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High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity
Abstract
Magnetic resonance (MR) diffusion tensor imaging (DTI) can resolve the white matter fiber orientation within a voxel provided that the fibers are strongly aligned. However, a given voxel may contain a distribution of fiber orientations due to, for example, intravoxel fiber crossing. The present study sought to test whether a geodesic, high b-value diffusion gradient sampling scheme could resolve multiple fiber orientations within a single voxel. In regions of fiber crossing the diffusion signal exhibited multiple local maxima/minima as a function of diffusion gradient orientation, indicating the presence of multiple intravoxel fiber orientations. The multimodality of the observed diffusion signal precluded the standard tensor reconstruction, so instead the diffusion signal was modeled as arising from a discrete mixture of Gaussian diffusion processes in slow exchange, and the underlying mixture of tensors was solved for using a gradient descent scheme. The multitensor reconstruction resolved multiple intravoxel fiber populations corresponding to known fiber anatomy. Ma
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“The DTI model cannot differentiate these components or even crossing fibers (Tuch et al., 2002; Jbabdi et al., 2010), which are estimated to occur in up to 90% of WM voxels at the typical dMRI resolution (Descoteaux et al., 2009; Jeurissen et al., 2013).”
From Diffusion MRI Indices and Their Relation to Cognitive Impairment in Brain Aging: The Updated Multi-protocol Approach in ADNI3 (2019) · cites this paper as Tuch et al., 2002
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Awate, S. P., & DiBella, E. (2013) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2013.6556399 · Cited by 19
Hosey, T. P., Harding, S. G., Carpenter, T. A., Ansorge, R. E., & Williams, G. B. (2007) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2007.07.002 · Cited by 19
“Multiple tensor fits to diffusion-weighted data have also been reported in the literature [11–13].”
BackgroundInferring Microstructural Information of White Matter from Diffusion MRI
Assaf, Y., & Cohen, Y. (2014) · Elsevier eBooks · doi:10.1016/b978-0-12-396460-1.00009-3 · Cited by 19
Multimodal Neuroimaging in Rett Syndrome With MECP2 Mutation
Kong, Y., Li, Q.-B., Zhao-hong, Y., Jiang, X., Zhang, G.-Q., Cheng, N., & Dang, N. (2022) · Frontiers in Neurology · doi:10.3389/fneur.2022.838206 · Cited by 21
Radial q‐space sampling for DSI
Baete, S. H., Yutzy, S. R., & Boada, F. E. (2015) · Magnetic Resonance in Medicine · doi:10.1002/mrm.25917 · Cited by 19
Li, J., Shi, Y., Tran, G., Dinov, I. D., Wang, D. J. J., & Toga, A. W. (2013) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2013.2274051 · Cited by 19
“Though in this paper the fast local-trust-region method is applied to DTI image registration, its principle is generally applicable to different diffusion models related to other acquisition schemes, for example, the multi-tensor model [38] related to the HARDI [3], and the nonparametric model related to the diffusion…”
MethodInfluentialBergmann, Ø., Kindlmann, G., Peled, S., & Westin, C. (2007) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2007.356972 · Cited by 19
“[1] was able, with some constraints, to solve for two diffusion tensors in an multitensor extension of the Stejskal-Tanner equations (presented in equation (2)) by applying a conjugate gradient algorithm to high-angular resolution acquisitions (HARDI).”
MethodInvestigation of superior longitudinal fasciculus fiber complexity in recent onset psychosis
Szeszko, P. R., Tan, E. T., Uluğ, A. M., Kingsley, P. B., Gallego, J. A., Rhindress, K., Malhotra, A. K., Robinson, D. G., & Marinelli, L. (2017) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2017.10.019 · Cited by 19
“Therefore, DSI relies on less stringent assumptions and does not depend on model based reconstruction (such as q-ball, spherical transforms, and spherical deconvolution) that is typically required with high angular resolution diffusion-weighted imaging (Tuch et al., 2002).”
MethodImaging the Developing Epileptic Brain
Grant, P. E. (2005) · Epilepsia · doi:10.1111/j.1528-1167.2005.00303.x · Cited by 19
“will occur in any one given measured direction (12,13).”
BackgroundAtypical White Matter Connectivity in Dyslexic Readers of a Fairly Transparent Orthography
Žarić, G., Timmers, I., Gerretsen, P., González, G. F., Tijms, J., van der Molen, M. W., Blomert, L., & Bonte, M. L. (2018) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.01147 · Cited by 18
Ma, Y., Bruce, I. P., Yeh, C., Petrella, J. R., Song, A. W., & Truong, T. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.119993 · Cited by 19
Liu, C., Murphy, N. E., & Li, W. (2013) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2013.00011 · Cited by 18
“…angular resolution by resolving these crossing fibers has been a major goal of diffusion based fiber tractography in the past decade (Frank, 2001, 2002; Alexander et al., 2002; Tuch et al., 2002; Lin et al., 2003; Liu et al., 2003a,b; Ozarslan and Mareci, 2003; Tuch, 2004; Jensen et al., 2005).”
