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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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Cites
Cortical Surface-Based Analysis
Dale, A. M., Fischl, B., & Sereno, M. I. (1999) · NeuroImage · doi:10.1006/nimg.1998.0395 · Cited by 10,910 · cited 1×
“For the FC and FDC analysis, we included intracranial volume (as computed using FreeSurfer from T1-weighted images (Dale et al., 1999)) as a nuisance covariate.”
MethodVoxel-Based Morphometry—The Methods
Ashburner, J., & Friston, K. J. (2000) · NeuroImage · doi:10.1006/nimg.2000.0582 · Cited by 8,676
Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data
Smith, S. M., Jenkinson, M., Johansen‐Berg, H., Rueckert, D., Nichols, T. E., Mackay, C. E., Watkins, K. E., Ciccarelli, O., Cader, M. Z., Matthews, P. M., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.02.024 · Cited by 6,598 · cited 2×
“Furthermore, as in TBSS (Smith et al., 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.”
MethodBasser, P. J., & Pierpaoli, C. (1996) · Journal of Magnetic Resonance, Series B · doi:10.1006/jmrb.1996.0086 · Cited by 4,306 · cited 2×
“By far the most popular approach to VBA of diffusion MRI is the analysis of diffusion tensor-derived fractional anisotropy (FA) (Basser and Pierpaoli, 1996), with voxel- or clusterlevel statistical inference using packages such as SPM (http://www. fil.ion.ucl.ac.uk/spm/) or FSL…”
MethodPermutation inference for the general linear model
Winkler, A. M., Ridgway, G. R., Webster, M. A., Smith, S. M., & Nichols, T. E. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.01.060 · Cited by 3,563 · cited 1×
“Family-wise error corrected p-values were assigned to each fixel using non-parametric permutation testing (Holmes et al., 1996; Winkler et al., 2014) with 5000 permutations.”
MethodSelf-citationProbabilistic diffusion tractography with multiple fibre orientations: What can we gain?
Behrens, T. E. J., Berg, H. J., Jbabdi, S., Rushworth, M. F. S., & Woolrich, M. W. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.09.018 · Cited by 3,471
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 · cited 6×
“In the context of voxel-averaged DWI measures (e.g. Alexander et al., 2010; Zhang et al., 2012), the ‘density’ of a voxel will also be influenced by partial volume with cerebral spinal fluid.”
BackgroundMethodInfluentialTraining induces changes in white-matter architecture
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×
“, 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.”
BackgroundJeurissen, B., Tournier, J.-D., Dhollander, T., Connelly, A., & Sijbers, J. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.07.061 · Cited by 1,484 · cited 1×
“(Jeurissen et al., 2014)) instead of tissue segmentations from T1-weighted images.”
BackgroundSelf-citationDiffusion tensor imaging of white matter tract evolution over the lifespan
Lebel, C., Gee, M., Camicioli, R., Wieler, M., Martin, W., & Beaulieu, C. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.11.094 · Cited by 1,100 · cited 1×
“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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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.
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Items 101–200 of 604
Petersen, M., Nägele, F. L., Mayer, C., Schell, M., Petersen, E. L., Kühn, S., Gallinat, J., Fiehler, J., Pasternak, O., Matschke, J., et al. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2217232120 · Cited by 83
“FC) was calculated to ensure a zero centered normal distribution.(29) FDC was calculated as the product of FC and FD.”
Li, X., Zatorre, R. J., & Du, Y. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab063 · Cited by 28
“2011) and analysis strategies including fiber orientation distributions function and fixel-based analysis (Raffelt et al. 2017) would solve the crossing-fiber issue, improve the tractography quality, and deepen our understanding of musicians’ advantage in processing speech.”
BackgroundManual dexterity in late childhood is associated with maturation of the corticospinal tract
Fuelscher, I., Hyde, C., Efron, D., & Silk, T. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117583 · Cited by 28
Direct Structural Connections between Auditory and Visual Motion-Selective Regions in Humans
Gurtubay-Antolin, A., Battal, C., Maffei, C., Rezk, M. S. M., Mattioni, S., Jovicich, J., & Collignon, O. (2020) · Journal of Neuroscience · doi:10.1101/2020.06.11.145490 · Cited by 28
“FC reflects changes in a fiber bundle's intra-axonal volume that are manifested as a difference in the number of voxels/spatial extent that the fiber bundle occupies (cross-sectional area) (90).”
BackgroundGriffa, A., Ville, D. V. D., Herrmann, F. R., & Allali, G. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.02.023 · Cited by 29
“microstructural properties of multiple nervous bundles passing through the same white matter voxels and pinpoint tract-specific alterations (Girard et al., 2017; O’Donnell et al., 2009; Raffelt et al., 2017).”
BackgroundPecheva, D., Tournier, J.-D., Pietsch, M., Christiaens, D., Batalle, D., Alexander, D., Hajnal, J., Edwards, A., Zhang, H., & Counsell, S. (2019) · NeuroImage: Clinical · doi:10.1016/j.nicl.2019.101820 · Cited by 28
“The determinant of the Jacobian describes the local expansion or contraction with respect to the template.”
