Fiber-tract localized diffusion coefficients highlight patterns of white matter disruption induced by proximity to glioma
Autoři:
Shawn D’Souza aff001; D. Ryan Ormond aff002; Jamie Costabile aff002; John A. Thompson aff002
Působiště autorů:
Department of Molecular Biology, University of Colorado, Boulder, CO, United States of America
aff001; Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
aff002; Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
aff003
Vyšlo v časopise:
PLoS ONE 14(11)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0225323
Souhrn
Gliomas account for 26.5% of all primary central nervous system tumors. Recent studies have used diffusion tensor imaging (DTI) to extract white matter fibers and the diffusion coefficients derived from MR processing to provide useful, non-invasive insights into the extent of tumor invasion, axonal integrity, and gross differentiation of glioma from metastasis. Here, we extend this work by examining whether a tract-based analysis can improve non-invasive localization of tumor impact on white matter integrity. This study retrospectively analyzed preoperative magnetic resonance sequences highlighting contrast enhancement and DTI scans of 13 subjects that were biopsy-confirmed to have either high or low-grade glioma. We reconstructed the corticospinal tract and superior longitudinal fasciculus by applying atlas-based regions of interest to fibers derived from whole-brain deterministic streamline tractography. Within-subject comparison of hemispheric diffusion coefficients (e.g., fractional anisotropy and mean diffusivity) indicated higher levels of white matter degradation in the ipsilesional hemisphere. Novel application of along-tract analyses revealed that tracts traversing the tumor region showed significant white matter degradation compared to the contralesional hemisphere and ipsilesional tracts displaced by the tumor.
Klíčová slova:
Alzheimer's disease – Central nervous system – Diffusion tensor imaging – Glioma – Mass diffusivity – Surgical oncology – Tractography – Tumor resection
Zdroje
1. Ostrom QT, Gittleman H, Liao P, Vecchione-Koval T, Wolinsky Y, Kruchko C, et al. CBTRUS Statistical Report: Primary brain and other central nervous system tumors diagnosed in the United States in 2010–2014. Neuro Oncol. Oxford University Press; 2017;19: v1–v88. doi: 10.1093/neuonc/nox158 29117289
2. Louis DN, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee WK, et al. The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary. Acta Neuropathol. Springer Berlin Heidelberg; 2016;131: 803–820. doi: 10.1007/s00401-016-1545-1 27157931
3. Raza SM, Lang FF, Aggarwal BB, Fuller GN, Wildrick DM, Sawaya R. Necrosis and Glioblastoma: A Friend or a Foe? A Review and a Hypothesis. Neurosurgery. Oxford University Press; 2002;51: 2–13. doi: 10.1097/00006123-200207000-00002 12182418
4. Goldbrunner R, Ruge M, Kocher M, Lucas CW, Galldiks N, Grau S. The treatment of gliomas in adulthood. Dtsch Aerzteblatt Online. 2018; doi: 10.3238/arztebl.2018.0356 29914619
5. Li YM, Suki D, Hess K, Sawaya R. The influence of maximum safe resection of glioblastoma on survival in 1229 patients: Can we do better than gross-total resection? J Neurosurg. 2016;124: 977–988. doi: 10.3171/2015.5.JNS142087 26495941
6. Kreth FW, Berlis A, Spiropoulou V, Faist M, Scheremet R, Rossner R, et al. The role of tumor resection in the treatment of glioblastoma multiforme in adults. Cancer. 1999;86: 2117–23. Available: http://www.ncbi.nlm.nih.gov/pubmed/10570440 10570440
