Magnetic resonance tractography based on the constrained spherical deconvolution in patients with gliomas of the optic pathway

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Abstract

Background: The use of magnetic resonance (MR) tractography in neurosurgery is becoming an increasingly common practice for noninvasive imaging of white matter pathways. The most common method of tract reconstruction is the deterministic algorithm of diffusion tensor magnetic resonance imaging (MRI). However, this method of reconstructing pathways has a  number of significant limitations. The most important of them are the lack of the possibility of visualizing the intersecting fibers, the complexity of building tracts in the area of perifocal edema and in the immediate vicinity of the tumor borders. The method of MR tractography, based on obtaining a  diffusion image with a  high angular resolution (High Angular Resolution Diffusion Imaging, HARDI), using the constrained spherical deconvolution (CSD) algorithm for post-processing of data, makes it possible to avoid these disadvantages. Relatively recently, a new algorithm, Single-Shell 3-Tissue CSD (SS3TCSD), has been proposed for processing HARDI data, which has the potential to improve the reconstructing of pathways in the area of perifocal edema or edema-infiltration.

Aim: To evaluate the potential of the new SS3TCSD algorithm compared to ST-CSD (Single-Tissue CSD) in the imaging of the optic radiation and visual tracts in patients with gliomas.

Materials and methods: Diffusion and routine brain MRI was performed in 10 patients with newly diagnosed cerebral gliomas, followed by reconstruction of the optic radiation and visual tracts. We compared new algorithms for postprocessing MR tractography (ST-CSD and SS3TCSD) in imaging of the optic tract and visual radiation in patients with brain gliomas affecting various parts of the visual system.

Results: The SS3T-CSD method showed a  lower mean percentage of false positive tracts compared to the ST-CSD method: 19.75% for the SS3T-CSD method and 80.32% for the ST-CSD method in cases of proximity of the tumor to the tracts, 5.27% for the SS3T-CSD method and 25.27% for the STCSD method in cases of reconstructing tracts in healthy white matter.

Conclusion: The SS3T-CSD method has a number of advantages over ST-CSD and allows for successful imaging of the optic pathways that have a complex structure and repeatedly change direction along their course.

About the authors

A. A. Baev

N.N. Burdenko National Medical Research Center of Neurosurgery

Author for correspondence.
Email: abaev@nsi.ru
ORCID iD: 0000-0003-4908-0534

Alexander A. Baev – Radiologist, Department of Neuroradiology and Radioisotope Diagnostic Imaging

16 4-ya Tverskaya-Yamskaya ul., Moscow, 125047

Russian Federation

E. L. Pogosbekian

N.N. Burdenko National Medical Research Center of Neurosurgery

Email: epogosbekyan@nsi.ru
ORCID iD: 0000-0002-4803-6948

Eduard L. Pogosbekian – Medical Physicist, Department of Neuroradiology and Radioisotope Diagnostic Imaging

16 4-ya Tverskaya-Yamskaya ul., Moscow, 125047

Russian Federation

N. E. Zakharova

N.N. Burdenko National Medical Research Center of Neurosurgery

Email: nzakharova@nsi.ru
ORCID iD: 0000-0002-0516-3613

Natalia E. Zakharova – MD, PhD, Professor of Russ. Acad. Sci., Leading Research Fellow, Department of Neuroradiology and Radioisotope Diagnostic Imaging

16 4-ya Tverskaya-Yamskaya ul., Moscow, 125047

Russian Federation

D. I. Pitskhelauri

N.N. Burdenko National Medical Research Center of Neurosurgery

Email: dav@nsi.ru
ORCID iD: 0000-0003-0374-7970

David I. Pitskhelauri – MD, PhD, Leading Research Fellow, Head of Neurosurgical Department

16 4-ya Tverskaya-Yamskaya ul., Moscow, 125047

Russian Federation

A. I. Batalov

N.N. Burdenko National Medical Research Center of Neurosurgery

Email: abatalov@nsi.ru
ORCID iD: 0000-0002-8924-7346

Artem I. Batalov – MD, PhD, Junior Research Fellow, Department of Neuroradiology and Radioisotope Diagnostic Imaging

