Skip to main content

Advertisement

Log in

Fractal dimension brain morphometry: a novel approach to quantify white matter in traumatic brain injury

  • Original Research
  • Published:
Brain Imaging and Behavior Aims and scope Submit manuscript

A Correction to this article was published on 03 November 2020

This article has been updated

Abstract

Traumatic brain injury (TBI) is the main cause of disability in people younger than 35 in the United States. The mechanisms of TBI are complex resulting in both focal and diffuse brain damage. Fractal dimension (FD) is a measure that can characterize morphometric complexity and variability of brain structure especially white matter (WM) structure and may provide novel insights into the injuries evident following TBI. FD-based brain morphometry may provide information on WM structural changes after TBI that is more sensitive to subtle structural changes post injury compared to conventional MRI measurements. Anatomical and diffusion tensor imaging (DTI) data were obtained using a 3 T MRI scanner in subjects with moderate to severe TBI and in healthy controls (HC). Whole brain WM volume, grey matter volume, cortical thickness, cortical area, FD and DTI metrics were evaluated globally and for the left and right hemispheres separately. A neuropsychological test battery sensitive to cognitive impairment associated with traumatic brain injury was performed. TBI group showed lower structural complexity (FD) bilaterally (p < 0.05). No significant difference in either grey matter volume, cortical thickness or cortical area was observed in any of the brain regions between TBI and healthy controls. No significant differences in whole brain WM volume or DTI metrics between TBI and HC groups were observed. Behavioral data analysis revealed that WM FD accounted for a significant amount of variance in executive functioning and processing speed beyond demographic and DTI variables. FD therefore, may serve as a sensitive marker of injury and may play a role in outcome prediction in TBI.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Change history

  • 03 November 2020

    The original published version of this article contained mistakes. The author noticed that figure captions/legends got mismatched with the figures.

Abbreviations

BET:

Brain Extraction Tool

DTI:

Diffusion Tensor Imaging

FAST:

FMRIB’s Automated Segmentation Tool

FD:

Fractal Dimension

FLIRT:

FMRIB’s Linear Image Registration Tool

FMRIB:

Functional Magnetic Resonance Imaging of Brain

FNIRT:

FMRIB’s Nonlinear Image Registration Tool

FSL:

Functional MRI of the brain Software Libraries

FWER:

Family-Wise Error Rate

FWHM:

Full-Width Half-Maximum

GLM:

general linear model

GM:

grey matter

MPRAGE:

magnetization prepared rapid gradient echo

MRI:

magnetic resonance imaging

SPM:

statistical parametric mapping

TBI:

Traumatic Brain Injury

VBM:

voxel based morphometry

WM:

white matter

References

  • Adams, J. H., Doyle, D., Ford, I., Gennarelli, T. A., Graham, D. I., & McLellan, D. R. (1989). Diffuse axonal injury in head injury: Definition, diagnosis and grading. [comparative study]. Histopathology, 15(1), 49–59.

    Article  CAS  PubMed  Google Scholar 

  • Bazarian, J. J., Veazie, P., Mookerjee, S., & Lerner, E. B. (2006). Accuracy of mild traumatic brain injury case ascertainment using ICD-9 codes. [Comparative Study Evaluation Studies Research Support, N.I.H., Extramural. Validation Studies]. Academic emergency medicine : official journal of the Society for Academic Emergency Medicine, 13(1), 31–38. https://doi.org/10.1197/j.aem.2005.07.038.

    Article  Google Scholar 

  • Bigler, E. D. (2004). Neuropsychological results and neuropathological findings at autopsy in a case of mild traumatic brain injury. Journal of the International Neuropsychological Society, 10(5), 794–806. https://doi.org/10.1017/S1355617704105146.

    Article  PubMed  Google Scholar 

  • Bigler, E. D. (2015). Structural image analysis of the brain in neuropsychology using magnetic resonance imaging (MRI) techniques. Neuropsychology Review, 25(3), 224–249. https://doi.org/10.1007/s11065-015-9290-0.

