Fiber visualization for preoperative glioma assessment: Tractography versus local connectivity mapping
Autoři:
Thomas Schult aff001; Till-Karsten Hauser aff002; Uwe Klose aff002; Helene Hurth aff003; Hans-Heino Ehricke aff001
Působiště autorů:
Institute for Applied Computer Science, Stralsund University of Applied Sciences, Stralsund, Germany
aff001; Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany
aff002; Department of Neurosurgery, University Hospital Tübingen, Tübingen, Germany
aff003
Vyšlo v časopise:
PLoS ONE 14(12)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0226153
Souhrn
In diffusion MRI, the advent of high angular resolution diffusion imaging (HARDI) and HARDI with compressed sensing (HARDI+CS) has led to clinically practical signal acquisition techniques which allow for the assessment of white matter architecture in routine patient studies. However, the reconstruction and visualization of fiber pathways by tractography has not yet been established as a standard methodology which can easily be applied. This is due to various algorithmic problems, such as a lack of robustness, error propagation and the necessity of fine-tuning parameters depending on the clinical question. In the framework of a clinical study of glioma patients, we compare two different whole-brain tracking methods to a local connectivity mapping approach which has recently shown promising results in an adaptation to diffusion MRI. The ability of the three methods to correctly depict fiber affection is analyzed by comparing visualization results to representations of local diffusion profiles provided by orientation distribution functions (ODFs). Our results suggest that methods beyond fiber tractography, which visualize local connectedness rather than global connectivity, should be evaluated further for pre-surgical assessment of fiber affection.
Klíčová slova:
Tractography – Central nervous system – Magnetic resonance imaging – Data acquisition – Anisotropy – Glioma – Ligation independent cloning
Zdroje
1. Tuch DS. Q-ball imaging. Magn Reson Med. 2004;52(6):1358–72. doi: 10.1002/mrm.20279 15562495
2. Descoteaux M, Angelino E, Fitzgibbons S, Deriche R. Regularized, fast, and robust analytical Q-ball imaging. Magn Reson Med. 2007;58(3):497–510. doi: 10.1002/mrm.21277 17763358
3. Aganj I, Lenglet C, Sapiro G, Yacoub E, Ugurbil K, Harel N. Reconstruction of the orientation distribution function in single- and multiple-shell q-ball imaging within constant solid angle. Magn Reson Med. 2010;64(2):554–66. doi: 10.1002/mrm.22365 20535807
4. Tournier JD, Calamante F, Gadian DG, Connelly A. Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution. Neuroimage [Internet]. 2004/11/06. 2004;23(3):1176–85. Available from: http://www.ncbi.nlm.nih.gov/pubmed/15528117 doi: 10.1016/j.neuroimage.2004.07.037 15528117
5. Tournier JD, Calamante F, Connelly A. Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution. Neuroimage [Internet]. 2007;35(4):1459–72. Available from: http://www.ncbi.nlm.nih.gov/pubmed/17379540 doi: 10.1016/j.neuroimage.2007.02.016 17379540
6. McGirt MJ, Chaichana KL, Gathinji M, Attenello FJ, Than K, Olivi A, et al. Independent association of extent of resection with survival in patients with malignant brain astrocytoma. J Neurosurg [Internet]. 2009 Jan;110(1):156–62. Available from: https://thejns.org/view/journals/j-neurosurg/110/1/article-p156.xml doi: 10.3171/2008.4.17536 18847342
7. Sanai N, Polley M-Y, McDermott MW, Parsa AT, Berger MS. An extent of resection threshold for newly diagnosed glioblastomas. J Neurosurg [Internet]. 2011 Jul;115(1):3–8. Available from: https://thejns.org/view/journals/j-neurosurg/115/1/article-p3.xml doi: 10.3171/2011.2.JNS10998 21417701
8. 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 [Internet]. 2017;15:659–72. Available from: https://linkinghub.elsevier.com/retrieve/pii/S2213158217301444 doi: 10.1016/j.nicl.2017.06.011 28664037
9. Kuhnt D, Bauer MHA, Egger J, Richter M, Kapur T, Sommer J, et al. Fiber tractography based on diffusion tensor imaging compared with high-angular-resolution diffusion imaging with compressed sensing: Initial experience. Neurosurgery. 2013;72(5):165–75.