16 4-ya Tverskaya-Yamskaya ul., Moscow, 125047

Russian Federation

A. M. Shkatova

N.N. Burdenko National Medical Research Center of Neurosurgery

Email: shkatova.a.m.v@gmail.com
ORCID iD: 0000-0003-4957-4286

Anastasia M. Shkatova – Neurosurgeon, Neurosurgical Department

16 4-ya Tverskaya-Yamskaya ul., Moscow, 125047

Russian Federation

E. I. Shults

N.N. Burdenko National Medical Research Center of Neurosurgery

Email: evgshults@gmail.com
ORCID iD: 0000-0001-5406-944X

Evgeny I. Shults – MD, PhD, Radiologist, Department of Neuroradiology and Radioisotope Diagnostic Imaging

16 4-ya Tverskaya-Yamskaya ul., Moscow, 125047

Russian Federation

A. E. Bykanov

N.N. Burdenko National Medical Research Center of Neurosurgery

Email: abykanov7@gmail.ru
ORCID iD: 0000-0002-0588-4779

Andrey E. Bykanov – MD, PhD, Neurosurgeon, Neurosurgical Department

16 4-ya Tverskaya-Yamskaya ul., Moscow, 125047

Russian Federation

S. A. Maryashev

N.N. Burdenko National Medical Research Center of Neurosurgery

Email: smaryashev@gmail.com
ORCID iD: 0000-0002-0108-0677

Sergey A. Maryashev – MD, PhD, Neurosurgeon, Neurosurgical Department

16 4-ya Tverskaya-Yamskaya ul., Moscow, 125047

Russian Federation

T. A. Konakova

N.N. Burdenko National Medical Research Center of Neurosurgery

Email: tknsipet@gmail.com
ORCID iD: 0000-0002-2505-7981

Tatiana A. Konakova – Postgraduate Student, Department of Neuroradiology and Radioisotope Diagnostic Imaging

16 4-ya Tverskaya-Yamskaya ul., Moscow, 125047

Russian Federation

I. N. Pronin

N.N. Burdenko National Medical Research Center of Neurosurgery

Email: pronin@nsi.ru
ORCID iD: 0000-0002-4480-0275

Igor N. Pronin – MD, PhD, Professor, Member of Russ. Acad. Sci., Head of Department of Neuroradiology and Radioisotope Diagnostic Imaging