    Article  PubMed  Google Scholar 

  • Bolzenius, J. D., B, W., Velez, C. S., Drennon, A. M., Cooper, D. B., Kennedy, J. E., Reid, M. W., Bowles, A. O., Thompson, P. M., Gutman, B., Lewis, J. D., Ritter, J. L., York, G. E., Bigler, E. D., & Tate, D. F. (2018). Relationships between subcortical shape measures and subjective symptom reporting in US Service members with mild traumatic brain injury. J Head Trauma Rehabil, Mar/Apr, 33(2), 113–122.

    Article  Google Scholar 

  • Bullmore, E., Brammer, M., Harvey, I., Persaud, R., Murray, R., & Ron, M. (1994). Fractal analysis of the boundary between white matter and cerebral cortex in magnetic resonance images: A controlled study of schizophrenic and manic-depressive patients. [Research Support, Non-U.S. Gov't]. Psychological Medicine, 24(3), 771–781.

    Article  CAS  PubMed  Google Scholar 

  • Chelly, H., Chaari, A., Daoud, E., Dammak, H., Medhioub, F., Mnif, J., et al. (2011). Diffuse axonal injury in patients with head injuries: An epidemiologic and prognosis study of 124 cases. The Journal of Trauma, 71(4), 838–846. https://doi.org/10.1097/TA.0b013e3182127baa.

    Article  PubMed  Google Scholar 

  • Cloots, R. J., Gervaise, H. M., van Dommelen, J. A., & Geers, M. G. (2008). Biomechanics of traumatic brain injury: Influences of the morphologic heterogeneities of the cerebral cortex. [research support, non-U.S. Gov't]. Annals of Biomedical Engineering, 36(7), 1203–1215, doi:https://doi.org/10.1007/s10439-008-9510-3.

  • Dale, A. M., Fischl, B., & Sereno, M. I. (1999). Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage, 9(2), 179–194. https://doi.org/10.1006/nimg.1998.0395.

    Article  CAS  PubMed  Google Scholar 

  • Delis, D. C., Kaplan, E., & Kramer, J. H. (2001). Delis-Kaplan executive function system (D-KEFS). San Antonio: Psychological Corporation.

    Google Scholar 

  • Desikan, R. S., Segonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., et al. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage, 31(3), 968–980. https://doi.org/10.1016/j.neuroimage.2006.01.021.

    Article  PubMed  Google Scholar 

  • Douglas, D. B., Iv, M., Douglas, P. K., Anderson, A., Vos, S. B., Bammer, R., et al. (2015). Diffusion tensor imaging of TBI: Potentials and challenges. Topics in Magnetic Resonance Imaging, 24(5), 241–251. https://doi.org/10.1097/RMR.0000000000000062.

    Article  PubMed  Google Scholar 

  • Esteban, F. J., Sepulcre, J., de Mendizabal, N. V., Goni, J., Navas, J., de Miras, J. R., et al. (2007). Fractal dimension and white matter changes in multiple sclerosis. [Research Support, Non-U.S. Gov't]. NeuroImage, 36(3), 543–549. https://doi.org/10.1016/j.neuroimage.2007.03.057.

    Article  PubMed  Google Scholar 

  • Faul, M., Xu, L., Wald, M. M., & Coronado, V. G. (2010). Traumatic brain injury in the United States. Emergency department visits, hospitalizations and deaths 2002–2006. Atlanta, GA.: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention.

  • Feng, Y., Abney, T. M., Okamoto, R. J., Pless, R. B., Genin, G. M., & Bayly, P. V. (2010). Relative brain displacement and deformation during constrained mild frontal head impact. [Research Support, N.I.H., Extramural]. Journal of the Royal Society, Interface / the Royal Society, 7(53), 1677–1688. https://doi.org/10.1098/rsif.2010.0210.

    Article  CAS  Google Scholar 

  • Finkelstein, E., Corso, P., & Miller, T. (2006). The incidence and economic burden of injuries in the United States. New York: Oxford University Press.

    Book  Google Scholar 

  • Fischl, B., & Dale, A. M. (2000). Measuring the thickness of the human cerebral cortex from magnetic resonance images. [Research Support, U.S. Gov't, P.H.S.]. Proceedings of the National Academy of Sciences of the United States of America, 97(20), 11050–11055. https://doi.org/10.1073/pnas.200033797.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Fischl, B., Liu, A., & Dale, A. M. (2001). Automated manifold surgery: Constructing geometrically accurate and topologically correct models of the human cerebral cortex. IEEE Transactions on Medical Imaging, 20(1), 70–80. https://doi.org/10.1109/42.906426.