BackgroundQuantitative MRI of the Spinal Cord
Cohen‐Adad, J., & Wheeler‐Kingshott, C. A. M. G. (2014) · Cited by 18
LONI MiND: Metadata in NIfTI for DWI
Patel, V. N., Dinov, I. D., Horn, J. D. V., Thompson, P. M., & Toga, A. W. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.02.069 · Cited by 18
Ye, W., Vemuri, B. C., & Entezari, A. (2012) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2012.6235711 · Cited by 18
“By letting the reconstruction kernel K(b, g|v j ) = ∫ϕ(p|v j )k(b, g|p)dp and considering the case of a constant b-value (which is quite common in HARDI acquisition), we have: (4) where K is represented in spline bases ψ k .”
BackgroundMethodCUDA-Accelerated Geodesic Ray-Tracing for Fiber Tracking
van Aart, E., Sepasian, N., Jalba, A. C., & Vilanova, A. (2011) · International Journal of Biomedical Imaging · doi:10.1155/2011/698908 · Cited by 18
“High Angular Resolution Diffision Imaging (HARDI) aims to overcome this limitation by measuring and modeling the diffusion in more directions [37].”
BackgroundResting State fMRI-guided Fiber Clustering: Methods and Applications
Ge, B., Guo, L., Zhang, T., Hu, X., Han, J., & Liu, T. (2012) · Neuroinformatics · doi:10.1007/s12021-012-9169-7 · Cited by 20
“In the future, advancements of neuroimaging techniques such as the High Angular Resolution Diffusion Imaging (HARDI) (Tuch et al. 2002) and ultra-high field MRI (Kerchner 2011), which has higher quality and can effectively deal with crossing white matter fibers, can further enhance the rsfMRI-guided fiber clustering p…”
MethodLove songs, bird brains and diffusion tensor imaging
Groof, G. D., & der Linden, A. V. (2010) · NMR in Biomedicine · doi:10.1002/nbm.1551 · Cited by 19
Differentiation among parkinsonisms using quantitative diffusion kurtosis imaging
Ito, K., Sasaki, M., Ohtsuka, C., Yokosawa, S., Harada, T., Uwano, I., Yamashita, F., Higuchi, S., & Terayama, Y. (2015) · Neuroreport · doi:10.1097/wnr.0000000000000341 · Cited by 18
Anisotropic phantom to calibrate high-q diffusion MRI methods
Komlosh, M. E., Benjamini, D., Barnett, A. S., Schram, V., Horkay, F., Avram, A., & Basser, P. J. (2016) · Journal of Magnetic Resonance · doi:10.1016/j.jmr.2016.11.017 · Cited by 18
“These include apparent diffusion coefficient (ADC) mapping [1,2], diffusion tensor imaging (DTI) [3,4], q-space MRI [5,6], diffusion spectrum imaging (DSI) [7,8], high angular resolution diffusion imaging (HARDI) [9], q-ball MRI [10,11], combined hindered and restricted model of water diffusion (CHARMED) MRI [12], AxC…”
Director Field Analysis (DFA): Exploring Local White Matter Geometric Structure in Diffusion MRI
Cheng, J., & Basser, P. J. (2017) · Medical Image Analysis · doi:10.1016/j.media.2017.10.003 · Cited by 18
“High Angular Resolution Diffu-sion Imaging (Tuch et al., 2002; Frank, 2002; Descoteaux et al., 2007; Tournier et al., 2007; Cheng et al., 2010, 2015, 2014; ¨Ozarslan et al., 2013), which makes no assumption of a 3D Gaussian distribution of the diffusion propagator, is used to reconstruct a general function field from DWI…”
BackgroundRensonnet, G., Scherrer, B., Warfield, S. K., Macq, B. M. M., & Taquet, M. (2017) · Magnetic Resonance in Medicine · doi:10.1002/mrm.26832 · Cited by 18
“The errors in Experiment IIa (in blue, obtained with the discrete-continuous optimization scheme [3]) are slightly larger than the asymptotic, noise-free errors observed in Experiment I.”
