has been estimated that most, if not all, white matter voxels contain crossing fibers.”
Sun, M., Allen, J., Baker, T. L., Spitz, G., Xavier, S., Lee, N. T., Mychasiuk, R., Spencer, S. J., McDonald, S. J., Wright, D. K., et al. (2025) · Experimental Neurology · doi:10.1016/j.expneurol.2025.115368 · Cited by 3
Progressive Myoclonus Epilepsy: Distinctive MRI Changes in Cerebellar and Motor Networks
Cameron, J., Mito, R., Berkovic, S., & Jackson, G. D. (2025) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.70010 · Cited by 4
Self-citationAlmgren, H., Mahoney, C. J., Huynh, W., D'Souza, A., Berte, S., Lv, J.-L., Wang, C.-Y., Kiernan, M., Calamante, F., & Tu, S. (2025) · Journal of Neurology · doi:10.1007/s00415-025-12920-9 · Cited by 4
“This framework overcomes the oversimplification exhibited by the DTI model and yields metrics that are more meaningfully interpretable in terms of changes in fibre density (FD), fibre-bundle cross-section (FC), and a combination of fibre density & cross-section (FDC) [6].”
Xu, J., Cheng, Q., Zhang, Y., Luo, Y., Zhong, L., Liu, H., Zhang, H., Yang, Z.-K., Zhang, J.-N., Ou, Z.-L., et al. (2025) · Brain Communications · doi:10.1093/braincomms/fcaf026 · Cited by 4
“22 Therefore, FDC could be used to estimate the total number of fibres in a fibre bundle.”
Bianco, K. M., Fuelscher, I., Lum, J., Singh, M., Barhoun, P., Silk, T., Caeyenberghs, K., Williams, J., Enticott, P. G., Mukherjee, M., et al. (2024) · Brain and Cognition · doi:10.1016/j.bandc.2024.106204 · Cited by 4
“FD is thought to reflect axon count and/or density within a voxel, which seems to be related to the speed of information transfer within a tract (Raffelt et al., 2017).”
BackgroundMethodResultInfluentialGenç, B., Aslan, K., Atay, M. H., & Akan, H. (2024) · Neuroradiology · doi:10.1007/s00234-024-03414-y · Cited by 4
“For the analysis of fibre density and cross-section in diffusion-weighted images, the standard multi-tissue constrained spherical deconvolution (CSD) using fixel-based analysis pipeline within Mrtrix 3.0.2 was utilized [19].”
MethodInfluentialHarmonizing multisite neonatal diffusion-weighted brain MRI data for developmental neuroscience
Bonthrone, A., Blesa-Cábez, M., Edwards, A. D., Hajnal, J., Counsell, S., & Boardman, J. P. (2024) · medRxiv · doi:10.1016/j.dcn.2024.101488 · Cited by 4
A practical evaluation of measures derived from compressed sensing diffusion spectrum imaging
Radhakrishnan, H., Zhao, C., Sydnor, V. J., Baller, E. B., Cook, P. A., Fair, D. A., Giesbrecht, B., Larsen, B., Murtha, K. A., Roalf, D. R., et al. (2024) · Human Brain Mapping · doi:10.1002/hbm.26580 · Cited by 5
“For example, high b -value shells can be more useful for tractography in the presence of crossing fibers (Raffelt et al., 2017; Schilling et al., 2017) while low b-value shells are required for estimating some free water parameters (Assaf & Basser, 2005; Tuch et al., 2002; Yoshiura et al., 2001).”
BackgroundEvaluation of tractography-based myelin-weighted connectivity across the lifespan
Bosticardo, S., Schiavi, S., Schaedelin, S. A., Battocchio, M., Baraković, M., Lu, P., Weigel, M., Melie‐García, L., Granziera, C., & Daducci, A. (2024) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1228952 · Cited by 6
“…microstructure estimates along distinct directions inside each voxel, such as quantitative anisotropy (Yeh et al., 2010) and fixel-based analyses (Raffelt et al., 2017), but these approaches still cannot decouple different microstructural properties of distinct fiber bundles sharing the same…”
BackgroundRosemann, S., & Rauschecker, J. P. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1293133 · Cited by 4
Bergamino, M., Aslam, S., Knittel, J. J., Alhilali, L., & Stokes, A. (2023) · Journal of Integrative Neuroscience · doi:10.31083/j.jin2205114 · Cited by 4
Yang, J., Zhang, X., Gao, X., Wu, H., Li, X., Yang, L., & Zhang, N. (2023) · Neurosurgery · doi:10.1227/neu.0000000000002356 · Cited by 6
Rowe, E. G., Zhang, Y., & Garrido, M. (2023) · bioRxiv · doi:10.1002/hbm.26467 · Cited by 4
Mackes, N. K., Mehta, M. A., Beyh, A., Nkrumah, R. O., Golm, D., Sarkar, S., Fairchild, G. F., Dell’Acqua, F., Sonuga-Barke, E. J. S., & on behalf of the ERA Young Adult Follow-Up Team (2022) · eNeuro · doi:10.1523/eneuro.0188-22.2022 · Cited by 9
“The fact that tractography and D-TBM approaches both found the same pattern of morphologic changes is consistent with the hypothesis that deprivation negatively impacts the number of axons and fiber bundle cross-sectional size in the affected tracts (Raffelt et al., 2017).”
ResultGagnon, A., Descoteaux, M., Bocti, C., & Takser, L. (2022) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2022.111568 · Cited by 5
Liang, X., Elsaid, N., Jiang, L., Roys, S., Puché, A. C., Gullapalli, R. P., Stone, M., Prince, J. L., & Zhuo, J. (2022) · Journal of Speech Language and Hearing Research · doi:10.1044/2022_jslhr-22-00040 · Cited by 4
Wang, C.-C., Ellingson, B., Salamon, N., & Holly, L. (2022) · Neurosurgery · doi:10.1227/neu.0000000000001839 · Cited by 4
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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