BackgroundMethodInfluentialSelf-citationResolution and b value dependent structural connectome in ex vivo mouse brain
Crater, S., Maharjan, S., Qi, Y. P., Zhao, Q., Cofer, G. P., Cook, J. C., Johnson, G. A., & Wang, N. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119199 · Cited by 30
“Recently, a quantitative comparison of the FODs has been proposed to provide more anatomically specific information about the microstructural properties of white matter populations, which is guaranteed in future studies (Raffelt et al., 2017; Tournier et al., 2019; Wu et al., 2020).”
BackgroundPrediction of Cognitive Recovery After Stroke
Aben, H. P., de Munter, L., Reijmer, Y., Spikman, J., Visser-Meily, J. A., Biessels, G., & de Kort, P. D. (2021) · Stroke · doi:10.1161/strokeaha.120.032033 · Cited by 27
Chen, R., Sun, C., Liu, T.-T., Liao, Y., Wang, J., Sun, Y., Zhang, Y., Wang, G.-B., & Wu, D. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119700 · Cited by 26
Strik, M., Lizama, L. E. C., Shanahan, C. J., van der Walt, A., Boonstra, F. M. C., Glarin, R. K., Kilpatrick, T. J., Geurts, J. J. G., Cleary, J. O., Schoonheim, M. M., et al. (2021) · Brain Communications · doi:10.1093/braincomms/fcab032 · Cited by 26
Fibre-specific laterality of white matter in left and right language dominant people
Verhelst, H., Dhollander, T., Gerrits, R., & Vingerhoets, G. (2020) · bioRxiv · doi:10.1101/2020.08.04.236000 · Cited by 26
Sleurs, C., Lemiere, J., Christiaens, D., Billiet, T., Peeters, R., Sunaert, S., Uyttebroeck, A., & Deprez, S. (2018) · Human Brain Mapping · doi:10.1002/hbm.24082 · Cited by 26
Fixel-based analysis reveals tau-related white matter changes in early stages of Alzheimer's disease
Ahmadi, K., Pereira, J. B., Westen, D. V., Pasternak, O., Zhang, F., Nilsson, M., Stomrud, E., Spotorno, N., & Hansson, O. (2024) · The Journal of Neuroscience · doi:10.1523/jneurosci.0538-23.2024 · Cited by 25
Rocca, M. A., Margoni, M., Battaglini, M., Eshaghi, A., Iliff, J. J., Pagani, E., Preziosa, P., Storelli, L., Taoka, T., Valsasina, P., et al. (2023) · Radiology · doi:10.1148/radiol.221512 · Cited by 30
Fixel based analysis of white matter alterations in early stage cerebral small vessel disease
Petersen, M., Frey, B., Mayer, C., Kühn, S., Gallinat, J., Hanning, U., Fiehler, J., Borof, K., Jagodzinski, A., Gerloff, C., et al. (2021) · Scientific Reports · doi:10.1038/s41598-022-05665-2 · Cited by 24
Koops, E. A., Haykal, S., & van Dijk, P. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.2996-20.2021 · Cited by 26
“After preprocessing, fixel-based analyses were performed as outlined in Raffelt et al. (2017); with the aid of MRtrix3 (Tournier et al., 2019).”
BackgroundMethodInfluentialEntrack: Probabilistic Spherical Regression with Entropy Regularization for Fiber Tractography
Wegmayr, V., & Buhmann, J. M. (2020) · International Journal of Computer Vision · doi:10.1007/s11263-020-01384-1 · Cited by 23
“Essentially, we have decomposed the tractogram T into the directions of its individual fiber bundles at each voxel, which is also known as fixel representation (Raffelt et al. 2017), referring to “a specific fiber bundle within a specific voxel” .”
