UKRAINS'KYI VISNYK PSYKHONEVROLOHII

The Scientific and Practical Journal of Medicine
ISSN 2079-0325(p)
DOI 10.36927/2079-0325
Home » Archive of numbers » 2023 » Volume 31, issue 2 (115) » FRACTAL ANALYSIS OF MAGNETIC RESONANCE BRAIN IMAGES: DIAGNOSTIC VALUE (literature review)

FRACTAL ANALYSIS OF MAGNETIC RESONANCE BRAIN IMAGES: DIAGNOSTIC VALUE (literature review)

Authors

Type of Article

  • Scientific Article

In the Section

  • LITERATURE REVIEW

Key words

Index UDK:
  • 611.813:57.086:517:530.191

Abstract

Fractal analysis is a relatively new mathematical method for image analysis, which quantitatively characterizes the spatial configuration complexity degree of the studied objects. In clinical neuroscience, fractal analysis is most often used for morphometric studies of cerebral hemispheres and cerebellum. An analysis of the cortex, white matter, and their outer surfaces, as well as analysis of brain tissue as a whole can be carried out. The fractal dimension (parameter determined by fractal analysis) depends on individual anatomical features and may change during ontogenesis. Changes in the fractal dimension were determined during the process of brain development and in its deviations, in normal aging and neurodegenerative diseases, acute brain tissue lesions (traumatic brain injury and cerebral circulation disorders) and in some mental disorders. The advantages of fractal analysis application in clinical practice include the possibility of detecting the morphological changes in the brain structures as well as the possibility of the quantitative and objective assessment of the severity of the detected changes.