10. Kuhnt D, Bauer MHA, Sommer J, Merhof D, Nimsky C. Optic Radiation Fiber Tractography in Glioma Patients Based on High Angular Resolution Diffusion Imaging with Compressed Sensing Compared with Diffusion Tensor Imaging—Initial Experience. Paul F, editor. PLoS One [Internet]. 2013 Jul 26;8(7):e70973. Available from: doi: 10.1371/journal.pone.0070973 23923036
11. Abhinav K, Yeh F-C, Mansouri A, Zadeh G, Fernandez-Miranda JC. High-definition fiber tractography for the evaluation of perilesional white matter tracts in high-grade glioma surgery. Neuro Oncol [Internet]. 2015 Jun 27;17(9):1199–209. Available from: https://academic.oup.com/neuro-oncology/article-lookup/doi/10.1093/neuonc/nov113 26117712
12. 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 [Internet]. 2013;3:361–8. Available from: https://linkinghub.elsevier.com/retrieve/pii/S2213158213001083 doi: 10.1016/j.nicl.2013.08.008 24273719
13. Mormina E, Longo M, Arrigo A, Alafaci C, Tomasello F, Calamuneri A, et al. MRI Tractography of Corticospinal Tract and Arcuate Fasciculus in High-Grade Gliomas Performed by Constrained Spherical Deconvolution: Qualitative and Quantitative Analysis. Am J Neuroradiol [Internet]. 2015 Oct;36(10):1853–8. Available from: doi: 10.3174/ajnr.A4368 26113071
14. Liao R, Ning L, Chen Z, Rigolo L, Gong S, Pasternak O, et al. Performance of unscented Kalman filter tractography in edema: Analysis of the two-tensor model. NeuroImage Clin [Internet]. 2017;15:819–31. Available from: https://linkinghub.elsevier.com/retrieve/pii/S2213158217301584 doi: 10.1016/j.nicl.2017.06.027 28725549
15. Chen Z, Tie Y, Olubiyi O, Rigolo L, Mehrtash A, Norton I, et al. Reconstruction of the arcuate fasciculus for surgical planning in the setting of peritumoral edema using two-tensor unscented Kalman filter tractography. NeuroImage Clin [Internet]. 2015;7:815–22. Available from: https://linkinghub.elsevier.com/retrieve/pii/S2213158215000510 doi: 10.1016/j.nicl.2015.03.009 26082890
16. O’Donnell LJ, Suter Y, Rigolo L, Kahali P, Zhang F, Norton I, et al. Automated white matter fiber tract identification in patients with brain tumors. NeuroImage Clin [Internet]. 2017;13:138–53. Available from: https://linkinghub.elsevier.com/retrieve/pii/S2213158216302315 doi: 10.1016/j.nicl.2016.11.023 27981029
17. Stadlbauer A, Nimsky C, Gruber S, Moser E, Hammen T, Engelhorn T, et al. Changes in fiber integrity, diffusivity, and metabolism of the pyramidal tract adjacent to gliomas: a quantitative diffusion tensor fiber tracking and MR spectroscopic imaging study. AJNR Am J Neuroradiol [Internet]. 2007 Mar;28(3):462–9. Available from: http://www.ncbi.nlm.nih.gov/pubmed/17353313 17353313
18. Pujol S, Wells W, Pierpaoli C, Brun C, Gee J, Cheng G, et al. The DTI Challenge: Toward Standardized Evaluation of Diffusion Tensor Imaging Tractography for Neurosurgery. J Neuroimaging [Internet]. 2015 Nov;25(6):875–82. Available from: doi: 10.1111/jon.12283 26259925
19. Barbosa BJAP, Dimostheni A, Teixeira MJ, Tatagiba M, Lepski G. Insular gliomas and the role of intraoperative assistive technologies: Results from a volumetry-based retrospective cohort. Clin Neurol Neurosurg [Internet]. 2016 Oct;149:104–10. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0303846716302852 doi: 10.1016/j.clineuro.2016.08.001 27509592
20. Charras P, Herbet G, Deverdun J, de Champfleur NM, Duffau H, Bartolomeo P, et al. Functional reorganization of the attentional networks in low-grade glioma patients: A longitudinal study. Cortex [Internet]. 2015 Feb;63:27–41. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0010945214002639 doi: 10.1016/j.cortex.2014.08.010 25241396