MethodPannek, K., George, J., Boyd, R., Colditz, P., Rose, S., & Fripp, J. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117163 · Cited by 24
Mizuguchi, N., Maudrich, T., Kenville, R., Carius, D., Maudrich, D., Villringer, A., & Ragert, P. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.04.062 · Cited by 24
Long-term cognitive training enhances fluid cognition and brain connectivity in individuals with MCI
Gozdas, E., Avelar‐Pereira, B., Fingerhut, H., Dacorro, L., Jo, B., Williams, L. M., O'Hara, R. M., & Hosseini, S. M. H. (2024) · Translational Psychiatry · doi:10.1038/s41398-024-03153-x · Cited by 24
Roy, M., Edde, M., Fortier, M., Croteau, É., Castellano, C., St‐Pierre, V., Vandenberghe, C., Rheault, F., Dadar, M., Duchesne, S., et al. (2022) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2022.04.005 · Cited by 25
Fekonja, L., Wang, Z., Aydogan, D., Roine, T., Engelhardt, M., Dreyer, F., Vajkoczy, P., & Picht, T. (2020) · Frontiers in Oncology · doi:10.3389/fonc.2020.622358 · Cited by 23
Storelli, L., Pagani, E., Preziosa, P., Filippi, M., & Rocca, M. A. (2020) · Multiple Sclerosis Journal · doi:10.1177/1352458520938999 · Cited by 22
Denier, N., Walther, S., Schneider, C., Federspiel, A., Wiest, R., & Bracht, T. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.05.008 · Cited by 23
Hellewell, S., Nguyen, V., Jayasena, R., Welton, T., & Grieve, S. (2020) · NeuroImage: Clinical · doi:10.1016/j.nicl.2020.102253 · Cited by 23
Linking spherical mean diffusion weighted signal with intra-axonal volume fraction
Li, H., Chow, H.-M., Chugani, D., & Chugani, H. (2018) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2018.11.006 · Cited by 23
Robinson, E. A., Gleeson, J., Arun, A. H., Clemente, A., Gaillard, A., Rossetti, M. G., Brambilla, P., Bellani, M., Crisanti, C., Curran, H., et al. (2023) · Frontiers in Neuroimaging · doi:10.3389/fnimg.2023.1129587 · Cited by 22
Early white matter connectivity and plasticity in post stroke aphasia recovery
Schevenels, K., Gerrits, R., Lemmens, R., Smedt, B. D., Zink, I., & Vandermosten, M. (2022) · NeuroImage: Clinical · doi:10.1016/j.nicl.2022.103271 · Cited by 22
Momi, D., Ozdemir, R., Tadayon, E., Boucher, P., Domenico, A. D., Fasolo, M., Shafi, M., Pascual-Leone, Á., & Santarnecchi, E. (2021) · Journal of Physiology · doi:10.1113/jp282393 · Cited by 22
“Following these processing steps, we calculated the three standard fixel-based metrics for FBA (Raffelt et al. 2017):”
MethodYeh, C., Tseng, R.-Y., Ni, H., Cocchi, L., Chang, J.-C., Hsu, M.-Y., Tu, E., Wu, Y., Chou, T., Gau, S. S., et al. (2022) · Molecular Autism · doi:10.1186/s13229-022-00499-1 · Cited by 22
Xiao, Y.-M., Peters, T. M., & Khan, A. R. (2021) · Human Brain Mapping · doi:10.1002/hbm.25558 · Cited by 22
“An increase in FC may be interpreted as widening of extra-axon space or improved organization of axons (Raffelt et al., 2017) while FDC measures the joint impacts from FC and FD.”
BackgroundMethodInfluentialMRI detection of brain abnormality in sickle cell disease
Stotesbury, H., Kawadler, J., Saunders, D., & Kirkham, F. (2021) · Expert Review of Hematology · doi:10.1080/17474086.2021.1893687 · Cited by 22
“techniques [98], fixel-based analysis [99], and diffusion kurtosis imaging [100] have yet to be applied in this population.”
MethodWang, C.-C., Laiwalla, A. N., Salamon, N., Ellingson, B., & Holly, L. (2020) · Brain Research · doi:10.1016/j.brainres.2020.147129 · Cited by 22
“Generally, a decrease in FD indicates a decrease of the total intra-axonal volume of white matter axons in any particular direction, thus providing information of degeneration within specific white matter tracts (Raffelt et al., 2015; Raffelt et al., 2017; Tournier et al., 2007).”
BackgroundSudre, G. P., Norman, L. J., Bouyssi-Kobar, M., Price, J., Shastri, G. G., & Shaw, P. (2022) · Biological Psychiatry · doi:10.1016/j.biopsych.2022.09.021 · Cited by 21
Lv, J., Zeng, R., Ho, M. P., D’Souza, A., & Calamante, F. (2022) · Magnetic Resonance in Medicine · doi:10.1002/mrm.29496 · Cited by 19
“Recently, the “Fixel”( representing fibre population within a voxel) based analysis(Dhollander et al., 2021; Raffelt et al., 2017a) has been developed to quantitatively compare FODs in each voxel, and their derived features, such as apparent fibre density(Raffelt et al., 2017a) and fibre…”
BackgroundMethodInfluentialFiber-specific white matter alterations in early-stage tremor-dominant Parkinson’s disease
Andica, C., Kamagata, K., Saito, Y., Uchida, W., Fujita, S., Hagiwara, A., Akashi, T., Wada, A., Ogawa, T., Hatano, T., et al. (2021) · npj Parkinson's Disease · doi:10.1038/s41531-021-00197-4 · Cited by 21
Translational neuroimaging in mild traumatic brain injury
Wiegand, T., Sollmann, N., Bonke, E., Umeasalugo, K. E., Sobolewski, K. R., Plesnila, N., Shenton, M., Lin, A., & Koerte, I. (2021) · Journal of Neuroscience Research · doi:10.1002/jnr.24840 · Cited by 21
“For example, one study found lower FA in the ipsilateral infralimbic area, and lower MD in the ipsilateral dentate gyrus 30 days after mTBI due to CHI.”