ResultLucas-Clarke, H. J., Messaritaki, E., Dimitriadis, S. I., & Metzler‐Baddeley, C. (2021) · Brain Connectivity · doi:10.1089/brain.2020.0935 · Cited by 18
“Diffusion-weighted MR images were acquired with High Angular Resolution Diffusion Imaging (HARDI) (Tuch et al., 2002) using a spin-echo echo-planar dual shell HARDI sequence with diffusion encoded along 90 isotropically distributed orientations (Jones et al., 1999) (30 directions at b-value = 1200…”
MethodInfluentialYu, 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
“Several high- order reconstruction and compartmental models have been proposed based on higher angular resolution diffusion MRI (HARDI) acquisition to resolve complex microstructures (Tournier et al., 2004; Tuch et al., 2002).”
BackgroundSteventon, J. J., Trueman, R. C., Rosser, A., & Jones, D. K. (2015) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2015.08.027 · Cited by 18
Modelling, Fitting and Sampling in Diffusion MRI
Alexander, D. C. (2009) · Mathematics and visualization · doi:10.1007/978-3-540-88378-4_1 · Cited by 18
“This observation has motivated extensive recent work on multiple-fibre reconstruction algorithms, such as multi-tensor models [5, 6 ], Qball Imaging [7], PASMRI [8] and spherical deconvolution [9–11]; see [12] for a review.”
MethodSalat, D. H., Lee, S. Y., Yu, P., Setty, B. N., Rosas, H. D., & Grant, P. E. (2009) · Elsevier eBooks · doi:10.1016/b978-0-12-374709-9.00010-9 · Cited by 18
Topological Organization of Whole-Brain White Matter in HIV Infection
Baker, L. M., Cooley, S., Cabeen, R. P., Laidlaw, D. H., Joska, J. A., Hoare, J., Stein, D. J., Heaps‐Woodruff, J. M., Salminen, L. E., & Paul, R. H. (2017) · Brain Connectivity · doi:10.1089/brain.2016.0457 · Cited by 18
“More sophisticated techniques that represent multiple fibers, such as multi-compartment and high angular resolution diffusion imaging, offer greater anatomical accuracy and improved sensitivity in detecting complex anatomical features related to white matter changes due to disease (Tuch et al., 1999; Tuch et al., 2002…”
A general role for ventral white matter pathways in morphological processing: Going beyond reading
Yablonski, M., Menashe, B. A., & Ben‐Shachar, M. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117577 · Cited by 16
Methods of MRI-based structural imaging in the aging monkey
Makris, N., Kennedy, D. N., Boriel, D., & Rosene, D. L. (2009) · Methods · doi:10.1016/j.ymeth.2009.06.007 · Cited by 18
Self-citationA linear and regularized ODF estimation algorithm to recover multiple fibers in Q-Ball imaging
Descoteaux, M., Angelino, E. L., Fitzgibbons, S., & Rachid Deriche, B. (2004) · Cited by 18
Siffredi, 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.”
MethodRadwan, A., Emsell, L., Vansteelandt, K., Cleeren, E., Peeters, R. R., Vleeschouwer, S. D., Theys, T., Dupont, P. J., & Sunaert, S. G. (2024) · Human Brain Mapping · doi:10.1002/hbm.26662 · Cited by 17
“High angular-resolution imaging (HARDI) methods like constrained spherical deconvolution (CSD) (Tournier et al., 2007) can address the limitations of DTI-FACT (Anderson, 2005; Tournier et al., 2004; Tuch et al., 2002, 2003; Wedeen et al., 2000, 2005, 2008).”
MethodLyksborg, M., Siebner, H. R., Sørensen, P. S., Blinkenberg, M., Parker, G. J. M., Dogonowski, A.-M., Garde, E., Larsen, R., & Dyrby, T. B. (2014) · PLoS ONE · doi:10.1371/journal.pone.0095540 · Cited by 17
“The multitensor model by [23] was chosen as the multi-fiber model and the parameters of the model were fitted using a Levenberg-Marquardt optimization available through the Camino software (http://cmic.”
BackgroundMethodCavallari, M., Moscufo, N., Meier, D., Skudlarski, P., Pearlson, G. D., White, W. B., WOLFSON, L. I., & Guttmann, C. R. G. (2014) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.2014.86 · Cited by 17
Resolving axon fiber crossings at clinical b‐values: An evaluation study
Ramírez-Manzanares, A., Cook, P. A., Hall, M. G., Ashtari, M., & Gee, J. C. (2011) · Medical Physics · doi:10.1118/1.3626571 · Cited by 17
A flocking based method for brain tractography
Aranda, R., Rivera, M., & Ramírez-Manzanares, A. (2014) · Medical Image Analysis · doi:10.1016/j.media.2014.01.009 · Cited by 17
Functional and Structural Neural Network Characterization of Serotonin Transporter Knockout Rats
van der Marel, K., Homberg, J. R., Otte, W. M., & Dijkhuizen, R. M. (2013) · PLoS ONE · doi:10.1371/journal.pone.0057780 · Cited by 18
“Measures of underlying structural integrity were obtained from Diffusion Tensor Imaging (DTI) using a highangular resolution diffusion imaging (HARDI) scheme [22].”