21. Kekhia H, Rigolo L, Norton I, Golby AJ. Special Surgical Considerations for Functional Brain Mapping. Neurosurg Clin N Am [Internet]. 2011 Apr;22(2):111–32. Available from: https://linkinghub.elsevier.com/retrieve/pii/S1042368011000052 doi: 10.1016/j.nec.2011.01.004 21435565
22. Kuhnt D, Bauer MHA, Becker A, Merhof D, Zolal A, Richter M, et al. Intraoperative Visualization of Fiber Tracking Based Reconstruction of Language Pathways in Glioma Surgery. Neurosurgery [Internet]. 2012 Apr;70(4):911–9. Available from: https://academic.oup.com/neurosurgery/article-lookup/doi/10.1227/NEU.0b013e318237a807 21946508
23. Wu J-S, Zhou L-F, Tang W-J, Mao Y, Hu J, Song Y-Y, et al. Clinical evaluation and follow-up outcome of diffusion tensor imaging-based functional neuronavigation: A prospective, controlled study in patients with gliomas involving pyramidal tracts. Neurosurgery [Internet]. 2007 Nov 1;61(5):935–48. Available from: https://academic.oup.com/neurosurgery/article/61/5/935/2558469 doi: 10.1227/01.neu.0000303189.80049.ab 18091270
24. Pierpaoli C, Basser PJ. Toward a quantitative assessment of diffusion anisotropy. Magn Reson Med [Internet]. 1996 Dec;36(6):893–906. Available from: http://www.ncbi.nlm.nih.gov/pubmed/8946355%5Cnhttp://doi.wiley.com/10.1002/mrm.1910360612 8946355
25. Tuch DS, Reese TG, Wiegell MR, Van J. Wedeen. Diffusion MRI of Complex Neural Architecture. Neuron [Internet]. 2003 Dec;40(5):885–95. Available from: https://linkinghub.elsevier.com/retrieve/pii/S089662730300758X doi: 10.1016/s0896-6273(03)00758-x 14659088
26. Kindlmann G. Superquadric Tensor Glyphs. In: Joint Eurographics—IEEE TCVG Symposium on Visualization [Internet]. Eurographics Association; 2004. p. 147–54. Available from: http://dx.doi.org/10.2312/VisSym/VisSym04/147-154
27. Höller M, Ehricke H-H, Synofzik M, Klose U, Groeschel S. Clinical Application of Fiber Visualization with LIC Maps Using Multidirectional Anisotropic Glyph Samples (A-Glyph LIC). Clin Neuroradiol [Internet]. 2017 Sep 27;27(3):263–73. Available from: http://link.springer.com/10.1007/s00062-015-0486-8 26614208
28. Cabral B, Leedom LC. Imaging vector fields using line integral convolution. In: Proceedings of the 20th annual conference on Computer graphics and interactive techniques—SIGGRAPH ‘93 [Internet]. New York, New York, USA: ACM Press; 1993. p. 263–70. Available from: http://portal.acm.org/citation.cfm?doid=166117.166151
29. Höller M, Otto K-M, Klose U, Groeschel S, Ehricke H-H. Fiber Visualization with LIC Maps Using Multidirectional Anisotropic Glyph Samples. Int J Biomed Imaging [Internet]. 2014;2014:1–14. Available from: http://www.ncbi.nlm.nih.gov/pubmed/25254038
30. Smith SM. Fast robust automated brain extraction. Hum Brain Mapp [Internet]. 2002 Nov;17(3):143–55. Available from: doi: 10.1002/hbm.10062 12391568
31. Jenkinson M, Beckmann CF, Behrens TEJ, Woolrich MW, Smith SM. FSL. Neuroimage [Internet]. 2012 Aug;62(2):782–90. Available from: https://linkinghub.elsevier.com/retrieve/pii/S1053811911010603 doi: 10.1016/j.neuroimage.2011.09.015 21979382
32. Andersson JLR, Sotiropoulos SN. An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. Neuroimage [Internet]. 2016 Jan;125:1063–78. Available from: https://linkinghub.elsevier.com/retrieve/pii/S1053811915009209 doi: 10.1016/j.neuroimage.2015.10.019 26481672
33. Jones DK, Basser PJ. “Squashing peanuts and smashing pumpkins”: How noise distorts diffusion-weighted MR data. Magn Reson Med [Internet]. 2004 Nov;52(5):979–93. Available from: doi: 10.1002/mrm.20283 15508154
