Treffer: White Matter Bundle Reconstruction From Single-Shell Diffusion Magnetic Resonance Imaging: Test-Retest Reliability and Predictive Capability Across Orientation Distribution Function Reconstruction Methods.
Original Publication: New York : Wiley-Liss, c1993-
IEEE Trans Med Imaging. 2014 Feb;33(2):384-99. (PMID: 24132007)
Neuroimage. 2016 Apr 1;129:117-132. (PMID: 26774615)
Magn Reson Med. 2012 Aug;68(2):474-83. (PMID: 22162075)
Magn Reson Med. 2017 May;77(5):1797-1809. (PMID: 27173617)
Neuroimage. 2016 Nov 1;141:556-572. (PMID: 27393418)
Hum Brain Mapp. 2025 Apr 01;46(5):e70166. (PMID: 40143640)
Neuroimage. 2021 Dec 15;245:118750. (PMID: 34823023)
Radiology. 2023 Oct;309(1):e230096. (PMID: 37906015)
Neuroimage. 2014 Feb 1;86:544-53. (PMID: 23921101)
Neuroimage. 2020 Dec;223:117329. (PMID: 32882375)
Neuroimage. 2018 Dec;183:239-253. (PMID: 30086412)
Imaging Neurosci (Camb). 2025 Jan 02;3:. (PMID: 40800749)
AJNR Am J Neuroradiol. 2013 Aug;34(8):1573-8. (PMID: 23493892)
Neuroimage. 2000 Jun;11(6 Pt 1):805-21. (PMID: 10860804)
NMR Biomed. 2019 Apr;32(4):e3841. (PMID: 29193413)
Biol Psychiatry Cogn Neurosci Neuroimaging. 2024 Jan;9(1):21-29. (PMID: 37734478)
Nature. 2022 Mar;603(7902):654-660. (PMID: 35296861)
Neuroimage. 2018 Sep;178:622-637. (PMID: 29870817)
Front Neurosci. 2019 Jan 14;12:1055. (PMID: 30692910)
J Magn Reson Imaging. 2001 Apr;13(4):534-46. (PMID: 11276097)
Neuroimage. 2020 Jan 1;204:116207. (PMID: 31539592)
Nat Commun. 2024 Dec 12;15(1):10678. (PMID: 39668158)
NMR Biomed. 2019 Apr;32(4):e3785. (PMID: 28945294)
Med Image Anal. 2015 Dec;26(1):287-305. (PMID: 26599155)
Neuroimage. 2016 Nov 15;142:394-406. (PMID: 27523449)
BMJ Open. 2025 Oct 15;15(10):e106428. (PMID: 41093339)
Neuroradiology. 2011 Oct;53(10):787-91. (PMID: 21547376)
Nat Commun. 2017 Nov 7;8(1):1349. (PMID: 29116093)
J Magn Reson Imaging. 2021 Jun;53(6):1666-1682. (PMID: 32557893)
Neuroimage Clin. 2017 Jul 25;16:222-233. (PMID: 28794981)
Imaging Neurosci (Camb). 2025 Jan 03;3:. (PMID: 40800995)
Neuroimage. 2022 Oct 15;260:119474. (PMID: 35842095)
Nat Methods. 2021 Jul;18(7):775-778. (PMID: 34155395)
J Neurosurg. 2017 May;126(5):1657-1668. (PMID: 27392264)
Neuropsychology. 2015 Mar;29(2):235-46. (PMID: 25180981)
Neuroimage. 2019 Aug 15;197:330-343. (PMID: 31029870)
Neuroimage. 2013 Oct 15;80:62-79. (PMID: 23684880)
Neuroimage. 2019 Jun;193:35-45. (PMID: 30831310)
Apert Neuro. 2021;1(1):. (PMID: 35079748)
Psychol Bull. 1979 Mar;86(2):420-8. (PMID: 18839484)
Neuroimage. 2014 Feb 1;86:231-43. (PMID: 24096127)
Hum Brain Mapp. 2022 Mar;43(4):1196-1213. (PMID: 34921473)
Magn Reson Med. 2020 Oct;84(4):2174-2189. (PMID: 32250475)
J Neurosci Methods. 2010 Mar 30;187(2):254-62. (PMID: 19945485)
Neuroimage. 2019 Nov 15;202:116137. (PMID: 31473352)
Neuroimage. 2005 Aug 1;27(1):48-58. (PMID: 15979342)
Imaging Neurosci (Camb). 2024 Oct 07;2:. (PMID: 40800413)
Neurobiol Aging. 2013 Dec;34(12):2726-33. (PMID: 23850342)
IEEE Trans Med Imaging. 2010 Sep;29(9):1626-35. (PMID: 20304721)
Neuroimage. 2022 Nov 15;262:119531. (PMID: 35931312)
Neuroimage. 2014 Jan 1;84:320-41. (PMID: 23994314)
Front Neurosci. 2019 Jun 07;13:536. (PMID: 31275091)
Magn Reson Imaging. 2019 Apr;57:194-209. (PMID: 30503948)
Neuroimage. 2019 Dec;203:116157. (PMID: 31494250)
Neuroimage Clin. 2023;39:103483. (PMID: 37572514)
PLoS One. 2015 Mar 24;10(3):e0120773. (PMID: 25803023)
Neuropsychology. 2012 Mar;26(2):251-265. (PMID: 22251308)
Neuroimage. 2018 Sep;178:318-331. (PMID: 29787865)
Nat Commun. 2022 Aug 22;13(1):4933. (PMID: 35995773)
IEEE Trans Med Imaging. 2010 Jun;29(6):1310-20. (PMID: 20378467)
Psychol Sci. 2020 Jul;31(7):792-806. (PMID: 32489141)
Nature. 2018 Oct;562(7726):203-209. (PMID: 30305743)
Nat Methods. 2025 Aug;22(8):1617-1619. (PMID: 40707713)
Dev Cogn Neurosci. 2018 Aug;32:16-22. (PMID: 29703560)
Neuroimage. 2012 Jul 16;61(4):1000-16. (PMID: 22484410)
Neurosci Biobehav Rev. 2015 Oct;57:411-32. (PMID: 26449760)