MethodIndependent component analysis‐based multifiber streamline tractography of the human brain
Singh, M., & Wong, C. W. (2010) · Magnetic Resonance in Medicine · doi:10.1002/mrm.22509 · Cited by 17
“(10) used a multicompartmental model to estimate parameters of multiple tensors mixed in a voxel.”
MethodSurface-based brain morphometry and diffusion tensor imaging in schizoaffective disorder
Landín-Romero, R., Canales-Rodríguez, E. J., Kumfor, F., Moreno‐Alcázar, A., Madre, M., Maristany, T., Pomarol‐Clotet, E., & Amann, B. L. (2016) · Australian & New Zealand Journal of Psychiatry · doi:10.1177/0004867416631827 · Cited by 18
“Such an approach does not adequately describe diffusion in areas of kissing, branching and crossing fibres and thus cannot fully explain all possible morphological abnormalities in complex brain regions (Tuch et al., 2002).”
BackgroundMerged Group Tractography Evaluation with Selective Automated Group Integrated Tractography
Chen, D. Q., zhong, J., Hayes, D. J., Behan, B., Walker, M., Hung, P. S.-P., & Hodaie, M. (2016) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2016.00096 · Cited by 17
“Improvements over the limits of the DTI model, particularly in increasing angular resolution to improve crossing fibers resolution has been a subject of great interest (Tuch et al., 2002; Fritzsche et al., 2010; Jeurissen et al., 2012).”
BackgroundTract-Specific White Matter Correlates of Age-Related Reward Devaluation Deficits in Macaque Monkeys
Gray, D. T., Umapathy, L., Burke, S. N., Trouard, T. P., & Barnes, C. A. (2018) · Journal of Neuroimaging in Psychiatry and Neurology · doi:10.17756/jnpn.2018-023 · Cited by 16
“Here, we have used DTI as well as modelfree High Angular Resolution Diffusion Imaging (HARDI) methods [29] to generate FA and fiber orientation distribution (FOD) maps, respectively.”
MethodAstola, L., & Florack, L. M. J. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-02256-2_19 · Cited by 17
Hyperspherical von Mises-Fisher Mixture (HvMF) Modelling of High Angular Resolution Diffusion MRI
Bhalerao, A. H., & Westin, C. (2007) · Springer eBooks · doi:10.1007/978-3-540-75757-3_29 · Cited by 17
“We also outlined the connection between spherical harmonic analysis of HARDI samples and our orientation space and how PDD calculations are equivalent.”
BackgroundInfluentialKim, S., Jeong, J., & Singh, M. (2005) · IEEE Transactions on Nuclear Science · doi:10.1109/tns.2004.843137 · Cited by 17
“Recently, it has been shown that the detailed three-dimensional (3-D) shape of the diffusion pattern in a voxel can be determined from a large number of angular measurements [6].”
BackgroundResultInfluentialSemi-Automatic Segmentation of Optic Radiations and LGN, and Their Relationship to EEG Alpha Waves
Renauld, E., Descoteaux, M., Bernier, M., Garyfallidis, E., & Whittingstall, K. (2016) · PLoS ONE · doi:10.1371/journal.pone.0156436 · Cited by 15
Volumetric and fiber-tracing MRI methods for gray and white matter
Larvie, M., & Fischl, B. R. (2016) · Handbook of clinical neurology · doi:10.1016/b978-0-444-53485-9.00003-9 · Cited by 18
Voskuilen, L., Mazzoli, V., Oudeman, J., Balm, A. J. M., van der Heijden, F., Froeling, M., de Win, M. M. L., Strijkers, G. J., Smeele, L. E., & Nederveen, A. J. (2019) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.26609 · Cited by 17
“Therefore, the diffusion sampling strategy required for CSD is referred to as high-angular resolution diffusion imaging (HARDI).(15) Application of this approach to the human tongue is not straightforward, since measurements of many diffusion directions necessitates a long scan time.”
MethodCharvet, C. J. (2020) · Developmental Dynamics · doi:10.1002/dvdy.218 · Cited by 16
“In adulthood, diffusion MR tractography identifies long-range projections (ie, bundles of axons) as fibers (ie, tracts) across the brain.(38-42) Diffusion MR tractography has not only enabled visualizing pathways in the adult brain, it has revealed, with unprecedented detail, the developmental time course of major dev…”
BackgroundScherrer, B., Taquet, M., & Warfield, S. K. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-38868-2_62 · Cited by 16
“Among them, generative models such as multi-tensor models [12,9], CHARMED [2] or NODDI”
MethodBaust, M., Weinmann, A., Wieczorek, M., Lasser, T., Storath, M., & Navab, N. (2016) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2016.2528820 · Cited by 16
“The major limitation of classical DTI appears in the representation of intravoxel crossings of fibers [84], [85].”