MethodInfluentialBao, L., Xiong, C., Wei, W., Chen, Z., van Zijl, P., & Li, X. (2020) · Medical Image Anal. · doi:10.1016/j.media.2020.101827 · Cited by 21
“Before these attempts, diffusion tensor imaging (DTI) was the only in vivo imaging technique for noninvasive characterization of WM fiber architecture (Mori et al., 1999; Basser et al., 2000; Cote et al., 2013; Raffelt et al., 2017).”
BackgroundWallace, E. J., Mathias, J., Ward, L., Fripp, J., Rose, S., & Pannek, K. (2020) · Human Brain Mapping · doi:10.1002/hbm.24939 · Cited by 21
“…anterior commissure) may not be accurately assessed using FBA; although micro-structural changes (FD) can be detected in small structures, FC can be insensitive and any macro-structural changes may instead present as micro-structural changes (FD) (Raffelt et al., 2017; Vaughan et al., 2017).”
BackgroundMethodResultInfluentialMu, J., Chen, T., Li, P., Ding, D., Ma, X., Zhang, M., & Liu, J.-X. (2018) · Human Brain Mapping · doi:10.1002/hbm.24321 · Cited by 21
“Fixelbased analysis (FBA) is a method based on the analysis of DTI data, which can compare measures related to the total intra-axonal volume of WM axons, providing a method that can be used to detect degeneration within WM tracts (Raffelt et al., 2017).”
MethodInfluentialWhite matter fiber-specific degeneration in older adults with metabolic syndrome
Andica, C., Kamagata, K., Uchida, W., Takabayashi, K., Shimoji, K., Kaga, H., Someya, Y., Tamura, Y., Kawamori, R., Watada, H., et al. (2022) · Molecular Metabolism · doi:10.1016/j.molmet.2022.101527 · Cited by 20
Connectivity-Based Topographical Changes of the Corpus Callosum During Aging
Liu, Y., Hsu, C. H., Huang, C., Zhang, Y., Zhao, J., Tsai, S., Chen, L., Lin, C., & Lo, C. Z. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.753236 · Cited by 20
Structural Connectivity Remote From Lesions Correlates With Somatosensory Outcome Poststroke
Koh, C.-L., Yeh, C.-H., Liang, X., Vidyasagar, R., Seitz, R., Nilsson, M., Connelly, A., & Carey, L. (2021) · Stroke · doi:10.1161/strokeaha.120.031520 · Cited by 20
“Major structures include (1) pontocerebellar fibers; (2) corpus callosum—sensorimotor portion; (3) corticospinal/spinothalamic tracts— inferior portion; (4) fornix; (5) corpus callosum—anterior portion; (6) thalamus; and (7) superior longitudinal fasciculus.”
Self-citationThalamic white matter macrostructure and subnuclei volumes in Parkinson’s disease depression
Bhome, R., Zarkali, A., Thomas, G. E. C., Iglesias, J., Cole, J., & Weil, R. (2021) · medRxiv · doi:10.1038/s41531-021-00270-y · Cited by 20
“Here, we focused on fibre cross section (FC) which is a relative metric of differences in fibre bundle cross section compared to a template based on the study population and is thought to be a measure of white matter macrostructure.(38) We used this metric as our previous work in PD has shown FC to be a more sensitive…”
MethodNguyen, T., Cheng, J.-S., Chen, Y.-L., Lin, Y.-C., Tsai, C.-C., Lu, C.-S., Weng, Y., Wu, Y.-M., Hoang, N., & Wang, J.-J. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.625874 · Cited by 20
Haykal, S., Jansonius, N., & Cornelissen, F. (2020) · European Journal of Radiology · doi:10.1016/j.ejrad.2020.109356 · Cited by 20
Mohammadian, M., Roine, T., Hirvonen, J., Kurki, T., Posti, J., Katila, A., Takala, R., Tallus, J., Maanpää, H.-R., Frantzén, J., et al. (2020) · Journal of Neurotrauma · doi:10.1089/neu.2020.7081 · Cited by 20
Sánchez, S. M., Duarte-Abritta, B., Abulafia, C., Pino, G. D., Bocaccio, H., Castro, M. N., Sevlever, G. E., Fonzo, G. A., Nemeroff, C. B., Gustafson, D., et al. (2020) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2019.12.019 · Cited by 27
Functional connectivity in autism spectrum disorder evaluated using rs-fMRI and DKI
Nagai, Y., Kirino, E., Tanaka, S., Usui, C., Inami, R., Inoue, R., Hattori, A., Uchida, W., Kamagata, K., & Aoki, S. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad451 · Cited by 19
“As assessed by DKI and fixel-based analysis (FBA) (Raffelt et al. 2017), reduced axonal density, marked by a decreased axonal water fraction, has also been suggested within the CC and long-range association tracts in adult ASD (Lazar et al. 2014; Dimond et al. 2019).”
