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Assessment of Tissue Injury in Severe Brain Trauma

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9556))

Abstract

We report our methodological developments to investigate, in a multi-center study using mean diffusivity, the tissue damage caused by a severe traumatic brain injury (GSC \(<9\)) in the 10 days post-event. To assess the diffuse aspect of the injury, we fuse several atlases to parcel cortical, subcortical and WM structures into well identified regions where MD values are computed and compared to normative values. We used P-LOCUS to provide brain tissue segmentation and exclude voxels labeled as CSF, ventricles and hemorrhagic lesion and then automatically detect the lesion load. Preliminary results demonstrate that our method is coherent with expert opinion in the identification of lesions. We outline the challenges posed in automatic analysis for TBI.

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Notes

  1. 1.

    http://www.fmrib.ox.ac.uk/fsl/.

  2. 2.

    http://www.neuromorphometrics.com/.

  3. 3.

    http://www.fil.ion.ucl.ac.uk/spm/software/spm12/.

  4. 4.

    http://www.mccauslandcenter.sc.edu/mricro/mricron/.

  5. 5.

    Between 2004–2014, more than 500 papers were published on lesion segmentation for each of these pathologies and only 53 for TBI. Source WebOfScience with keywords: Brain and MRI and (Segmentation or Classification) and ‘Pathology’.

References

  1. Spiotta, A.M., Stiefel, M.F., Gracias, V.H., et al.: Brain tissue oxygen-directed management and outcome in patients with severe traumatic brain injury. J. Neurosurg. 113(3), 571–580 (2010)

    Article  Google Scholar 

  2. Green, J.A., Pellegrini, D.C., Vanderkolk, W.E., et al.: Goal directed brain tissue oxygen monitoring versus conventional management in traumatic brain injury: an analysis of in hospital recovery. Neurocrit. Care 18(1), 20–25 (2013)

    Article  Google Scholar 

  3. Davenport, N.D., Lim, K.O., Armstrong, M.T., Sponheim, S.R.: Diffuse and spatially variable white matter disruptions are associated with blast-related mild traumatic brain injury. Neuroimage 59(3), 2017–2024 (2012)

    Article  Google Scholar 

  4. Narayana, P.A., Yu, X., Hasan, K.M., et al.: Multi-modal mri of mild traumatic brain injury. Neuroimage Clin. 7, 87–97 (2015)

    Article  Google Scholar 

  5. Yuh, E.L., Mukherjee, P., Lingsma, H.F., et al.: Magnetic resonance imaging improves 3-month outcome prediction in mild traumatic brain injury. Ann. Neurol. 73(2), 224–235 (2013)

    Article  Google Scholar 

  6. Galanaud, D., Perlbarg, V., Gupta, R., et al.: Assessment of white matter injury and outcome in severe brain trauma: a prospective multicenter cohort. Anesthesiology 117(6), 1300–1310 (2012)

    Article  Google Scholar 

  7. Cunningham, A.S., Salvador, R., Coles, J.P., et al.: Physiological thresholds for irreversible tissue damage in contusional regions following traumatic brain injury. Brain 128(Pt 8), 1931–1942 (2005)

    Article  Google Scholar 

  8. Shenton, M.E., Hamoda, H.M., Schneiderman, J.S., et al.: A review of magnetic resonance imaging and diffusion tensor imaging findings in mild traumatic brain injury. Brain Imaging Behav. 6(2), 137–192 (2012)

    Article  Google Scholar 

  9. Bigler, E.D., Wilde, E.A.: Quantitative neuroimaging and the prediction of rehabilitation outcome following traumatic brain injury. Front. Hum. Neurosci. 4, 228 (2010)

    Article  Google Scholar 

  10. Kasahara, K., Hashimoto, K., Abo, M., Senoo, A.: Voxel- and atlas-based analysis of diffusion tensor imaging may reveal focal axonal injuries in mild traumatic brain injury - comparison with diffuse axonal injury. Magn. Reson. Imaging 30(4), 496–505 (2012)

    Article  Google Scholar 

  11. Newcombe, V.F., Correia, M.M., Ledig, C., et al.: Dynamic changes in white matter abnormalities correlate with late improvement and deterioration following tbi: a diffusion tensor imaging study. Neurorehabil. Neural Repair 30(1), 49–62 (2016)

