Simulation of Spread and Control of Lesions in Brain

TL;DR

This paper presents a network-based simulation model for the spread and control of brain lesions, inspired by Multiple Sclerosis, demonstrating diverse lesion growth and control scenarios through parameter analysis.

Contribution

It introduces a novel graph-based simulation framework for lesion dynamics in the CNS, incorporating alarm signaling and programmed cell death mechanisms.

Findings

Model captures various lesion growth and arrest scenarios

Smooth transition observed between uncontrolled and controlled states

Simulation results align with clinical lesion behaviors

Abstract

A simulation model for the spread and control of lesions in the brain is constructed using a planar network (graph) representation for the Central Nervous System (CNS). The model is inspired by the lesion structures observed in the case of Multiple Sclerosis (MS), a chronic disease of the CNS. The initial lesion site is at the center of a unit square and spreads outwards based on the success rate in damaging edges (axons) of the network. The damaged edges send out alarm signals which, at appropriate intensity levels, generate programmed cell death. Depending on the extent and timing of the programmed cell death, the lesion may get controlled or aggravated akin to the control of wild fires by burning of peripheral vegetation. The parameter phase space of the model shows smooth transition from uncontrolled situation to controlled situation. The simulations show that the model is capable of generating a wide variety of lesion growth and arrest scenarios.