Tracking the Adaptation and Compensation Processes of Patients’ Brain Arterial Network to an Evolving Glioblastoma

Junxi Zhu, Spencer Teolis, Nadia Biassou, Amy Tabb, Pierre Emmanuel Jabin, Orit Lavi

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

The brain’s vascular network dynamically affects its development and core functions. It rapidly responds to abnormal conditions by adjusting properties of the network, aiding stabilization and regulation of brain activities. Tracking prominent arterial changes has clear clinical and surgical advantages. However, the arterial network functions as a system; thus, local changes may imply global compensatory effects that could impact the dynamic progression of a disease. We developed automated personalized system-level analysis methods of the compensatory arterial changes and mean blood flow behavior from a patient’s clinical images. By applying our approach to data from a patient with aggressive brain cancer compared with healthy individuals, we found unique spatiotemporal patterns of the arterial network that could assist in predicting the evolution of glioblastoma over time. Our personalized approach provides a valuable analysis tool that could augment current clinical assessments of the progression of glioblastoma and other neurological disorders affecting the brain.

Original languageEnglish (US)
Pages (from-to)488-501
Number of pages14
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume44
Issue number1
DOIs
StatePublished - Jan 2022

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

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