    Article  CAS  PubMed  Google Scholar 

  • Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., et al. (2002). Whole brain segmentation: Automated labeling of neuroanatomical structures in the human brain. Neuron, 33(3), 341–355.

    Article  CAS  PubMed  Google Scholar 

  • Fischl, B., Salat, D. H., van der Kouwe, A. J., Makris, N., Segonne, F., Quinn, B. T., et al. (2004). Sequence-independent segmentation of magnetic resonance images. NeuroImage, 23(Suppl 1), S69–S84. https://doi.org/10.1016/j.neuroimage.2004.07.016.

    Article  PubMed  Google Scholar 

  • Gennarelli, T. A., Thibault, L. E., Adams, J. H., Graham, D. I., Thompson, C. J., & Marcincin, R. P. (1982). Diffuse axonal injury and traumatic coma in the primate. [Research Support, U.S. Gov't, P.H.S.]. Annals of Neurology, 12(6), 564–574. https://doi.org/10.1002/ana.410120611.

    Article  CAS  PubMed  Google Scholar 

  • Ghosh, A., Wilde, E. A., Hunter, J. V., Bigler, E. D., Chu, Z., Li, X., et al. (2009). The relation between Glasgow Coma Scale score and later cerebral atrophy in paediatric traumatic brain injury. [Multicenter Study Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't]. Brain injury : [BI], 23(3), 228–233. https://doi.org/10.1080/02699050802672789.

    Article  Google Scholar 

  • Graham DI, G. T. (2000). Pathology of brain damage after head injury. In G. J. Cooper PR (Ed.), Head Injury (pp. 133–153). New York: McGraw-Hill.

    Google Scholar 

  • Huang, M. X., Theilmann, R. J., Robb, A., Angeles, A., Nichols, S., Drake, A., et al. (2009). Integrated imaging approach with MEG and DTI to detect mild traumatic brain injury in military and civilian patients. [Research Support, U.S. Gov't, Non-P.H.S.]. Journal of Neurotrauma, 26(8), 1213–1226. https://doi.org/10.1089/neu.2008.0672.

    Article  CAS  PubMed  Google Scholar 

  • Johnston, K. M., Ptito, A., Chankowsky, J., & Chen, J. K. (2001). New frontiers in diagnostic imaging in concussive head injury. [Research Support, Non-U.S. Gov't Review]. Clinical journal of sport medicine : official journal of the Canadian Academy of Sport Medicine, 11(3), 166–175.

    Article  CAS  Google Scholar 

  • Jovicich, J., Czanner, S., Han, X., Salat, D., van der Kouwe, A., Quinn, B., et al. (2009). MRI-derived measurements of human subcortical, ventricular and intracranial brain volumes: Reliability effects of scan sessions, acquisition sequences, data analyses, scanner upgrade, scanner vendors and field strengths. NeuroImage, 46(1), 177–192. https://doi.org/10.1016/j.neuroimage.2009.02.010.

    Article  PubMed  Google Scholar 

  • Kinnunen, K. M., Greenwood, R., Powell, J. H., Leech, R., Hawkins, P. C., Bonnelle, V., et al. (2011). White matter damage and cognitive impairment after traumatic brain injury. [Research Support, Non-U.S. Gov't]. Brain : a Journal of Neurology, 134(Pt 2), 449–463. https://doi.org/10.1093/brain/awq347.

    Article  Google Scholar 

  • Kirkwood, M. W., Yeates, K. O., & Wilson, P. E. (2006). Pediatric sport-related concussion: A review of the clinical management of an oft-neglected population. [review]. Pediatrics, 117(4), 1359–1371. https://doi.org/10.1542/peds.2005-0994.

    Article  PubMed  Google Scholar 

  • Kraus, M. F., Susmaras, T., Caughlin, B. P., Walker, C. J., Sweeney, J. A., & Little, D. M. (2007). White matter integrity and cognition in chronic traumatic brain injury: A diffusion tensor imaging study. [Research Support, N.I.H., Extramural]. Brain : a journal of neurology, 130(Pt 10), 2508–2519. https://doi.org/10.1093/brain/awm216.

