New Funding Within Priority Program »Computational Connectomics« for Team of Charité Berlin and Members of »Cutting«
Creation of Personalized Models of the Brain of Tumor Patients
Connectome construction of a patient with a tumor in the speech-eloquent area of the brain.
The connection strengths of the white matter are shown as edges with a heat map (dark = weak connection, light = strong connection). The cortical areas of the brain and their size are illustrated as nodes in the form of spheres. Additionally, three orange TMS points are shown (TMS = Transcranial Magnetic Stimulation). In this case, the patient’s speech network could be non-invasively disturbed in these areas and mapped accordingly.
The visualization of the white matter is based on tractography. The different directions of the white matter can be measured and displayed by means of diffusion-weighted magnetic resonance imaging. Copyright: Lucius Fekonja & Image Guidance Lab, Charité – Universitätsmedizin Berlin
The field of connectomics aims to comprehensively describe the physical and functional coupling among the neural elements of the brain. Creating personalized models of the brain of tumor patients helps to better understand the impact of a brain tumor on the cerebral network and plasticity and functional reserve capacity. Similarly, it helps to improve effects of neurosurgery on the connectome and identify key nodes and edges, i.e., potential high-risk areas for surgery, reveal the network basis of language function in relation to tumors, and predict the course of recovery.
This work is also closely related to the Cluster Project Adaptive Digital Twin within the project Cutting which aims at embodying the central nervous system of healthy subjects and patients in the digital space. They study and develop co-adaptive models that enable simulation, statistical analysis and visual inspection of the brain using individually acquired functional and structural data.
In engineering, the production of »digital twins« refers to the practice of maintaining continuously updated digital models of highly sensitive and sophisticated machinery, such as aircraft jet engines, in order to predict and anticipate failures and other disruptions. This specific regime of digital materialization inspired us to simulate the possible consequences of tumor growth and neurosurgery.
The project is funded by the German Research Foundation (DFG) and part of the in March 2016 established Priority Programme Computational Connectomics (SPP 2041) and will run for three years.