Multimodal imaging of the dynamic brain tumor microenvironment during glioblastoma progression and in response to treatment

Published: 25 May 2022| Version 1 | DOI: 10.17632/yt99rmbcdt.1
Johanna Joyce


• The deposited data have been generated by intravital imaging of glioma-bearing mice, which allows one to longitudinally track different cell types during tumor progression and response to therapy. • Raw and processed data are divided into two folders, based on the cell lineage-tracing model used (either CX3CR1 or FLT3 lineage-tracing model). • Each folder contains the raw imaging data and an R script folder. • The raw imaging data consist of “Statistics”, parameters extracted after analysis with Imaris (.csv files). Each subfolder represents a specific timepoint for a unique imaging position in one individual mouse. Note that each segmented component (microglia (MG), second harmonic generation (SHG, measuring collagen), and tumor cells) have their own individual subfolder. • The R script folder contains 3 files: the source file containing custom functions for processing and visualization; the processing file which combines imaging- and metadata, and transforms this into a single experimental object in R; and the output file which presents the analyses and visualizations of the data.


Steps to reproduce

• The source and output R scripts can be used to extract the data which are presented in Figures 3, S3 and S5 of the manuscript. The R script provides explanations for the different coding parts. • The provided data and R scripts can also be used for further data analysis and additional exploration of the features of single cells exported from Imaris.


Universite de Lausanne, Ludwig Center for Cancer Research of the University of Lausanne


Macrophage, Microenvironment, Brain Tumor, Intravital Microscopy, Magnetic Resonance Imaging of Brain Tumor