    Article  Google Scholar 

  • Maas, A. I., Stocchetti, N., & Bullock, R. (2008). Moderate and severe traumatic brain injury in adults. [Research Support, N.I.H., Extramural Research Support, U.S. Gov't, Non-P.H.S. Review]. Lancet Neurology, 7(8), 728–741. https://doi.org/10.1016/S1474-4422(08)70164-9.

    Article  PubMed  Google Scholar 

  • Maas, A. I., Roozenbeek, B., & Manley, G. T. (2010). Clinical trials in traumatic brain injury: Past experience and current developments. [Review]. Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics, 7(1), 115–126. https://doi.org/10.1016/j.nurt.2009.10.022.

    Article  Google Scholar 

  • Mandelbrot, B. B. (1982). The fractal geometry of nature. New York, NY: Freeman.

    Google Scholar 

  • Medina, D., DeToledo-Morrell, L., Urresta, F., Gabrieli, J. D., Moseley, M., Fleischman, D., et al. (2006). White matter changes in mild cognitive impairment and AD: A diffusion tensor imaging study. Neurobiology of Aging, 27(5), 663–672. https://doi.org/10.1016/j.neurobiolaging.2005.03.026.

    Article  PubMed  Google Scholar 

  • Mustafa, N., Ahearn, T. S., Waiter, G. D., Murray, A. D., Whalley, L. J., & Staff, R. T. (2012). Brain structural complexity and life course cognitive change. [Research Support, Non-U.S. Gov't]. NeuroImage, 61(3), 694–701. https://doi.org/10.1016/j.neuroimage.2012.03.088.

    Article  PubMed  Google Scholar 

  • Powell, J. M., Ferraro, J. V., Dikmen, S. S., Temkin, N. R., & Bell, K. R. (2008). Accuracy of mild traumatic brain injury diagnosis. [research support, U.S. Gov't, P.H.S.]. Archives of Physical Medicine and Rehabilitation, 89(8), 1550–1555. https://doi.org/10.1016/j.apmr.2007.12.035.

    Article  PubMed  Google Scholar 

  • Rabinowitz, A. R., Hart, T., Whyte, J., & Kim, J. (2018). Neuropsychological recovery trajectories in moderate to severe traumatic brain injury: Influence of patient characteristics and diffuse axonal injury. Journal of the International Neuropsychological Society, 24(3), 237–246. https://doi.org/10.1017/S1355617717000996.

    Article  PubMed  Google Scholar 

  • Rajagopalan, V., Liu, Z., Allexandre, D., Zhang, L., Wang, X. F., Pioro, E. P., et al. (2013). Brain white matter shape changes in amyotrophic lateral sclerosis (ALS): A fractal dimension study. PLoS One, 8(9), e73614. https://doi.org/10.1371/journal.pone.0073614.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Scheid, R., Walther, K., Guthke, T., Preul, C., & von Cramon, D. Y. (2006). Cognitive sequelae of diffuse axonal injury. Archives of Neurology, 63(3), 418–424. https://doi.org/10.1001/archneur.63.3.418.

    Article  PubMed  Google Scholar 

  • Scolding, N. J. (1999). Greenfield's neuropathology. Sixth edition. Journal of Neurology, Neurosurgery, and Psychiatry, 66(5), 696.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Segonne, F., Pacheco, J., & Fischl, B. (2007). Geometrically accurate topology-correction of cortical surfaces using nonseparating loops. IEEE Transactions on Medical Imaging, 26(4), 518–529. https://doi.org/10.1109/TMI.2006.887364.

    Article  PubMed  Google Scholar 

  • Skandsen, T., Kvistad, K. A., Solheim, O., Strand, I. H., Folvik, M., & Vik, A. (2010). Prevalence and impact of diffuse axonal injury in patients with moderate and severe head injury: A cohort study of early magnetic resonance imaging findings and 1-year outcome. Journal of Neurosurgery, 113(3), 556–563. https://doi.org/10.3171/2009.9.JNS09626.

    Article  PubMed  Google Scholar 

  • Sled, J. G., Zijdenbos, A. P., & Evans, A. C. (1998). A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Transactions on Medical Imaging, 17(1), 87–97. https://doi.org/10.1109/42.668698.