16 4-ya Tverskaya-Yamskaya ul., Moscow, 125047

Russian Federation

References

  1. Тоноян АС, Агеев ИС, Овчаренко ТА, Захарова НЕ, Александрова ЕВ, Горяйнов СА, Быканов АЕ, Шурхай ВА, Шульц ЕИ, Пронин ИН. Новые возможности магнитно-резонансной трактографии в нейрорадиологии: модель HARDI-CSD. Вестник Российского фонда фундаментальных исследований. 2016;2(90): 20–32. doi: 10.22204/2410-4639-2016-090-02-20-32.
  2. Ramnani N, Miall RC. A system in the human brain for predicting the actions of others. Nat Neurosci. 2004;7(1):85–90. doi: 10.1038/nn1168.
  3. Hofer S, Frahm J. Topography of the human corpus callosum revisited – comprehensive fiber tractography using diffusion tensor magnetic resonance imaging. Neuroimage. 2006;32(3):989–994. doi: 10.1016/j.neuroimage.2006.05.044.
  4. Jones DK, Knösche TR, Turner R. White matter integrity, fiber count, and other fallacies: the do's and don'ts of diffusion MRI. Neuroimage. 2013;73:239–254. doi: 10.1016/j.neuroimage.2012.06.081.
  5. Farquharson S, Tournier JD, Calamante F, Fabinyi G, Schneider-Kolsky M, Jackson GD, Connelly A. White matter fiber tractography: why we need to move beyond DTI. J Neurosurg. 2013;118(6):1367–1377. doi: 10.3171/2013.2.JNS121294.
  6. Jeurissen B, Leemans A, Tournier JD, Jones DK, Sijbers J. Investigating the prevalence of complex fiber configurations in white matter tissue with diffusion magnetic resonance imaging. Hum Brain Mapp. 2013;34(11):2747–2766. doi: 10.1002/hbm.22099.
  7. Kramm CM, Wagner S, Van Gool S, Schmid H, Sträter R, Gnekow A, Rutkowski S, Wolff JE. Improved survival after gross total resection of malignant gliomas in pediatric patients from the HIT-GBM studies. Anticancer Res. 2006;26(5B):3773–3779.
  8. Tuch DS, Reese TG, Wiegell MR, Makris N, Belliveau JW, Wedeen VJ. High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity. Magn Reson Med. 2002;48(4):577–582. doi: 10.1002/mrm.10268.
  9. Tournier JD, Calamante F, Connelly A. Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution. Neuroimage. 2007;35(4):1459–1472. doi: 10.1016/j.neuroimage.2007.02.016.
  10. Jeurissen B, Tournier JD, Dhollander T, Connelly A, Sijbers J. Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data. Neuroimage. 2014;103:411–426. doi: 10.1016/j.neuroimage.2014.07.061.
  11. Veraart J, Novikov DS, Christiaens D, AdesAron B, Sijbers J, Fieremans E. Denoising of diffusion MRI using random matrix theory. Neuroimage. 2016;142:394–406. doi: 10.1016/j.neuroimage.2016.08.016.
  12. Tournier JD, Calamante F, Connelly A. Determination of the appropriate b value and number of gradient directions for high-angular-resolution diffusion-weighted imaging. NMR Biomed. 2013;26(12):1775–1786. doi: 10.1002/nbm.3017.
  13. Dhollander T, Connelly A. A novel iterative approach to reap the benefits of multi-tissue CSD from just single-shell (+ b=0) diffusion MRI data. Proc. Intl. Soc. Mag. Reson. Med. 24. 2016; 3010.
  14. Binder DK, Sonne DC, Fischbein NJ. Cranial nerves: anatomy, pathology, imaging. New York: Thieme; 2010. 248 p.
  15. Rubino PA, Rhoton AL Jr, Tong X, de Oliveira E. Three-dimensional relationships of the optic radiation. Neurosurgery. 2005;57(4 Suppl):219–227; discussion 219–227. doi: 10.1227/01.neu.0000176415.83417.16.
  16. Meyer A. The connections of the occipital lobes and the present status of the cerebral visual affections. Transactions Association of the American Physicians. 1907;(22):7–23.
  17. Sincoff EH, Tan Y, Abdulrauf SI. White matter fiber dissection of the optic radiations of the temporal lobe and implications for surgical approaches to the temporal horn. J Neurosurg. 2004;101(5):739–746. doi: 10.3171/jns.2004.101.5.0739.
  18. Türe U, Yaşargil MG, Friedman AH, Al-Mefty O. Fiber dissection technique: lateral aspect of the brain. Neurosurgery. 2000;47(2):417–426; discussion 426–427. doi: 10.1097/00006123-200008000-00028.
  19. Ebeling U, Reulen HJ. Neurosurgical topography of the optic radiation in the temporal lobe. Acta Neurochir (Wien). 1988;92(1–4):29–36. doi: 10.1007/BF01401969.
  20. Quinones-Hinojosa A, Raza SM, Ahmed I, Rincon-Torroella J, Chaichana K, Olivi A. Middle Temporal Gyrus Versus Inferior Temporal Gyrus Transcortical Approaches to High-Grade Astrocytomas in the Mediobasal Temporal Lobe: A Comparison of Outcomes, Functional Restoration, and Surgical Considerations. Acta Neurochir Suppl. 2017;124:159–164. doi: 10.1007/978-3-319-39546-3_25.
  21. Dhollander T, Raffelt D, Connelly A. Unsupervised 3-tissue response function estimation from single-shell or multi-shell diffusion MR data without a co-registered T1 image [Internet]. ResearchGate. 2016. Available from: https://www.researchgate.net/publication/307863133_Unsupervised_3-tissue_response_function_estimation_from_single-shell_or_multi-shell_diffusion_MR_data_without_a_co-registered_T1_image.

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Copyright (c) 2021 Baev A.A., Pogosbekian E.L., Zakharova N.E., Pitskhelauri D.I., Batalov A.I., Shkatova A.M., Shults E.I., Bykanov A.E., Maryashev S.A., Konakova T.A., Pronin I.N.

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