de Almeida, J. S., Baud, O., Fau, S., Munoz, F. B., Courvoisier, S., Lordier, L., Lazeyras, F., & Hüppi, P. S. (2023) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2023.101254 · Cited by 24
Efficacy and Safety of Leriglitazone in Patients With Friedreich Ataxia
Pandolfo, M., Reetz, K., Darling, A., Garrido, F. J. R. D. R., Henry, P., Joers, J. M., Lenglet, C., Adanyeguh, I. M., Deelchand, D. K., Mochel, F., et al. (2022) · Neurology Genetics · doi:10.1212/nxg.0000000000200034 · Cited by 42
Emerging Trends in Neuroimaging of Epilepsy
Bernasconi, N., & Wang, I. (2021) · Epilepsy Currents · doi:10.1177/1535759721991161 · Cited by 19
“Similar findings were obtained with fixel-based analysis, a reconstruction technique which combines measurements of fiber cross-sectional area and density, thereby providing a sensitive marker of intra-axonal volume.(10,11) Neurite orientation dispersion and density imaging, commonly referred to as NODDI, is Epilepsy…”
MethodChahal, R., Delevich, K. M., Kirshenbaum, J. S., Borchers, L. R., Ho, T. C., & Gotlib, I. H. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117598 · Cited by 21
Reduced apparent fiber density in the white matter of premature-born adults
Menegaux, A., Hedderich, D. M., Bäuml, J., Manoliu, A., Daamen, M., Berg, R., Preibisch, C., Zimmer, C., Boecker, H., Bartmann, P., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-73717-6 · Cited by 20
Kirkovski, M., Fuelscher, I. T., Hyde, C. E., Donaldson, P. H., Ford, T. C., Rossell, S. L., Fitzgerald, P. B., & Enticott, P. G. (2020) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2020.00040 · Cited by 24
Dennis, E. L., Caeyenberghs, K., Asarnow, R. F., Babikian, T., Bartnik‐Olson, B., Bigler, E. D., Figaji, A., Giza, C. C., Goodrich‐Hunsaker, N. J., Hodges, C. B., et al. (2020) · Brain Imaging and Behavior · doi:10.1007/s11682-020-00363-x · Cited by 26
Longitudinal Trajectories of White Matter Development in Attention-Deficit/Hyperactivity Disorder
Fuelscher, I. T., Hyde, C. E., Thomson, P., Vijayakumar, N., Sciberras, E., Efron, D., Anderson, V. A., Hazell, P., & Silk, T. J. (2023) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2023.03.008 · Cited by 15
Radhakrishnan, V., Galléa, C., Valabrègue, R., Krishnan, S., Kesavadas, C., Thomas, B., James, P., Menon, R. N., & Kishore, A. (2023) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2023.1019239 · Cited by 18
“FD and FC provide a macrostructural and microstructural measure of change in the fiber tracts, respectively, and their combined measure of FDC obtained as a product of FD and FC provides an overall measure of the ability of the fiber bundle to relay information (Raffelt et al., 2017).”
BackgroundAngular Super-Resolution in Diffusion MRI with a 3D Recurrent Convolutional Autoencoder
Lyon, M., Armitage, P., & Álvarez, M. A. (2022) · International Conference on Medical Imaging with Deep Learning · doi:10.48550/arxiv.2203.15598 · Cited by 18
“Introduction Advances in diffusion MRI (dMRI) analysis techniques continue to push the boundaries of what is attainable through the non-invasive imaging modality (Zhang et al., 2012; Raffelt et al., 2017; Drake-Pérez et al., 2018).”
BackgroundSiffredi, V., Liverani, M. C., Ville, D. V. D., Freitas, L. G. A., Tolsa, C. B., Hüppi, P. S., & Leuchter, R. H. (2023) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2023.101211 · Cited by 19
“More advanced DWI tractography methods, such as Q-ball (Tuch et al., 2002) or fixel-based analysis (Raffelt et al., 2017), have been proposed to resolve complex fibre architecture in a given voxel and might bring further insight into callosal development in VPT children and adolescents.”
MethodKristensen, T. D., Glenthøj, L., Ambrosen, K., Syeda, W., Ragahava, J. M., Krakauer, K., Wenneberg, C., Fagerlund, B., Pantelis, C., Glenthøj, B., et al. (2021) · Acta Psychiatrica Scandinavica · doi:10.1111/acps.13355 · Cited by 18
Gagnon, H. C., Simmonite, M., Cassady, K. E., Chamberlain, J. D., Freiburger, E., Lalwani, P., Kelley, S., Foerster, B. R., Park, D. C., Petrou, M., et al. (2019) · BMC Neurology · doi:10.1186/s12883-019-1294-6 · Cited by 23
Newman, B. T., Jacokes, Z., Venkadesh, S., Webb, S. J., Kleinhans, N. M., McPartland, J. C., Druzgal, T. J., Pelphrey, K. A., & Horn, J. D. V. (2024) · PLoS ONE · doi:10.1371/journal.pone.0301964 · Cited by 21
“…FDC as a direct volume fraction estimate after removing isotropic signal from CSF and intracellular structures is intended to provide fiber specific estimates even in cases where individual axon diameters are too small to measure using apparent inter-axonal perpendicular diffusion [30, 33].”