    Article  Google Scholar 

  12. Sidaros, A., Skimminge, A., Liptrot, M.G., et al.: Long-term global and regional brain volume changes following severe traumatic brain injury: a longitudinal study with clinical correlates. Neuroimage 44(1), 1–8 (2009)

    Article  Google Scholar 

  13. Strangman, G.E., O’Neil-Pirozzi, T.M., Supelana, C., et al.: Regional brain morphometry predicts memory rehabilitation outcome after traumatic brain injury. Front. Hum. Neurosci. 4, 182 (2010)

    Article  Google Scholar 

  14. Pasco, A., Ter Minassian, A., Chapon, C., et al.: Dynamics of cerebral edema and the apparent diffusion coefficient of water changes in patients with severe traumatic brain injury. a prospective mri study. Eur. Radiol. 16(7), 1501–1508 (2006)

    Article  Google Scholar 

  15. Irimia, A., Chambers, M.C., Alger, J.R., et al.: Comparison of acute and chronic traumatic brain injury using semi-automatic multimodal segmentation of mr volumes. J. Neurotrauma 28(11), 2287–2306 (2011)

    Article  Google Scholar 

  16. Hasan, K.M., Wilde, E.A., Miller, E.R., et al.: Serial atlas-based diffusion tensor imaging study of uncomplicated mild traumatic brain injury in adults. J. Neurotrauma 31(5), 466–475 (2014)

    Article  Google Scholar 

  17. Ledig, C., Heckemann, R.A., Hammers, A., et al.: Robust whole-brain segmentation: application to traumatic brain injury. Med. Image Anal. 21(1), 40–58 (2015)

    Article  Google Scholar 

  18. Doyle, S., Forbes, F., Dojat, M.: P-locus, a complete suite for brain scan segmentation. In: 9h IEEE International Symposium on Biomedical Imaging (ISBI) (2012)

    Google Scholar 

  19. Manjon, J.V., Coupe, P., Concha, L., Buades, A., Collins, D.L., Robles, M.: Diffusion weighted image denoising using overcomplete local pca. PLOS One 8(9), e73021 (2013)

    Article  Google Scholar 

  20. Forbes, F., Doyle, S., Garcia-Lorenzo, D., Barillot, C., Dojat, M.: A weighted Multi-sequence Markov model for brain lesion segmentation. In: The Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS), pp. 225–232 (2010)

    Google Scholar 

  21. Warfield, S.K., Zou, K.H., Wells, W.M.: Validation of image segmentation by estimating rater bias and variance. Philos. Trans. A Math. Phys. Eng. Sci. 366(1874), 2361–2375 (2008)

    Article  Google Scholar 

  22. Kim, N., Branch, C.A., Kim, M., Lipton, M.L.: Whole brain approaches for identification of microstructural abnormalities in individual patients: comparison of techniques applied to mild traumatic brain injury. PLoS One 8(3), e59382 (2013)

    Article  Google Scholar 

  23. Mirzaalian, H., de Pierrefeu, A., Savadjiev, P., Pasternak, S., Bouix, S., Kubicki, M., Westin, C., Shenton, M., Rathi, Y.: Harmonizing diffusion mri data across multiple sites and scanners. Med. Image Comput. Comput. Assist. Interv. 18(Pt 2), 12–19 (2015)

    Google Scholar 

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Acknowledgments

Grenoble MRI facility IRMaGe was partly funded by the French program Investissement d\(^{\prime }\) avenir run by the Agence Nationale pour la Recherche; grant Infrastructure d\(^{\prime }\) avenir en Biologie Santé - ANR-11-INBS-0006. Research funded by French ministry of research and education under the Projet Hospitalier de Recherche Clinique grant OXY-TC to JFP.

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Correspondence to Michel Dojat .

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Maggia, C. et al. (2016). Assessment of Tissue Injury in Severe Brain Trauma. In: Crimi, A., Menze, B., Maier, O., Reyes, M., Handels, H. (eds) Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2015. Lecture Notes in Computer Science(), vol 9556. Springer, Cham. https://doi.org/10.1007/978-3-319-30858-6_6

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  • DOI: https://doi.org/10.1007/978-3-319-30858-6_6

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30857-9

  • Online ISBN: 978-3-319-30858-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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