Deep intravital brain tumor imaging enabled by tailored three-photon microscopy and analysis.
Marc Cicero SchubertStella Judith SoykaAmr TamimiEmanuel MausJulian SchroersNiklas WißmannEkin ReyhanSvenja Kristin TetzlaffYvonne YangRobert DenningerRobin PeretzkeCarlo BerettaMichael DrummAlina HeuerVerena BuchertAlicia SteffensJordain WalshonKathleen McCortneySabine HeilandMartin BendszusPeter F NeherAnna GolebiewskaWolfgang WickFrank WinklerMichael O BreckwoldtAnna KreshukThomas KunerCraig M HorbinskiFelix Tobias KurzRobert PrevedelVarun VenkataramaniPublished in: Nature communications (2024)
Intravital 2P-microscopy enables the longitudinal study of brain tumor biology in superficial mouse cortex layers. Intravital microscopy of the white matter, an important route of glioblastoma invasion and recurrence, has not been feasible, due to low signal-to-noise ratios and insufficient spatiotemporal resolution. Here, we present an intravital microscopy and artificial intelligence-based analysis workflow (Deep3P) that enables longitudinal deep imaging of glioblastoma up to a depth of 1.2 mm. We find that perivascular invasion is the preferred invasion route into the corpus callosum and uncover two vascular mechanisms of glioblastoma migration in the white matter. Furthermore, we observe morphological changes after white matter infiltration, a potential basis of an imaging biomarker during early glioblastoma colonization. Taken together, Deep3P allows for a non-invasive intravital investigation of brain tumor biology and its tumor microenvironment at subcortical depths explored, opening up opportunities for studying the neuroscience of brain tumors and other model systems.
Keyphrases
- white matter
- high resolution
- single molecule
- artificial intelligence
- multiple sclerosis
- optical coherence tomography
- high speed
- high throughput
- cell migration
- machine learning
- mass spectrometry
- big data
- deep learning
- label free
- living cells
- risk assessment
- functional connectivity
- single cell
- fluorescence imaging
- cross sectional