BackgroundFixel-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
“Atrophy in the basal ganglia was previously reported between patients with HD and their first-degree relatives at risk of developing the disease (Valdés Hernández et al., 2019).”
BackgroundBeare, R. J., Alexander, B., Warren, A. E. L., Kean, M. J., Seal, M. L., Wray, A. C., Maixner, W. J., & Yang, J. Y. (2022) · International Journal of Computer Assisted Radiology and Surgery · doi:10.1007/s11548-022-02736-7 · Cited by 16
Rashidi, F., Khanmirzaei, M., Hosseinzadeh, F., Kolahchi, Z., Jafarimehrabady, N., Moghisseh, B., & Aarabi, M. H. (2023) · Biology · doi:10.3390/biology12030475 · Cited by 16
Basics of Magnetic Resonance Imaging and Magnetic Resonance Spectroscopy
Brix, G., Kolem, H., Nitz, W. R., Bock, M., Huppertz, A., Zech, C. J., & Dietrich, O. (2007) · Springer eBooks · doi:10.1007/978-3-540-29355-2_2 · Cited by 16
“To overcome this limitation, more complex measurement techniques such as high-angular resolution diffusion imaging (HARDI) (Frank 2001; Tuch et al.”
MethodMultiple Q-Shell ODF Reconstruction in Q-Ball Imaging
Aganj, I., Lenglet, C., Sapiro, G., Yacoub, E. S., Uǧurbil, K., & Harel, N. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-04271-3_52 · Cited by 16
“(HARDI) technique which has been proven very successful in resolving multiple intravoxel fiber orientations in MR images.”
BackgroundInfluentialMeesters, S., Ossenblok, P., Wagner, L., Schijns, O. E. M. G., Boon, P., Florack, L. M. J., Vilanova, A., & Duits, R. (2017) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2017.05.029 · Cited by 16
“Since the tip of the Meyer’s oop has a high curvature, its reconstruction could especially benet from the HARDI acquisition scheme (Tuch et al., 2002), which easures a larger number of directions of diffusion such as 64 r 128 directions.”
Das, A., & Takahashi, E. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx224 · Cited by 15
“HARDI tractography enables identification and discrimination of complex overlapping white matter pathways (Tuch et al. 2002; Berman et al. 2013), even in immature fetal brains (e.g., Takahashi et al. 2011, 2012), which are typically more challenging to segment due to a surplus of unmyelinated…”
BackgroundQuantitative brain morphological analysis in CHARGE syndrome
Shiohama, T., McDavid, J., Levman, J. E. D., & Takahashi, E. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101866 · Cited by 16
Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
Phillips, J. S., Greenberg, A. S., Pyles, J. A., Pathak, S., Behrmann, M., Schneider, W., & Tarr, M. J. (2012) · Journal of Visualized Experiments · doi:10.3791/4125 · Cited by 16
Geodesic regression on orientation distribution functions with its application to an aging study
Du, J. T., Goh, A., Kushnarev, S., & Qiu, A. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.06.081 · Cited by 16
“From existing literature (Aganj et al., 2010b; Descoteaux et al., 2007; Tuch, 2002), we know that at a specific spatial location, x ∈ Ω, HARDI measurements can be used to reconstruct the ODF, the diffusion angular profile of water molecules.”
MethodDiffusion tensor smoothing through weighted Karcher means
Carmichael, O. T., Chen, J., Paul, D., & Peng, J. (2013) · Electronic Journal of Statistics · doi:10.1214/13-ejs825 · Cited by 15
“Such signal to noise ratios are typical for real DTI studies with SNR= 100 at the higher end and SNR = 10 at the lower end (Farrell et al., 2007; Parker et al., 2000; Tuch et al., 2002).”
BackgroundKumar, R., Vemuri, B. C., Wang, F., Syeda-Mahmood, T. F., Carney, P. R., & Mareci, T. H. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-02498-6_12 · Cited by 16
“[25, 3, 20, 9]) that use a discrete mixture of basis functions to approximate the MR signal attenuation.”