34. Manjón J V., Coupé P, Concha L, Buades A, Collins DL, Robles M. Diffusion Weighted Image Denoising Using Overcomplete Local PCA. Gong G, editor. PLoS One [Internet]. 2013 Sep 3;8(9):e73021. Available from: doi: 10.1371/journal.pone.0073021 24019889
35. Manjón J V. OLPCA [Internet]. 2019. Available from: https://sites.google.com/site/pierrickcoupe/softwares/denoising-for-medical-imaging/dwi-denoising/dwi-denoising-software
36. Hess CP, Mukherjee P, Han ET, Xu D, Vigneron DB. Q-ball reconstruction of multimodal fiber orientations using the spherical harmonic basis. Magn Reson Med [Internet]. 2006 Jul;56(1):104–17. Available from: doi: 10.1002/mrm.20931 16755539
37. Aganj I, Lenglet C, Sapiro G. ODF reconstruction in q-ball imaging with solid angle consideration. In: 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro [Internet]. IEEE; 2009. p. 1398–401. Available from: http://ieeexplore.ieee.org/document/5193327/
38. Kamath A, Aganj I, Xu J, Yacoub E, Ugurbil K, Sapiro G, et al. Generalized Constant Solid Angle ODF and Optimal Acquisition Protocol for Fiber Orientation Mapping. In: Proceedings of the MICCAI Workshop on Computational Diffusion MRI. Nice, France; 2012. p. 67–78.
39. Aganj I. CSA-ODF Matlab implementation [Internet]. 2018. Available from: https://de.mathworks.com/matlabcentral/fileexchange/62516-orientation-distribution-function-in-constant-solid-angle—csa-odf—and-hough-transform-tractography?s_tid=prof_contriblnk
40. Tuch DS, Reese TG, Wiegell MR, Makris N, Belliveau JW, Van Wedeen J. High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity. Magn Reson Med. 2002;48(4):577–82. doi: 10.1002/mrm.10268 12353272
41. IACS—Institute for Applied Computer Science. fiberViewMR [Internet]. 2018. Available from: https://www.hochschule-stralsund.de/forschung-und-transfer/institute/institute-for-applied-computer-science/health-informatics/
42. Tournier J-D, Calamante F, Connelly A. MRtrix: Diffusion tractography in crossing fiber regions. Int J Imaging Syst Technol [Internet]. 2012 Mar;22(1):53–66. Available from: http://doi.wiley.com/10.1002/ima.22005
43. Qi S, Meesters S, Nicolay K, ter Haar Romeny BM, Ossenblok P. Structural Brain Network: What is the Effect of LiFE Optimization of Whole Brain Tractography? Front Comput Neurosci [Internet]. 2016 Feb 16;10(12). Available from: http://journal.frontiersin.org/Article/10.3389/fncom.2016.00012/abstract
44. Mori S, Crain BJ, Chacko VP, Van Zijl PCM. Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Ann Neurol [Internet]. 1999 Feb;45(2):265–9. Available from: http://www.ncbi.nlm.nih.gov/pubmed/9989633 doi: 10.1002/1531-8249(199902)45:2<265::aid-ana21>3.0.co;2-3 9989633
45. Calamante F, Tournier J-D, Heidemann RM, Anwander A, Jackson GD, Connelly A. Track density imaging (TDI): Validation of super resolution property. Neuroimage [Internet]. 2011 Jun;56(3):1259–66. Available from: https://linkinghub.elsevier.com/retrieve/pii/S1053811911002151 doi: 10.1016/j.neuroimage.2011.02.059 21354314
46. 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 [Internet]. 2007 Jul;36(3):630–44. Available from: https://linkinghub.elsevier.com/retrieve/pii/S1053811907001383 doi: 10.1016/j.neuroimage.2007.02.049 17481925
47. Maier-Hein KH, Neher PF, Houde J-C, Côté M-A, Garyfallidis E, Zhong J, et al. The challenge of mapping the human connectome based on diffusion tractography. Nat Commun [Internet]. 2017 Dec 7;8(1):1349. Available from: http://www.nature.com/articles/s41467-017-01285-x doi: 10.1038/s41467-017-01285-x 29116093