Neuroimage. 2018 Sep;178:57-68. (PMID: 29758339)
Neuroimage. 2015 Apr 1;109:341-56. (PMID: 25555998)
PLoS Comput Biol. 2021 Sep 16;17(9):e1009279. (PMID: 34529652)
Neuroimage. 2016 Jan 15;125:903-919. (PMID: 26520775)
Neuroimage. 2019 Sep;198:231-241. (PMID: 31102735)
Hum Brain Mapp. 2025 Dec 1;46(17):e70429. (PMID: 41376618)
Hum Brain Mapp. 2023 Apr 1;44(5):1913-1933. (PMID: 36541441)
NMR Biomed. 2013 Dec;26(12):1775-86. (PMID: 24038308)
Neuroimage. 2022 Apr 1;249:118870. (PMID: 34979249)
Front Neurosci. 2020 May 06;14:396. (PMID: 32435181)
Neuroimage. 2007 May 1;35(4):1459-72. (PMID: 17379540)
Hum Brain Mapp. 2014 Nov;35(11):5667-85. (PMID: 25044786)
J Neuroimaging. 2016 Jan-Feb;26(1):46-57. (PMID: 26464179)
Invest Radiol. 2024 Jan 1;59(1):13-25. (PMID: 37707839)
Neuroimage. 2016 Jan 15;125:1063-1078. (PMID: 26481672)
Neuroimage. 2010 Jan 15;49(2):1357-71. (PMID: 19819339)
Neuroimage. 2006 Jul 1;31(3):1116-28. (PMID: 16545965)
Front Neuroimaging. 2024 Mar 28;3:1359589. (PMID: 38606197)
Neuroimage. 2014 Dec;103:411-426. (PMID: 25109526)
Hum Brain Mapp. 2019 Jul;40(10):3041-3057. (PMID: 30875144)
Neuroimage. 2022 Nov;263:119636. (PMID: 36116616)
Hum Brain Mapp. 2021 Jul;42(10):3102-3118. (PMID: 33830577)
GigaByte. 2024 Mar 07;2024:gigabyte113. (PMID: 38496213)
Weitere Informationen
Deriving white matter (WM) bundles in vivo has thus far mainly been applied in research settings, leveraging high angular resolution, multi-shell diffusion MRI (dMRI) acquisitions that enable modern reconstruction methods. However, these advanced acquisitions are both time-consuming and costly to acquire. The ability to reconstruct WM bundles in the massive amounts of existing single-shelled, lower angular resolution data from legacy research studies and healthcare systems would offer much broader clinical applications and population-level generalizability. While legacy scans may offer a valuable, large-scale complement to contemporary research datasets, the reliability of white matter bundles derived from these scans remains unclear. Here, we leverage a large research dataset where each 64-direction dMRI scan was acquired as two independent 32-direction runs per subject. To investigate how a state-of-the-art bundle-specific reconstruction method generalizes to this data, we evaluated the test-retest reliability of WM bundles reconstructed from the two 32-direction scans across three orientation distribution function (ODF) reconstruction methods: generalized q-sampling imaging (GQI), constrained spherical deconvolution (CSD), and single-shell three-tissue CSD (SS3T). We found that the majority of WM bundles could be reliably extracted from dMRI scans that were acquired using the 32-direction, single-shell acquisition scheme. The mean Dice coefficient of reconstructed WM bundles was consistently higher within subject than between subject for all WM bundles and ODF reconstruction methods, illustrating preservation of person-specific anatomy. Further, when using features of the bundles to predict complex reasoning assessed using a computerized cognitive battery, we observed stable prediction accuracies (r: 0.15-0.36) across the test-retest data. Among the three ODF reconstruction methods, SS3T had a good balance between sensitivity and specificity when comparing the reconstructed bundles to atlas bundles, a high intra-class correlation of extracted features, more plausible bundles, and strong predictive performance. More broadly, these results demonstrate that bundle-specific reconstruction can achieve robust performance even on lower angular resolution, single-shell dMRI, with particular advantages for ODF methods optimized for single-shell data. This highlights the considerable potential for dMRI collected in healthcare settings and legacy research datasets to accelerate and expand the scope of WM research.
(© 2025 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)