BackgroundMethodInfluentialExploring individual fixel-based white matter abnormalities in epilepsy
Mito, R., Pedersen, M., Pardoe, H., Parker, D., Smith, R., Cameron, J., Scheffer, I., Berkovic, S., Vaughan, D., & Jackson, G. D. (2023) · Brain Communications · doi:10.1093/braincomms/fcad352 · Cited by 17
“We present an advanced diffusion MRI approach quantifying WM abnormalities in individual epilepsy patients, by adapting the FBA framework to individualized assessment.”
BackgroundMethodInfluentialSelf-citationHan, A., Dhollander, T., Sun, Y., Chad, J. A., & Chen, J. J. (2023) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2023.06.007 · Cited by 17
Öz, G., Cocozza, S., Henry, P.-G., Lenglet, C., Deistung, A., Faber, J., Schwarz, A., Timmann, D., van Dijk, K. V., Harding, I., et al. (2023) · Cerebellum · doi:10.1007/s12311-023-01572-y · Cited by 17
“Other more advanced diffusion metrics such as fiber density and cross-section from fixel-based analysis [71] can be used to better characterize individual fiber bundles, even in regions with complex (i.e., crossing) white matter configurations.”
BackgroundThe effects of puberty and sex on adolescent white matter development: A systematic review
Piekarski, D. J., Colich, N. L., & Ho, T. C. (2023) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2023.101214 · Cited by 25
“…fiber density and cross-section (FDC), a combined metric of fiber density (FD) and fiber cross-section (FC) that is a proxy for axonal diameter (Raffelt et al., 2017; see also Table 1), young adolescents (ages 9–14 years) in which boys and girls were matched on pubertal stage (n=159), Chahal…”
BackgroundCerebellum Dysfunction in Patients With PRRT2-Related Paroxysmal Dyskinesia
Ekmen, A., Méneret, A., Valabrègue, R., Béranger, B., Worbe, Y., Lamy, J., Mehdi, S., Hervé, A., Adanyeguh, I., Temiz, G., et al. (2022) · Neurology · doi:10.1212/wnl.0000000000200060 · Cited by 17
“In our patients, the apparent FD was greater in the superior cerebellar peduncles, likely reflecting a larger number of axons in that fiber population or the presence of bigger axons.(26) In addition, FC was greater in the motor cerebellum (lobule VI) and the mPFC.”
BackgroundMethodInfluentialYu, Y.-M., Zheng, W., Tan, X., Li, X., Zhang, X.-T., Gao, J., Pan, G., Wu, D., & Luo, B. (2021) · Journal of Neuroscience Research · doi:10.1002/jnr.24921 · Cited by 17
“They proposed a fixel- based analysis (FBA), by using which we could reveal withinvoxel microstructural differences in any particular direction and detect alterations within specific WM fibers (Raffelt et al., 2017).”
BackgroundMethodBilateral Structural Network Abnormalities in Epilepsy Associated With Bottom-of-Sulcus Dysplasia
Mito, R., Vaughan, D., Semmelroch, M., Connelly, A., & Jackson, G. (2021) · Neurology · doi:10.1212/wnl.0000000000013006 · Cited by 17
Self-citationLiang, X., Yeh, C.-H., D., J. F. D., Poudel, G., Swinnen, S., & Caeyenberghs, K. (2021) · NeuroImage: Clinical · doi:10.1016/j.nicl.2021.102621 · Cited by 17
“section (FDC), between TBI patients and healthy controls using the fixel-based analysis (FBA) framework (Raffelt et al., 2017), where a fixel refers to a specific fibre population within a”
BackgroundMethodInfluentialBlommaert, J., Radwan, A., Sleurs, C., Maggen, C., van Gerwen, M., Wolters, V. E. R. A., Christiaens, D., Peeters, R. R., Dupont, P. J., Sunaert, S. G., et al. (2020) · EClinicalMedicine · doi:10.1016/j.eclinm.2020.100598 · Cited by 18
“Higher FDC in the chemotherapy subgroup and higher FCS in the whole study group were observed in the anterior thalamic radiations.”
BackgroundMethodInfluentialHyde, C., Fuelscher, I., Sciberras, E., Efron, D., Anderson, V., & Silk, T. (2020) · Progress in Neuro-psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2020.110125 · Cited by 17
Distinct fiber-specific white matter reductions pattern in early- and late-onset Alzheimer’s disease
Luo, X., Wang, S., Jiaerken, Y., Li, K., Zeng, Q., Hong, H., Guan⁴, X., Guo, T., Wang, C., Zhang, R., et al. (2021) · Aging · doi:10.18632/aging.202702 · Cited by 19
“Decreased FD represents decreased volume fraction of restricted water within a voxel; while decreased FC reflects a shrink of fiber bundle's cross-sectional area [15].”
