Towards patient-specific modeling of brain tumor growth and formation of secondary nodes guided by DTI-MRI

NeuroImage. Clinical
Stelios AngeliTriantafyllos Stylianopoulos

Abstract

Previous studies to simulate brain tumor progression, often investigate either temporal changes in cancer cell density or the overall tissue-level growth of the tumor mass. Here, we developed a computational model to bridge these two approaches. The model incorporates the tumor biomechanical response at the tissue level and accounts for cellular events by modeling cancer cell proliferation, infiltration to surrounding tissues, and invasion to distant locations. Moreover, acquisition of high resolution human data from anatomical magnetic resonance imaging, diffusion tensor imaging and perfusion imaging was employed within the simulations towards a realistic and patient specific model. The model predicted the intratumoral mechanical stresses to range from 20 to 34 kPa, which caused an up to 4.5 mm displacement to the adjacent healthy tissue. Furthermore, the model predicted plausible cancer cell invasion patterns within the brain along the white matter fiber tracts. Finally, by varying the tumor vascular density and its invasive outer ring thickness, our model showed the potential of these parameters for guiding the timing (83-90 days) of cancer cell distant invasion as well as the number (0-2 sites) and location (temportal and/o...Continue Reading

Associated Clinical Trials

Citations

Mar 10, 2020·Methods : a Companion to Methods in Enzymology·Myrianthi HadjicharalambousVasileios Vavourakis
May 11, 2021·Zeitschrift für medizinische Physik·S KnobeCh Rübe
Jun 3, 2021·Journal of Clinical Medicine·Jacopo FalcoFrancesco Acerbi

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Methods Mentioned

BETA
imaging techniques

Software Mentioned

Diffusion Toolkit
COMSOL
COMSOL Multiphysics
Matlab

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