BackgroundMulti‐directional anisotropy from diffusion orientation distribution functions
Tan, E. T., Marinelli, L., Sperl, J. I., Menzel, M. I., & Hardy, C. J. (2014) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.24589 · Cited by 16
“Nevertheless, one advantage to using such multi-direction, multi-b value acquisitions is that they yield richer information about constituent fibers and enable multi-fiber tractography that resolves crossing fibers; examples of such acquisitions are high-angular-resolution diffusion imaging or HARDI (27), q-ball (28),…”
BackgroundInfluentialTemperature dependence of water diffusion pools in brain white matter
Dhital, B., Labadie, C., Stallmach, F., Möller, H. E., & Turner, R. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.11.064 · Cited by 16
“Diffusion measurements have also been extensively used in the context of diffusion tensor imaging (DTI) (Basser et al., 1994) and other more complex and powerful methods to reveal fiber orientation in WM (Tuch et al., 2002; Wedeen et al., 2005).”
MethodLee, B., Zhu, X., Li, X., & Chen, W. (2018) · Brain Structure and Function · doi:10.1007/s00429-018-1804-0 · Cited by 17
Information-Theoretic Analysis of Brain White Matter Fiber Orientation Distribution Functions
Chiang, M.-C., Klunder, A. D., McMahon, K. L., de Zubicaray, G. I., Wright, M. J., Toga, A. W., & Thompson, P. M. (2007) · Lecture notes in computer science · doi:10.1007/978-3-540-73273-0_15 · Cited by 16
“High angular resolution diffusion imaging (HARDI) is a variant of conventional MRI that uses multiple radially-distributed gradients to encode directional profiles and orientations of water diffusion [1].”
BackgroundInfluentialBootGraph: Probabilistic fiber tractography using bootstrap algorithms and graph theory
Vorburger, R. S., Reischauer, C., & Boesiger, P. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.10.058 · Cited by 16
“, 2005) and high-angular resolution diffusion-weighted imaging methods (Alexander et al., 2002; Frank, 2001; Jansons and Alexander, 2003; Ozarslan and Mareci, 2003; Ozarslan et al., 2006; Tuch, 2004; Tuch et al., 2002), have recently been introduced.”
BackgroundMethodDT-MRI estimation, regularization and fiber tractography
Rachid Deriche, B., Tschumperlé, D., & Lenglet, C. (2005) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2004.1398461 · Cited by 16
“To better describe the complexity of the diffusion profile, high angular resolution DWI [22] or q-space and Diffusion Spectrum Imaging [10] have been proposed but still yield long acquisition times.”
BackgroundUsing Multiple Tensor Deflection to Reconstruct White Matter Fiber Traces With Branching
Guo, W., Zeng, Q., Chen, Y., & Liu, Y. (2006) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2006.1624854 · Cited by 16
“[7] applied it only to the voxels where the Gaussian model fits the data badly.”
MethodApparent Diffusion Coefficient Approximation and Diffusion Anisotropy Characterization in DWI
Chen, Y., Guo, W., Zeng, Q., Yan, X., Rao, M., & Liu, Y. (2005) · Lecture notes in computer science · doi:10.1007/11505730_21 · Cited by 16
“In [ 18 ,17,19] the model of a mixture of two Gaussians were used to estimate the PDF.”
BackgroundMethodAPOE-ε4-related differences in left thalamic microstructure in cognitively healthy adults
Mole, J. P., Fasano, F., Evans, J., Sims, R., Kidd, E., Aggleton, J. P., & Metzler-Baddeley, C. (2020) · Scientific Reports · doi:10.1038/s41598-020-75992-9 · Cited by 15
Jordan, K., Morin, O., Wahl, M. T., Amirbekian, B., Chapman, C. H., Owen, J. P., Mukherjee, P., Braunstein, S. E., & Henry, R. G. (2019) · Frontiers in Oncology · doi:10.3389/fonc.2019.00810 · Cited by 15
Grant, M., Liu, J., Wintermark, M., Bağcı, U., & Douglas, D. (2023) · Neuroimaging Clinics of North America · doi:10.1016/j.nic.2023.01.004 · Cited by 15
Onda, K., Chavez‐Valdez, R., Graham, E. M., Everett, A. D., Northington, F. J., & Oishi, K. (2023) · Developmental Neuroscience · doi:10.1159/000530938 · Cited by 15
Pisharady, P. K., Eberly, L. E., Adanyeguh, I. M., Manousakis, G., Guliani, G. K., Walk, D., & Lenglet, C. (2023) · Communications Medicine · doi:10.1038/s43856-023-00318-5 · Cited by 19
From Individual to Population: Challenges in Medical Visualization