7. Stummer W, Reulen H-J, Meinel T, Pichlmeier U, Schumacher W, Tonn J-C, et al. Extent of Resection and Survival in Glioblastoma Multiforme. Neurosurgery. 2008;62: 564–576. doi: 10.1227/01.neu.0000317304.31579.17 18425006
8. Costabile JD, Alaswad E, D’Souza S, Thompson JA, Ormond DR. Current Applications of Diffusion Tensor Imaging and Tractography in Intracranial Tumor Resection. Front Oncol. Frontiers Media SA; 2019;9: 426. doi: 10.3389/fonc.2019.00426 31192130
9. Bucci M, Mandelli ML, Berman JI, Amirbekian B, Nguyen C, Berger MS, et al. Quantifying diffusion MRI tractography of the corticospinal tract in brain tumors with deterministic and probabilistic methods. NeuroImage Clin. Elsevier; 2013;3: 361–368. doi: 10.1016/J.NICL.2013.08.008 24273719
10. Essayed WI, Zhang F, Unadkat P, Cosgrove GR, Golby AJ, O’Donnell LJ. White matter tractography for neurosurgical planning: A topography-based review of the current state of the art. NeuroImage Clin. 2017;15: 659–672. doi: 10.1016/j.nicl.2017.06.011 28664037
11. Caverzasi E, Hervey-Jumper SL, Jordan KM, Lobach I V., Li J, Panara V, et al. Identifying preoperative language tracts and predicting postoperative functional recovery using HARDI q-ball fiber tractography in patients with gliomas. J Neurosurg. 2016;125: 33–45. doi: 10.3171/2015.6.JNS142203 26654181
12. Meyer EJ, Gaggl W, Gilloon B, Swan B, Greenstein M, Voss J, et al. The Impact of Intracranial Tumor Proximity to White Matter Tracts on Morbidity and Mortality: A Retrospective Diffusion Tensor Imaging Study. Neurosurgery. 2017;80: 193–200. doi: 10.1093/neuros/nyw040 28173590
13. D’Andrea G, Familiari P, Di Lauro A, Angelini A, Sessa G. Safe Resection of Gliomas of the Dominant Angular Gyrus Availing of Preoperative FMRI and Intraoperative DTI: Preliminary Series and Surgical Technique. World Neurosurg. 2016;87: 627–639. doi: 10.1016/j.wneu.2015.10.076 26548825
14. Vassal F, Schneider F, Nuti C. Intraoperative use of diffusion tensor imaging-based tractography for resection of gliomas located near the pyramidal tract: comparison with subcortical stimulation mapping and contribution to surgical outcomes. Br J Neurosurg. 2013;27: 668–675. doi: 10.3109/02688697.2013.771730 23458557
15. Alexander AL, Lee JE, Lazar M, Field AS. Diffusion tensor imaging of the brain. Neurotherapeutics. NIH Public Access; 2007;4: 316–29. doi: 10.1016/j.nurt.2007.05.011 17599699
16. Racine AM, Adluru N, Alexander AL, Christian BT, Okonkwo OC, Oh J, et al. Associations between white matter microstructure and amyloid burden in preclinical Alzheimer’s disease: A multimodal imaging investigation. NeuroImage Clin. Elsevier; 2014;4: 604–14. doi: 10.1016/j.nicl.2014.02.001 24936411
17. Winklewski PJ, Sabisz A, Naumczyk P, Jodzio K, Szurowska E, Szarmach A. Understanding the Physiopathology Behind Axial and Radial Diffusivity Changes-What Do We Know? Front Neurol. Frontiers Media SA; 2018;9: 92. doi: 10.3389/fneur.2018.00092 29535676
18. Clark KA, Nuechterlein KH, Asarnow RF, Hamilton LS, Phillips OR, Hageman NS, et al. Mean diffusivity and fractional anisotropy as indicators of disease and genetic liability to schizophrenia. J Psychiatr Res. NIH Public Access; 2011;45: 980–8. doi: 10.1016/j.jpsychires.2011.01.006 21306734
19. Naggara O, Oppenheim C, Rieu D, Raoux N, Rodrigo S, Dalla Barba G, et al. Diffusion tensor imaging in early Alzheimer’s disease. Psychiatry Res Neuroimaging. Elsevier; 2006;146: 243–249. doi: 10.1016/J.PSCYCHRESNS.2006.01.005 16520023
20. Laule C, Vavasour IM, Moore GRW, Oger J, Li DKB, Paty DW, et al. Water content and myelin water fraction in multiple sclerosis. J Neurol. 2004;251: 284–293. doi: 10.1007/s00415-004-0306-6 15015007
