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Updated: Jun 23, 2026

Characterizing Multiscale Mechanical Properties of Brain Tissue Using Atomic Force Microscopy, Impact Indentation, and Rheometry
Published on: September 6, 2016
Microscale mechanical properties of brain tumor characterized by atomic force microscopy: implications for
Xuan Qin1, Ping Wu1, Xinrui Zeng2
1State Key Laboratory of Mechanics and Control for Aerospace Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China; MIIT Key Laboratory of Multifunctional Lightweight Materials and Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
Abstract:
The infiltrative growth pattern of glioblastoma leads to poorly defined tumor margins, which represents a major cause of treatment failure and high recurrence rates. Although mechanomedicine has recently shown promise, the distribution of microscale mechanical properties at glioblastoma margin remains unclear. In this study, we investigated the ex vivo microscale mechanical properties of glioblastoma and its contralateral brain tissue from tumor-bearing mice (n = 6), as well as brain tissue from healthy mice (n = 3), using atomic force microscopy. Our findings reveal that glioblastoma increases the stiffness of contralateral brain, including gray matter, white matter, and aqueduct. Glioblastoma tissues exhibit pronounced mechanical heterogeneity, with a ring-like Young's modulus distribution. The Young's modulus of the inner tumor margin (2018.9 ± 1191.6 Pa) is higher than that of the tumor center (1988.7 ± 1033.0 Pa) and outer tumor margin (1391.8 ± 415.5 Pa). This ring-like mechanical pattern may correspond to the ring enhancement observed on clinical MRI, which typically indicates the contrast-enhancing, highly cellular invasive front surrounding a necrotic core. Furthermore, Young's modulus maps reveal that the inner margin region exhibits the strongest mechanical heterogeneity and highest maximum stiffness gradient among the three regions, suggesting this region constitutes the invasive front. The findings contribute to the understanding of glioblastoma progression and provide novel insights for glioblastoma margin delineation.
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