InfluentialRegional neurodegeneration correlates with sleep–wake dysfunction after stroke
Gottlieb, E., Egorova, N., Khlif, M. S., Khan, W., Werden, E., Pase, M. P., Howard, M. E., & Brodtmann, A. G. (2020) · SLEEP · doi:10.1093/sleep/zsaa054 · Cited by 15
Mapping connectomes with diffusion MRI: Deterministic or probabilistic tractography?
Smith, R. E., Calamante, F., & Connelly, A. (2019) · Magnetic Resonance in Medicine · doi:10.1002/mrm.27916 · Cited by 20
Self-citationGuberman, G. I., Houde, J.-C., Ptito, A., Gagnon, I., & Descoteaux, M. (2019) · Brain Structure and Function · doi:10.1007/s00429-019-02002-8 · Cited by 17
White matter degeneration profile in the cognitive cortico‐subcortical tracts in Parkinson's disease
Hanganu, A., Houde, J., Fonov, V., Degroot, C., Mejia‐Constain, B., Lafontaine, A., Soland, V., Chouinard, S., Collins, D. L., Descoteaux, M., et al. (2018) · Movement Disorders · doi:10.1002/mds.27364 · Cited by 15
Advances in fetal and neonatal neuroimaging and everyday exposures
Lautarescu, A., Bonthrone, A., Bos, B., Barratt, B., & Counsell, S. (2024) · Pediatric Research · doi:10.1038/s41390-024-03294-1 · Cited by 16
Bonthrone, A. F., Green, D., Morgan, A. T., Mankad, K., Clark, C. A., & Liegeois, F. J. (2023) · Developmental Medicine & Child Neurology · doi:10.1111/dmcn.15745 · Cited by 18
“40 Fibre cross-section is a macrostructural measure related to fibre bundle diameter; 39 values were log-transformed to normalize the data as recommended by the MRtrix3 pipeline (log[fold change]).”
MethodDong, Q.-L., Li, J., Ju, Y.-M., Xiao, C.-M., Li, K.-N., Shi, B., Zheng, W., & Zhang, Y. (2023) · Brain Science · doi:10.3390/brainsci13071098 · Cited by 16
Spatio-Angular Convolutions for Super-resolution in Diffusion MRI
Lyon, M., Armitage, P., & Álvarez, M. A. (2023) · Neural Information Processing Systems · doi:10.48550/arxiv.2306.00854 · Cited by 16
“Whilst there is a myriad of downstream analyses for dMRI, this work focuses on two commonly used methods: FBA [25] and NODDI [36].”
MethodChahal, R., Ho, T., Miller, J. G., Borchers, L., & Gotlib, I. (2022) · JCPP Advances · doi:10.1002/jcv2.12061 · Cited by 16
Fixel-Based Analysis Effectively Identifies White Matter Tract Degeneration in Huntington’s Disease
Oh, S. L., Chen, C.-M., Wu, Y.-R., Valdes-Hernandez, M. D., Tsai, C.-C., Cheng, J.-S., Chen, Y.-L., Wu, Y.-M., Lin, Y.-C., & Wang, J.-J. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.711651 · Cited by 16
“Studies on preclinical mouse models have indicated that cortical neuronal death is not proportionally accompanied by white matter tract degeneration (Rattray et al., 2013), and early white matter changes are a main feature of neuronal and axonal connectivity impairment in fluorescenttagged animals…”
BackgroundMulti-Channel 4D Parametrized Atlas of Macro- and Microstructural Neonatal Brain Development
Uus, A., Grigorescu, I., Pietsch, M., Batalle, D., Christiaens, D., Hughes, E., Hutter, J., Cordero-Grande, L., Price, A., Tournier, J.-D., et al. (2021) · bioRxiv · doi:10.1101/2021.02.11.430835 · Cited by 16
Self-citationPalmer, J., Duffy, S., Meares, S., Pye, J. E., Calamante, F., Cespedes, M. I., Hickie, I., & Naismith, S. (2021) · Sleep · doi:10.1093/sleep/zsab007 · Cited by 16
Cheong, J., Cameron, K. L. I., Thompson, D. K., Anderson, P., Ranganathan, S., Clark, R., Mentiplay, B., Burnett, A. C., Lee, K. J., Doyle, L., et al. (2021) · BMJ Open · doi:10.1136/bmjopen-2020-044491 · Cited by 16
Bauer, T., Ernst, L., David, B., Becker, A., Wagner, J., Witt, J., Helmstaedter, C., Weber, B., Hattingen, E., Elger, C., et al. (2020) · NeuroImage: Clinical · doi:10.1016/j.nicl.2020.102289 · Cited by 16
Microangiopathy in temporal lobe epilepsy with diffusion MRI alterations and cognitive decline
Liu, J. Y. W., Binding, L. P., Puntambekar, I., Patodia, S., Lim, Y. M., Mryzyglod, A., Xiao, F., Pan, S., Mito, R., de Tisi, J., et al. (2024) · Acta Neuropathologica · doi:10.1007/s00401-024-02809-8 · Cited by 20
“DWI data were also analysed using the FBA framework [53].”