21. Aung WY, Mar S, Benzinger TL. Diffusion tensor MRI as a biomarker in axonal and myelin damage. Imaging Med. NIH Public Access; 2013;5: 427–440. doi: 10.2217/iim.13.49 24795779
22. Sun S-W, Liang H-F, Trinkaus K, Cross AH, Armstrong RC, Song S-K. Noninvasive detection of cuprizone induced axonal damage and demyelination in the mouse corpus callosum. Magn Reson Med. 2006;55: 302–308. doi: 10.1002/mrm.20774 16408263
23. Colby JB, Soderberg L, Lebel C, Dinov ID, Thompson PM, Sowell ER. Along-tract statistics allow for enhanced tractography analysis. Neuroimage. 2012;59: 3227–3242. doi: 10.1016/j.neuroimage.2011.11.004 22094644
24. Ormond DR, D’Souza S, Thompson JA. Global and Targeted Pathway Impact of Gliomas on White Matter Integrity Based on Lobar Localization. Cureus. 2017; doi: 10.7759/cureus.1660 29147635
25. Puig J, Blasco G, Schlaug G, Stinear CM, Daunis-i-Estadella P, Biarnes C, et al. Diffusion tensor imaging as a prognostic biomarker for motor recovery and rehabilitation after stroke. Neuroradiology. 2017;59: 343–351. doi: 10.1007/s00234-017-1816-0 28293701
26. Rong D, Zhang M, Ma Q, Lu J, Li K. Corticospinal Tract Change during Motor Recovery in Patients with Medulla Infarct: A Diffusion Tensor Imaging Study. Biomed Res Int. 2014;2014: 1–5. doi: 10.1155/2014/524096 24967374
27. Kamali A, Flanders AE, Brody J, Hunter J V, Hasan KM. Tracing superior longitudinal fasciculus connectivity in the human brain using high resolution diffusion tensor tractography. Brain Struct Funct. NIH Public Access; 2014;219: 269–81. doi: 10.1007/s00429-012-0498-y 23288254
28. Madhavan KM, McQueeny T, Howe SR, Shear P, Szaflarski J. Superior longitudinal fasciculus and language functioning in healthy aging. Brain Res. NIH Public Access; 2014;1562: 11–22. doi: 10.1016/j.brainres.2014.03.012 24680744
29. Sollmann N, Fratini A, Zhang H, Zimmer C, Meyer B, Krieg SM. Associations between clinical outcome and tractography based on navigated transcranial magnetic stimulation in patients with language-eloquent brain lesions. J Neurosurg. 2019; 1–10. doi: 10.3171/2018.12.JNS182988 30875686
30. Li Z, Wang M, Zhang L, Fan X, Tao X, Qi L, et al. Neuronavigation-Guided Corticospinal Tract Mapping in Brainstem Tumor Surgery: Better Preservation of Motor Function. World Neurosurg. 2018;116: e291–e297. doi: 10.1016/j.wneu.2018.04.189 29733992
31. Yeh F-C, Tseng W-YI. NTU-90: A high angular resolution brain atlas constructed by q-space diffeomorphic reconstruction. Neuroimage. Academic Press; 2011;58: 91–99. doi: 10.1016/j.neuroimage.2011.06.021 21704171
32. Yushkevich PA, Piven J, Hazlett HC, Smith RG, Ho S, Gee JC, et al. User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability. Neuroimage. Academic Press; 2006;31: 1116–1128. doi: 10.1016/j.neuroimage.2006.01.015 16545965
33. Strugar JG, Criscuolo GR, Rothbart D, Harrington WN. Vascular endothelial growth/permeability factor expression in human glioma specimens: correlation with vasogenic brain edema and tumor-associated cysts. J Neurosurg. Journal of Neurosurgery Publishing Group; 1995;83: 682–689. doi: 10.3171/jns.1995.83.4.0682 7674019
34. Yeh F-C, Wedeen VJ, Tseng W-YI. Generalized $ {q}$-Sampling Imaging. IEEE Trans Med Imaging. 2010;29: 1626–1635. doi: 10.1109/TMI.2010.2045126 20304721
35. Yeh F-C, Liu L, Hitchens TK, Wu YL. Mapping immune cell infiltration using restricted diffusion MRI. Magn Reson Med. John Wiley & Sons, Ltd; 2017;77: 603–612. doi: 10.1002/mrm.26143 26843524