48. Ohue S, Kohno S, Inoue A, Yamashita D, Harada H, Kumon Y, et al. Accuracy of Diffusion Tensor Magnetic Resonance Imaging-Based Tractography for Surgery of Gliomas Near the Pyramidal Tract. Neurosurgery [Internet]. 2012 Feb;70(2):283–93. Available from: https://academic.oup.com/neurosurgery/article-lookup/doi/10.1227/NEU.0b013e31823020e6 21811189
49. Nimsky C, Ganslandt O, Hastreiter P, Wang R, Benner T, Sorensen AG, et al. Preoperative and Intraoperative Diffusion Tensor Imaging-based Fiber Tracking in Glioma Surgery. Neurosurgery [Internet]. 2005 Jan;56(1):130–8. Available from: https://academic.oup.com/neurosurgery/article-lookup/doi/10.1227/01.NEU.0000144842.18771.30 15617595
50. Nimsky C, Ganslandt O, Hastreiter P, Wang R, Benner T, Sorensen a G, et al. Intraoperative Diffusion-Tensor MR Imaging: Shifting of White Matter Tracts during Neurosurgical Procedures—Initial Experience. Radiology [Internet]. 2005 Jan;234(1):218–25. Available from: http://pubs.rsna.org/doi/10.1148/radiol.2341031984 15564394
51. Golby AJ, Kindlmann G, Norton I, Yarmarkovich A, Pieper S, Kikinis R. Interactive Diffusion Tensor Tractography Visualization for Neurosurgical Planning. Neurosurgery [Internet]. 2011 Feb 1;68(2):496–505. Available from: https://academic.oup.com/neurosurgery/article/68/2/496/2606344 doi: 10.1227/NEU.0b013e3182061ebb 21135713
52. Castellano A, Cirillo S, Bello L, Riva M, Falini A. Functional MRI for Surgery of Gliomas. Curr Treat Options Neurol [Internet]. 2017 Oct 23;19(10):34. Available from: http://link.springer.com/10.1007/s11940-017-0469-y 28831723
53. Feng L, Hotz I, Hamann B, Joy KI. Anisotropic Noise Samples. IEEE Trans Vis Comput Graph [Internet]. 2008 Mar;14(2):342–54. Available from: http://ieeexplore.ieee.org/document/4359502/ doi: 10.1109/TVCG.2007.70434 18192714
54. Kindlmann G, Westin C. Diffusion Tensor Visualization with Glyph Packing. IEEE Trans Vis Comput Graph [Internet]. 2006 Sep;12(5):1329–36. Available from: http://ieeexplore.ieee.org/document/4015499/ doi: 10.1109/tvcg.2006.134 17080869
55. Chen W, Zhang S, Correia S, Tate DF. Visualizing diffusion tensor imaging data with merging ellipsoids. In: 2009 IEEE Pacific Visualization Symposium [Internet]. IEEE; 2009. p. 145–51. Available from: http://ieeexplore.ieee.org/document/4906849/
56. Tax CMW, Chamberland M, van Stralen M, Viergever MA, Whittingstall K, Fortin D, et al. Seeing More by Showing Less: Orientation-Dependent Transparency Rendering for Fiber Tractography Visualization. Hodaie M, editor. PLoS One [Internet]. 2015 Oct 7;10(10):e0139434. Available from: https://dx.plos.org/10.1371/journal.pone.0139434 26444010
Článok vyšiel v časopise
PLOS One
2019 Číslo 12
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
- Nejasný stín na plicích – kazuistika
- Masturbační chování žen v ČR − dotazníková studie
- Těžké menstruační krvácení může značit poruchu krevní srážlivosti. Jaký management vyšetření a léčby je v takovém případě vhodný?
- Fixní kombinace paracetamol/kodein nabízí synergické analgetické účinky
Najčítanejšie v tomto čísle
- Methylsulfonylmethane increases osteogenesis and regulates the mineralization of the matrix by transglutaminase 2 in SHED cells
- Oregano powder reduces Streptococcus and increases SCFA concentration in a mixed bacterial culture assay
- The characteristic of patulous eustachian tube patients diagnosed by the JOS diagnostic criteria
- Parametric CAD modeling for open source scientific hardware: Comparing OpenSCAD and FreeCAD Python scripts