MethodZarkali, A., Hannaway, N., McColgan, P., Heslegrave, A., Veleva, E., Laban, R., Zetterberg, H., Lees, A. J., Fox, N. C., & Weil, R. S. (2024) · Brain Communications · doi:10.1093/braincomms/fcae130 · Cited by 18
“…and macrostructural changes at whole-brain and tract level using fixel-based analysis, a technique able to reliably model crossing fibres 34 ; and (iii) changes in functional and structural connectivity at whole-network level in people with PD who develop poor outcomes during follow-up,…”
InfluentialEdde, M., Théaud, G., Dumont, M., Théberge, A., Valcourt-Caron, A., Gilbert, G., Houde, J.-C., Maltais, L., Rheault, F., Spagnolo, F., et al. (2023) · Human Brain Mapping · doi:10.1002/hbm.26310 · Cited by 15
“Another study shows that a fixel-based analysis (D. A. Raffelt et al., 2017) reveals a specific degeneration of the SLF with preservation of the CST and the CC in Alzheimer’s disease whereas this degeneration results in an increase in FA with conventional DTI measures, i.e., the decrease in FA of…”
BackgroundDevelopment of white matter fiber covariance networks supports executive function in youth
Bagautdinova, J., Bourque, J., Sydnor, V. J., Cieslak, M., Alexander‐Bloch, A. F., Bertolero, M. A., Cook, P. A., Gur, R. E., Gur, R. C., Hu, F., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.113487 · Cited by 24
“To delineate these covariance networks, we applied the fixel-based analysis (FBA) pipeline (4) with single-shell three tissue constrained spherical deconvolution (31) to DWI data from 939 youth aged 8-22 years (see Figure S1 for sample selection).”
InfluentialGeorge, J., Pagnozzi, A., Bora, S., Boyd, R., Colditz, P., Rose, S., Ware, R., Pannek, K., Bursle, J., Fripp, J., et al. (2020) · BMJ Open · doi:10.1136/bmjopen-2019-036480 · Cited by 15
“43 Anatomically constrained tractography will be performed using MRtrix3, 44 and filtered using Spherical Deconvolution Informed Filtering of Tractograms.”
MethodGrazioplene, R. G., Tseng, W., Cimino, K., Kalvin, C. B., Ibrahim, K., Pelphrey, K. A., & Sukhodolsky, D. G. (2020) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2019.12.018 · Cited by 13
“While FA captures information about overall relative diffusion patterns in a voxel, studies in both phantom and human data show that fixelbased analysis can approximate both the density and macrostructural cross section of distinct fiber bundles traversing a voxel (29,30).”
BackgroundMethodDimond, D., Heo, S., Ip, A., Rohr, C. S., Tansey, R., Graff, K., Dhollander, T., Smith, R. E., Lebel, C., Dewey, D., et al. (2019) · bioRxiv · doi:10.1101/852764 · Cited by 15
“Techniques such as fixel-based analysis (FBA; Raffelt et al., 2017) can be used to overcome this issue by estimating structural metrics at the level of individually oriented fiber bundle”
InfluentialSelf-citationFinkelstein, A., Faiyaz, A., Weber, M. T., Qiu, X., Uddin, M. N., Zhong, J., & Schifitto, G. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.725059 · Cited by 15
D'Mello, A. M., Frosch, I. R., Meisler, S. L., Grotzinger, H., Perrachione, T. K., & Gabrieli, J. D. E. (2023) · The Journal of Neuroscience · doi:10.1523/jneurosci.0608-22.2023 · Cited by 14
“FODs were intensity-normalized (Raffelt et al., 2017).”
Two axes of white matter development
Luo, A. C., Meisler, S. L., Sydnor, V. J., Alexander‐Bloch, A. F., Bagautdinova, J., Barch, D. M., Bassett, D. S., Davatzikos, C. A., Franco, A. R., Goldsmith, J., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-68714-8 · Cited by 11
“FODsservedasthebasisofbiologicallyinterpretablestreamline tractography 88,89 .”
Fiber-specific structural properties relate to reading skills in children and adolescents
Meisler, S., & de Gabrieli, J. (2022) · bioRxiv · doi:10.1101/2022.07.21.501025 · Cited by 14
van der Weijden, C. W. J., van der Hoorn, A., Potze, J. H., Renken, R. J., Borra, R., Dierckx, R., Gutmann, I. W., Ouaalam, H., Karimi, D., Gholipour, A., et al. (2022) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x221107953 · Cited by 16
“The fixels were then reoriented, after which the fixels of a subject were assigned to template fixels, and finally the FC and FDC were calculated.(44) The FD, FC, and FDC fixel images were then converted to voxel images and transformed from template to subject space, in order to be able to compare all diffusion derive…”
Method
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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