    Article  CAS  PubMed  Google Scholar 

  • Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E., Johansen-Berg, H., et al. (2004). Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage, 23(Suppl 1), S208–S219. https://doi.org/10.1016/j.neuroimage.2004.07.051.

    Article  PubMed  Google Scholar 

  • Tate, D. F., Wade, B. S., Velez, C. S., Drennon, A. M., Bolzenius, J., Gutman, B. A., et al. (2016). Volumetric and shape analyses of subcortical structures in United States service members with mild traumatic brain injury. Journal of Neurology, 263(10), 2065–2079. https://doi.org/10.1007/s00415-016-8236-7.

    Article  PubMed  PubMed Central  Google Scholar 

  • Teasdale, G., & Jennett, B. (1976). Assessment and prognosis of coma after head injury. [Research Support, U.S. Gov't, P.H.S.]. Acta Neurochirurgica, 34(1–4), 45–55.

    Article  CAS  PubMed  Google Scholar 

  • Wen, W., & Sachdev, P. S. (2004). Extent and distribution of white matter hyperintensities in stroke patients: The Sydney stroke study. Stroke, 35(12), 2813–2819. https://doi.org/10.1161/01.STR.0000147034.25760.3d.

    Article  PubMed  Google Scholar 

  • Wilson, J. T., Pettigrew, L. E., & Teasdale, G. M. (1998). Structured interviews for the Glasgow outcome scale and the extended Glasgow outcome scale: Guidelines for their use. [Research Support, Non-U.S. Gov't]. Journal of Neurotrauma, 15(8), 573–585.

    Article  CAS  PubMed  Google Scholar 

  • Yue, J. K., Vassar, M. J., Lingsma, H., Cooper, S. R., Yuh, E. L., Mukherjee, P., et al. (2013). Transforming research and clinical knowledge in traumatic brain injury (TRACK-TBI) pilot: Multicenter implementation of the common data elements for traumatic brain injury. Journal of Neurotrauma. https://doi.org/10.1089/neu.2013.2970.

  • Zhang, Y., Brady, M., & Smith, S. (2001). Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. [research support, non-U.S. Gov't]. IEEE Transactions on Medical Imaging, 20(1), 45–57. https://doi.org/10.1109/42.906424.

    Article  CAS  PubMed  Google Scholar 

  • Zhang, L., Liu, J. Z., Dean, D., Sahgal, V., & Yue, G. H. (2006). A three-dimensional fractal analysis method for quantifying white matter structure in human brain. [Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.]. Journal of Neuroscience Methods, 150(2), 242–253. https://doi.org/10.1016/j.jneumeth.2005.06.021.

    Article  PubMed  Google Scholar 

  • Zhang, L., Dean, D., Liu, J. Z., Sahgal, V., Wang, X., & Yue, G. H. (2007). Quantifying degeneration of white matter in normal aging using fractal dimension. [Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't. Research Support, U.S. Gov't, Non-P.H.S.]. Neurobiology of Aging, 28(10), 1543–1555. https://doi.org/10.1016/j.neurobiolaging.2006.06.020.

    Article  CAS  PubMed  Google Scholar 

  • Zhang, L., Butler, A. J., Sun, C. K., Sahgal, V., Wittenberg, G. F., & Yue, G. H. (2008). Fractal dimension assessment of brain white matter structural complexity post stroke in relation to upper-extremity motor function. [Multicenter Study Research Support, N.I.H., Extramural]. Brain Research, 1228, 229–240. https://doi.org/10.1016/j.brainres.2008.06.008.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This study was partially supported by a grant of New Jersey Commission on Brain Injury Research (CBIR15MIG004).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Guang H. Yue.

Ethics declarations

Conflict of interest

The authors do not have any conflict of interest.

Electronic supplementary material

ESM 1

(DOCX 17 kb)

ESM 2

(JPG 130 kb)

ESM 3

(PNG 439 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rajagopalan, V., Das, A., Zhang, L. et al. Fractal dimension brain morphometry: a novel approach to quantify white matter in traumatic brain injury. Brain Imaging and Behavior 13, 914–924 (2019). https://doi.org/10.1007/s11682-018-9892-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11682-018-9892-2

Keywords

Navigation