36. Schilling KG, Gao Y, Li M, Wu T, Blaber J, Landman BA, et al. Functional tractography of white matter by high angular resolution functional‐correlation imaging (HARFI). Magn Reson Med. 2019;81: 2011–2024. doi: 10.1002/mrm.27512 30277272
37. Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, et al. Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain. Neuroimage. Academic Press; 2002;15: 273–289. doi: 10.1006/nimg.2001.0978 11771995
38. Yeh F-C, Verstynen TD, Wang Y, Fernández-Miranda JC, Tseng W-YI. Deterministic Diffusion Fiber Tracking Improved by Quantitative Anisotropy. Zhan W, editor. PLoS One. Public Library of Science; 2013;8: e80713. doi: 10.1371/journal.pone.0080713 24348913
39. Rousselet GA, Pernet CR, Wilcox RR. Beyond differences in means: robust graphical methods to compare two groups in neuroscience. Eur J Neurosci. 2017;46: 1738–1748. doi: 10.1111/ejn.13610 28544058
40. Doksum K. Empirical Probability Plots and Statistical Inference for Nonlinear Models in the Two-Sample Case. Ann Stat. Institute of Mathematical Statistics; 1974;2: 267–277. doi: 10.1214/aos/1176342662
41. Wilcox RR. Comparing Two Independent Groups Via Multiple Quantiles. Stat. John Wiley & Sons, Ltd (10.1111); 1995;44: 91. doi: 10.2307/2348620
42. Harrell FE, Davis CE. A New Distribution-Free Quantile Estimator. Biometrika. Oxford University PressBiometrika Trust; 1982;69: 635. doi: 10.2307/2335999
43. Mori S, Wakana S, Van Zijl PCM, Nagae-Poetscher LM. MRI atlas of human white matter. Elsevier; 2005.
44. Wakana S, Caprihan A, Panzenboeck MM, Fallon JH, Perry M, Gollub RL, et al. Reproducibility of quantitative tractography methods applied to cerebral white matter. Neuroimage. Academic Press; 2007;36: 630–644. doi: 10.1016/j.neuroimage.2007.02.049 17481925
45. Manjón J V., Coupé P. volBrain: An Online MRI Brain Volumetry System. Front Neuroinform. Frontiers; 2016;10: 30. doi: 10.3389/fninf.2016.00030 27512372
46. Manjón J V., Tohka J, Robles M. Improved estimates of partial volume coefficients from noisy brain MRI using spatial context. Neuroimage. Academic Press; 2010;53: 480–490. doi: 10.1016/j.neuroimage.2010.06.046 20600978
47. Jellison BJ, Field AS, Medow J, Lazar M, Salamat MS, Alexander AL. American Journal of Neuroradiology. Am J Neuroradiol. American Journal of Neuroradiology; 2004;23: 67–75. Available: http://www.ajnr.org/content/25/3/356.short
48. Provenzale JM, Mukundan S, Barboriak DP. Diffusion-weighted and Perfusion MR Imaging for Brain Tumor Characterization and Assessment of Treatment Response. Radiology. 2006;239: 632–649. doi: 10.1148/radiol.2393042031 16714455
49. Henry RG, Berman JI, Nagarajan SS, Mukherjee P, Berger MS. Subcortical pathways serving cortical language sites: initial experience with diffusion tensor imaging fiber tracking combined with intraoperative language mapping. Neuroimage. Academic Press; 2004;21: 616–622. doi: 10.1016/j.neuroimage.2003.09.047 14980564
50. Holodny AI, Schwartz TH, Ollenschleger M, Liu W-C, Schulder M. Tumor involvement of the corticospinal tract: diffusion magnetic resonance tractography with intraoperative correlation. J Neurosurg. 2001;95: 1082. doi: 10.3171/jns.2001.95.6.1082 11765829
51. Stadlbauer A, Nimsky C, Buslei R, Salomonowitz E, Hammen T, Buchfelder M, et al. Diffusion tensor imaging and optimized fiber tracking in glioma patients: Histopathologic evaluation of tumor-invaded white matter structures. Neuroimage. Academic Press; 2007;34: 949–956. doi: 10.1016/j.neuroimage.2006.08.051 17166744