Pages

  • 93-97

Year / Issue

Download PDF

References

  1. Advances in MRI-based computational neuroanatomy: from morphometry to  in-vivo histology  / [N. Weiskopf, S. Mohammadi, A. Lutti, M. F. Callaghan] // Curr Opin Neurol. 2015. 28 (4). 313—322. DOI: https://doi.org/10.1097/WCO.0000000000000222.
  2. Mandelbrot B. The  fractal geometry of  nature. San Francisco : W. H. Freeman and Company, 1982.
  3. Fractals in the Neurosciences, Part I: General Principles and Basic Neurosciences / A. Di  Ieva, F. Grizzi, H.  Jelinek [et  ]  // Neuroscientist. 2014. 20  (4). 403—417. DOI: https://doi.org/10.1177/1073858413513927.
  4. Fractals in the  neurosciences, Part II: clinical applications and future perspectives  / A.  Di  Ieva, F.    Esteban, F.  Grizzi  [et  al.]  // Neuroscientist. 2015. 21  (1). 30—43. DOI: https://doi.org/10.1177/1073858413513928.
  5. Feder J. Fractals. New York : Plenum Press, 1988.
  6. Characterization of Atrophic Changes in the Cerebral Cortex Using Fractal Dimensional Analysis / R.    King, A. T.  George, T.  Jeon T. [et  al]; the  Alzheimer’s Disease Neuroimaging Initiative  // Brain Imaging Behav. 2009. 3  (2). 154—166. DOI: https://doi.org/10.1007/s11682-008-9057-9.
  7. Fractal dimension analysis of the cortical ribbon in mild Alzheimer’s disease / R. D. King, B. Brown, M. Hwang [et al.] // Neuroimage. 2010. 53 (2). 471—9. DOI: https://doi.org/10.1016/j.neuroimage.2010.06.050.
  8. Brain Cortical Complexity Alteration in Amyotrophic Lateral Sclerosis: A Preliminary Fractal Dimensionality Study / [J.    Chen, N.  X. Huang, T.  X. Zou, H.  J. Chen; Alzheimer’s Disease Neuroimaging Initiative] // Biomed Res Int. 2020 Mar 19; 2020. 1521679. DOI: https://doi.org/10.1155/2020/1521679.
  9. Kalmanti E. Fractal dimension as an index of brain cortical changes throughout life / E. Kalmanti, T. G. Maris // In Vivo. 2007. 21 (4). 641—646. PMID: 17708359.
  10. Fractal dimension in human cortical surface: multiple regression analysis with cortical thickness, sulcal depth, and 96 ISSN 2079-0325. folding area / K. Im, J.    Lee, U. Yoon  [et  al.]  // Hum  Brain Mapp. 2006. 27 (12). 994—1003. DOI: https://doi.org/10.1002/hbm.20238.
  11. Madan C. R. Cortical complexity as a measure of age-related brain atrophy / C. R. Madan, E. A. Kensinger // Neuroimage. 2016. 134. 617—629. DOI: https://doi.org/10.1016/j.neuroimage.2016.04.029.
  12. Cortical surface complexity in frontal and temporal areas varies across subgroups of schizophrenia  / [I.  Nenadic, R. A. Yotter, H. Sauer, C. Gaser] // Hum Brain Mapp. 2014. 35 (4). 1691—1699. DOI: https://doi.org/10.1002/hbm.22283.
  13. Left cerebral cortex complexity differences in sporadic healthy individuals with auditory verbal hallucinations: A pilot study / C. Zhuo, G. Li, C. Chen C. [et al.] // Psychiatry Res. 2020. 285. 112834. DOI: https://doi.org/10.1016/j.psychres.2020.112834.
  14. Cortical complexity in bipolar disorder applying a spherical harmonics approach / I. Nenadic, R.  Yotter, M.  Dietzek [et al.] // Psychiatry Res Neuroimaging. 2017. 263. 44—47. DOI: https://doi.org/10.1016/j.pscychresns.2017.02.007.
  15. Cortical thickness, local gyrification index and fractal dimensionality in people with acute and recovered Anorexia Nervosa and in people with Bulimia Nervosa / G. Cascino, A. Canna, A. M. Monteleone [et al.] // Psychiatry Res Neuroimaging. 2020. 299. 111069. DOI: https://doi.org/10.1016/j.pscychresns.2020.111069.
  16. Altered cortical gyrification, sulcal depth, and fractal dimension in the autism spectrum disorder comorbid attention-deficit/hyperactivity disorder than the  autism spectrum disorder / Y. Chen, J. Luo, S. Chen [et al.] // Neuroreport. 2023. 34 (2). 93—101. DOI: https://doi.org/10.1097/WNR.0000000000001864.
  17. Cortical fractal dimension predicts disability worsening in Multiple Sclerosis patients / E. Roura, G. Maclair, M. Andorrà, [et ] // Neuroimage Clin. 2021. 30. 102653. DOI: https://doi.org/10.1016/j.nicl.2021.102653.
  18. Farahibozorg S. Age- and sex-related variations in the brain white matter fractal dimension throughout adulthood: an  MRI study  / S.  Farahibozorg, S.    HashemiGolpayegani, J.  Ashburner  // Clin Neuroradiol. 2015. 25  (1). 19—32. DOI: https://doi.org/10.1007/s00062-013-0273-3.
  19. Quantifying degeneration of white matter in normal aging using fractal dimension / L. Zhang, D. Dean, J. Z. Liu [et al.] // Neurobiol Aging. 2007. 28 (10). 1543—55. DOI: https://doi.org/10.1016/j.neurobiolaging.2006.06.020.
  20. Fractal dimension brain morphometry: a novel approach to quantify white matter in  traumatic brain injury  / V. Rajagopalan, A. Das, L. Zhang [et al.] // Brain Imaging Behav. 2019. 13 (4). 914—924. DOI: https://doi.org/10.1007/s11682-018-9892-2.
  21. Maryenko N. I. Comparative analysis of fractal dimensions of human cerebellum: impact of image preprocessing and fractal analysis methods / N.   Maryenko, O. Y.  Stepanenko  // Wiad Lek. 2022. 75 (2). 438—443. DOI: https://doi.org/10.36740/WLek202202120.
  22. Liu J. Z. Fractal dimension in human cerebellum measured by magnetic resonance imaging / J. Z. Liu, L. D. Zhang, G. H. Yue // Biophys J. 2003. 85 (6). 4041—4046. DOI: https://doi.org/10.1016/S0006-3495(03)74817-6.
  23. Fractal dimension analysis of cerebellum in Chiari Malformation type I. / [E. Akar, S. Kara, H. Akdemir, A. Kırış] // Comput Biol Med. 2015. 64. 179—186. DOI: https://doi.org/10.1016/j.compbiomed.2015.06.024.
  24. Fractal dimension analysis for quantifying cerebellar morphological change of multiple system atrophy of the cerebellar type (MSA-C) / Y. T. Wu, K.   Shyu, C. W.  Jao  [et  al.] Neuroimage. 2010. 49 (1). 539—551. DOI: https://doi.org/10.1016/j.neuroimage.2009.07.042.
  25. Maryenko N. Fractal dimension of cerebellum in acute cerebellar infarction (magnetic resonance imaging study) / N. Maryenko, O.  Stepanenko  // Aktualności Neurologiczne (Current Neurology). 2022. 22  (1). 3—10. DOI: https://doi.org/10.15557/AN.2022.0001.
  26. Takao H. Brain morphology is individual-specific information / H. Takao, N. Hayashi, K. Ohtomo // Magn Reson Imaging. 2015. 33 (6). 816—821. DOI: https://doi.org/10.1016/j.mri.2015.03.010.
  27. Automatic localization of  cerebral cortical malformations using fractal analysis  / A.  De  Luca, F.  Arrigoni, R. Romaniello [et al.] // Phys Med Biol. 2016. 61 (16). 6025—6040. DOI: https://doi.org/10.1088/0031-9155/61/16/6025

Journal’s Indexing:

UKRAINS'KYI VISNYK PSYKHONEVROLOHII

The Scientific and Practical Journal of Medicine

ДУ «ІНПН імені
П.В. ВОЛОШИНА
НАМН УКРАЇНИ»