Botha, C. P., Preim, B., Kaufman, A. E., Takahashi, S., & Ynnerman, A. (2014) · Mathematics and visualization · doi:10.1007/978-1-4471-6497-5_23 · Cited by 15
Dimensionless, Scale Invariant, Edge Weight Metric for the Study of Complex Structural Networks
Colón-Pérez, L. M., Spindler, C., Goicochea, S., Triplett, W. T., Parekh, M. B., Montie, E. W., Carney, P. R., Price, C. C., & Mareci, T. H. (2015) · PLoS ONE · doi:10.1371/journal.pone.0131493 · Cited by 16
“High angular resolution diffusion imaging (HARDI) [37] data were obtained with a spin-echo prepared echo planar image [38] readout using the following set of parameters: TR/TE = 17300/81 ms, 2 scans without diffusion weighting, 6 diffusion gradient directions with b-values of 100 s/mm2 and 64 diffusion gradient direct…”
MethodInfluentialSnow, N. J., Peters, S., Borich, M. R., Shirzad, N., Auriat, A. M., Hayward, K. S., & Boyd, L. A. (2015) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2015.09.025 · Cited by 14
Leigland, L. A., & Kroenke, C. D. (2010) · Neuromethods · doi:10.1007/978-1-60761-883-6_13 · Cited by 14
The Potential for Advanced Magnetic Resonance Neuroimaging Techniques in Pediatric Stroke Research
Domi, T., Vossough, A., Stence, N. V., Felling, R. J., Leung, J., Krishnan, P., Watson, C. G., Grant, P. E., & Kassner, A. (2017) · Pediatric Neurology · doi:10.1016/j.pediatrneurol.2016.12.015 · Cited by 15
Estimation of individual axon bundle properties by a Multi-Resolution Discrete-Search method
Coronado‐Leija, R., Ramírez-Manzanares, A., & Marroquin, J. L. (2017) · Medical Image Analysis · doi:10.1016/j.media.2017.06.008 · Cited by 14
“Originally, this hantom was created using the GMM model for the HARDI recontruction Challenge 2012, however in this work, in order to exper- 4 http://hardi.epfl.ch/static/events/2012 _ ISBI/ . o u ment on as realistic as possible data, we re-created it by using he model (11) as mentioned in Section 3.2 .”
BackgroundMethodInfluentialKwon, D.-H., Paek, S. H., Kim, Y.-B., Lee, H., & Cho, Z.-H. (2021) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2021.739576 · Cited by 15
“Ultra-high field 7T MRI provides an opportunity to investigate the human brain at an enhanced signal-to-noise ratio (SNR), contrast, and resolution compared to low-field MRI (Cho et al., 2010).”
MethodInfluentialBrain‐age estimation accuracy is significantly increased using multishell free‐water reconstruction
Nemmi, F., Levardon, M., & Péran, P. (2022) · Human Brain Mapping · doi:10.1002/hbm.25792 · Cited by 15
Ye, C., Murano, E. Z., Stone, M. L., & Prince, J. L. (2015) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2015.07.005 · Cited by 15
Diffusion spectrum MRI using body-centered-cubic and half-sphere sampling schemes
Kuo, L., Chiang, W.-Y., Yeh, F.-C. F., Wedeen, V. J., & Tseng, W. I. (2012) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2012.09.028 · Cited by 15
“One of the high angularresolution diffusion imaging (HARDI) techniques, diffusion spectrum MRI (DSI), has been demonstrated to have the superb ability to reconstruct fiber pathways and quantify white matter integrity (Kuo et al., 2008b; Tuch et al., 2002; Tuch et al., 2003; Wedeen et al., 2005; Wedeen et al., 2008).”
BackgroundSelf-citationDiffusion magnetic resonance imaging for Brainnetome: A critical review
Zuo, N., Cheng, J., & Jiang, T. (2012) · Neuroscience Bulletin · doi:10.1007/s12264-012-1245-3 · Cited by 15
“The term HARDI was first proposed by Tuch et al. [36] [37] , who reported a finer angular resolution sampling scheme than the conventional DTI scheme.”
BackgroundMethodInfluentialAnatomy-Guided Dense Individualized and Common Connectivity-Based Cortical Landmarks (A-DICCCOL)
Jiang, X., Zhang, T., Zhu, D., Li, K., Chen, H., Lv, J., Hu, X., Han, J., Shen, D. G., Guo, L., et al. (2014) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2014.2369491 · Cited by 15
“Table I) because of its superior quality and capability of dealing with crossing fibers [39].”
BackgroundZhou, D., Dryden, I. L., Koloydenko, A. A., Audenaert, K. M. R., & Bai, L. (2015) · Journal of Applied Statistics · doi:10.1080/02664763.2015.1080671 · Cited by 15
“Also, when more angular directions are available such as in HARDI data [32] more flexible models than diffusion tensors can be explored, which also present more challenges for non-Euclidean statistical analysis.”