52. Castellano A, Bello L, Michelozzi C, Gallucci M, Fava E, Iadanza A, et al. Role of diffusion tensor magnetic resonance tractography in predicting the extent of resection in glioma surgery. Neuro Oncol. Oxford University Press; 2012;14: 192–202. doi: 10.1093/neuonc/nor188 22015596
53. Nilsson M, Englund E, Szczepankiewicz F, van Westen D, Sundgren PC. Imaging brain tumour microstructure. Neuroimage. Academic Press; 2018;182: 232–250. doi: 10.1016/j.neuroimage.2018.04.075 29751058
54. Song S-K, Sun S-W, Ju W-K, Lin S-J, Cross AH, Neufeld AH. Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia. Neuroimage. Academic Press; 2003;20: 1714–1722. doi: 10.1016/j.neuroimage.2003.07.005 14642481
55. Song S-K, Yoshino J, Le TQ, Lin S-J, Sun S-W, Cross AH, et al. Demyelination increases radial diffusivity in corpus callosum of mouse brain. Neuroimage. 2005;26: 132–140. doi: 10.1016/j.neuroimage.2005.01.028 15862213
56. Rosas HD, Lee SY, Bender AC, Zaleta AK, Vangel M, Yu P, et al. Altered white matter microstructure in the corpus callosum in Huntington’s disease: Implications for cortical “disconnection.” Neuroimage. 2010;49: 2995–3004. doi: 10.1016/j.neuroimage.2009.10.015 19850138
57. Della Nave R, Ginestroni A, Tessa C, Giannelli M, Piacentini S, Filippi M, et al. Regional Distribution and Clinical Correlates of White Matter Structural Damage in Huntington Disease: A Tract-Based Spatial Statistics Study. Am J Neuroradiol. 2010;31: 1675–1681. doi: 10.3174/ajnr.A2128 20488902
58. Odish OFF, Reijntjes RHAM, van den Bogaard SJA, Roos RAC, Leemans A. Progressive microstructural changes of the occipital cortex in Huntington’s disease. Brain Imaging Behav. Springer US; 2018;12: 1786–1794. doi: 10.1007/s11682-018-9849-5 29492750
59. Bourbon-Teles J, Bells S, Jones DK, Coulthard E, Rosser A, Metzler-Baddeley C. Myelin Breakdown in Human Huntington’s Disease: Multi-Modal Evidence from Diffusion MRI and Quantitative Magnetization Transfer. Neuroscience. Pergamon; 2019;403: 79–92. doi: 10.1016/j.neuroscience.2017.05.042 28579146
60. Acosta-Cabronero J, Williams GB, Pengas G, Nestor PJ. Absolute diffusivities define the landscape of white matter degeneration in Alzheimer’s disease. Brain. 2010;133: 529–539. doi: 10.1093/brain/awp257 19914928
61. Salat DH, Tuch DS, van der Kouwe AJW, Greve DN, Pappu V, Lee SY, et al. White matter pathology isolates the hippocampal formation in Alzheimer’s disease. Neurobiol Aging. 2010;31: 244–256. doi: 10.1016/j.neurobiolaging.2008.03.013 18455835
62. Cavedo E, Lista S, Rojkova K, Chiesa PA, Houot M, Brueggen K, et al. Disrupted white matter structural networks in healthy older adult APOE ε4 carriers–An international multicenter DTI study. Neuroscience. Pergamon; 2017;357: 119–133. doi: 10.1016/j.neuroscience.2017.05.048 28596117
63. Pozorski V, Oh JM, Adluru N, Merluzzi AP, Theisen F, Okonkwo O, et al. Longitudinal white matter microstructural change in Parkinson’s disease. Hum Brain Mapp. John Wiley & Sons, Ltd; 2018;39: 4150–4161. doi: 10.1002/hbm.24239 29952102
64. Della Nave R, Ginestroni A, Diciotti S, Salvatore E, Soricelli A, Mascalchi M. Axial diffusivity is increased in the degenerating superior cerebellar peduncles of Friedreich’s ataxia. Neuroradiology. 2011;53: 367–372. doi: 10.1007/s00234-010-0807-1 21128070
65. Angeli S, Emblem KE, Due-Tonnessen P, Stylianopoulos T. Towards patient-specific modeling of brain tumor growth and formation of secondary nodes guided by DTI-MRI. NeuroImage Clin. Elsevier; 2018;20: 664–673. doi: 10.1016/j.nicl.2018.08.032 30211003
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