Structural connectivity modifications in the brain of selected patients with tumour after its removal by surgery (a case study)

E. Sayari* (Corresponding Author), Evandro G. Seifert, F. E. Cruziniani, Enrique C. Gabrick, Kelly C. Iarosz, Jose D. Szezech Jr, Murilo Baptista, I. L. Caldas, Antonio M. Batista

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The brain is a complex organ that plays an important role in the control of
most functions of the body, such as awareness, thoughts, sensations, movements, speech, and memory. A tumour formed in the brain can affect its
ability to accurately and properly perform such functions. In this work,
we use two brains with malignant tumours of different sizes before and after surgery. To identify the brain structural topology, we analyse different
networks with various configurations and use diagnostic tools to match the
network topologies generated by simulations with those obtained from the
data. Our results show that the Newman-Watts small-world network best reproduces the topology from the patients with small and large tumours before
surgery. Considering two analysed brains, our outcomes suggest that surgery
can alter the brain topology from small-world to extended Barab´asi-Albert
scale-free.
Original languageEnglish
Article number128849
Number of pages15
JournalPhysica. A, Statistical Mechanics and its Applications
Volume623
Early online date23 May 2023
DOIs
Publication statusPublished - 1 Aug 2023

Bibliographical note

Acknowledgments
This study was possible by partial financial support from the following agencies: Funda¸c˜ao Arauc´aria, Brazilian National Council for Scientific and Technological Development (CNPq), and Coordination for the Improvement of Higher Education Personnel (CAPES). S˜ao Paulo Research Foundation (FAPESP 2018/03211-6, 2022/13761-9). We thank 105 Group Science (www.105groupscience.com).

Keywords

  • Complex system
  • Brain tumor
  • Structural connectivity matrix
  • Graph theory

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