BackgroundYoung, R. J., Tan, E. T., Peck, K. K., Jenabi, M., Karimi, S., Brennan, N. M. P., Rubel, J., Lyo, J. K., Shi, W., Zhang, Z., et al. (2016) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2016.10.001 · Cited by 15
“Diffusion spectrum imaging (DSI) is a higher-order diffusion technique capable of resolving crossing fibers.(5-7) These higher-order techniques have demonstrated improved tract density and white matter mapping in the presence of brain tumors.”
BackgroundMeoded, A., Huisman, T. A. G. M., Casamassima, M. G. S., Jallo, G. I., & Poretti, A. (2017) · Neuroradiology · doi:10.1007/s00234-017-1831-1 · Cited by 15
Jayachandra, M. R., Rehbein, N., Herweh, C., & Heiland, S. (2008) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21775 · Cited by 15
“[8]) and have shown the results in the case of a fourth-order tensor.”
BackgroundADVANCED PULSE SEQUENCE TECHNIQUES
Bernstein, M. A., King, K. F., & Zhou, X. J. (2004) · Elsevier eBooks · doi:10.1016/b978-012092861-3/50024-8 · Cited by 15
The Spectral Theory of Tensors (Rough Version)Preprint
Qi, L. (2012) · arXiv (Cornell University) · doi:10.48550/arxiv.1201.3424 · Cited by 15
Magnetic resonance imaging of the dopamine system in schizophrenia – A scoping review
Schulz, J., Zimmermann, J., Sorg, C., Menegaux, A., & Brandl, F. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.925476 · Cited by 14
Palombo, M., Bodini, B., Grussu, F., Bihan, D. L., Nilsson, M., Pérez-López, R., Oei, E. H. G., Schoots, I. G., Smits, M., & Jelescu, I. (2025) · European Radiology · doi:10.1007/s00330-025-12033-x · Cited by 14
Yang, J. Y., Chen, J., Alexander, B., Schilling, K. G., Kean, M. J., Wray, A. C., Seal, M. L., Maixner, W. J., & Beare, R. J. (2022) · NeuroImage Clinical · doi:10.1016/j.nicl.2022.103097 · Cited by 14
“Questions remained regarding the impact of EPI distortion with intraoperatively acquired High Angular Resolution Diffusion Imaging (HARDI) data that has the potential to optimize tractography reconstruction (Tournier, Mori, & Leemans, 2011; Tuch et al., 2002).”
BackgroundSubject–Motion Correction in HARDI Acquisitions: Choices and Consequences
Elhabian, S., Gur, Y., Vachet, C., Piven, J., Styner, M. A., Leppert, I. R., Pike, G. B., & Gerig, G. (2014) · Frontiers in Neurology · doi:10.3389/fneur.2014.00240 · Cited by 14
Probabilistic Inference on Q-ball Imaging Data
Fonteijn, H. M. J., Verstraten, F. A. J., & Norris, D. G. (2007) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2007.907297 · Cited by 14
“This model has been used in a deterministic way [18] and in a Bayesian framework [12], [13].”
BackgroundMethodReal valued diffusion‐weighted imaging using decorrelated phase filtering
Sprenger, T., Sperl, J. I., Fernandez, B., Haase, A., & Menzel, M. I. (2016) · Magnetic Resonance in Medicine · doi:10.1002/mrm.26138 · Cited by 14
“These can be model-dependent techniques such as high angular-resolution diffusion imaging (9), or the model-free approach called diffusion spectrum imaging (DSI) (10).”
Method
Metadata
- Authors
- Tuch, D. S., Reese, T. G., Wiegell, M. R., Makris, N., Belliveau, J. W., & Wedeen, V. J.
- Affiliations
- Massachusetts General Hospital (US)
- Corresponding author
- Wedeen, Van J.
- Venue
- Magnetic Resonance in Medicine
- Publisher
- Wiley
- Published
- 2002-09-26
- Volume
- 48
- Issue
- 4
- Pages
- 577-582
- ISSN
- 0740-3194 (ISSN-L)
- 1522-2594
- OpenAlex
- W2080198834
- Cited by
- 1,548
- References
- 27
- Citations by year
- 2026: 20 · 2025: 43 · 2024: 39 · 2023: 52 · 2022: 59 · 2021: 65 · 2020: 65 · 2019: 82 · 2018: 76 · 2017: 84 · 2016: 84 · 2015: 115 · 2014: 93 · 2013: 95 · 2012: 79
- FWCI
- 23.23
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Magnetic Resonance in Medicine (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Sol Goldman Charitable Trust
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- high angular resolution diffusion imaging
- MeSH terms
- Brain, Computer Simulation, Humans, Image Processing, Computer-Assisted, Male, Nerve Fibers, Anisotropy, Diffusion Magnetic Resonance Imaging
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