Topological Analysis of Mouse Brain Vasculature via 3D Light-sheet Microscopy Images (2402.16894v1)
Abstract: Vascular networks play a crucial role in understanding brain functionalities. Brain integrity and function, neuronal activity and plasticity, which are crucial for learning, are actively modulated by their local environments, specifically vascular networks. With recent developments in high-resolution 3D light-sheet microscopy imaging together with tissue processing techniques, it becomes feasible to obtain and examine large-scale brain vasculature in mice. To establish a structural foundation for functional study, however, we need advanced image analysis and structural modeling methods. Existing works use geometric features such as thickness, tortuosity, etc. However, geometric features cannot fully capture structural characteristics such as the richness of branches, connectivity, etc. In this paper, we study the morphology of brain vasculature through a topological lens. We extract topological features based on the theory of topological data analysis. Comparing of these robust and multi-scale topological structural features across different brain anatomical structures and between normal and obese populations sheds light on their promising future in studying neurological diseases.
- “Sugar for the brain: the role of glucose in physiological and pathological brain function,” Trends in neurosciences, vol. 36, no. 10, pp. 587–597, 2013.
- “How energy supports our brain to yield consciousness: Insights from neuroimaging based on the neuroenergetics hypothesis,” Frontiers in Systems Neuroscience, vol. 15, pp. 648860, 2021.
- “Glucose and lactate metabolism during brain activation,” Journal of neuroscience research, vol. 66, no. 5, pp. 824–838, 2001.
- “Vascular and neurogenic rejuvenation of the aging mouse brain by young systemic factors,” Science, vol. 344, no. 6184, pp. 630–634, 2014.
- “The effects of exercise on spatial learning and anxiety-like behavior are mediated by an igf-i-dependent mechanism related to hippocampal neurogenesis,” Molecular and Cellular Neuroscience, vol. 37, no. 2, pp. 402–411, 2008.
- Costantino Iadecola, “The neurovascular unit coming of age: a journey through neurovascular coupling in health and disease,” Neuron, vol. 96, no. 1, pp. 17–42, 2017.
- “Glial and neuronal control of brain blood flow,” Nature, vol. 468, no. 7321, pp. 232–243, 2010.
- “Advances in studying whole mouse brain vasculature using high-resolution 3d light microscopy imaging,” Neurophotonics, vol. 9, no. 2, pp. 021902–021902, 2022.
- “Rapid and fully automated blood vasculature analysis in 3d light-sheet image volumes of different organs,” Cell Reports Methods, vol. 3, no. 3, 2023.
- “Open-source analysis and visualization of segmented vasculature datasets with vesselvio,” Cell reports methods, vol. 2, no. 4, 2022.
- “Interactive visualization and analysis of morphological skeletons of brain vasculature networks with vessmorphovis,” Bioinformatics, vol. 36, no. Supplement_1, pp. i534–i541, 2020.
- “Machine learning analysis of whole mouse brain vasculature,” Nature methods, vol. 17, no. 4, pp. 442–449, 2020.
- Computational topology: an introduction, American Mathematical Society, 2010.
- Computational topology for data analysis, Cambridge University Press, 2022.
- “Topological persistence and simplification,” Discrete & Computational Geometry, vol. 28, pp. 511–533, 2002.
- “Persistent homology transform for modeling shapes and surfaces,” Information and Inference: A Journal of the IMA, 2014.