Kontomaris Stylianos Vasileios, Malamou Anna, Stylianou Andreas
Cancer Mechanobiology and Applied Biophysics Group, School of Sciences, European University Cyprus, 2404 Nicosia, Cyprus.
School of Electrical & Computer Engineering, National Technical University of Athens, 157 80 Athens, Greece.
Sensors (Basel). 2025 Jun 2;25(11):3510. doi: 10.3390/s25113510.
This review explores recent advances in data processing for atomic force microscopy (AFM) nanoindentation on soft samples, with a focus on "apparent" or "average" Young's modulus distributions used for cancer diagnosis and treatment monitoring. Young's modulus serves as a potential key biomarker, distinguishing normal from cancerous cells or tissue by assessing stiffness variations at the nanoscale. However, user-independent, reproducible classification remains challenging due to assumptions in traditional mechanics models, particularly Hertzian theory. To enhance accuracy, depth-dependent mechanical properties and polynomial corrections have been introduced to address sample heterogeneity and finite thickness. Additionally, AFM measurements are affected by tip imperfections and the viscoelastic nature of biological samples, requiring careful data processing and consideration of loading conditions. Furthermore, a quantitative approach using distributions of mechanical properties is suitable for tissue classification and for evaluating treatment-induced changes in nanomechanical properties. As part of this review, the use of AFM-based mechanical properties as a tool for monitoring treatment outcomes-including treatments with antifibrotic drugs and photodynamic therapy-is also presented. By analyzing nanomechanical property distributions before and after treatment, AFM provides insights for optimizing therapeutic strategies, reinforcing its role in personalized cancer care and expanding its applications in research and clinical settings.
本综述探讨了软样品原子力显微镜（AFM）纳米压痕数据处理的最新进展，重点关注用于癌症诊断和治疗监测的“表观”或“平均”杨氏模量分布。杨氏模量作为一种潜在的关键生物标志物，通过评估纳米尺度的硬度变化来区分正常细胞与癌细胞或组织。然而，由于传统力学模型（特别是赫兹理论）中的假设，独立于用户的、可重复的分类仍然具有挑战性。为了提高准确性，已引入深度依赖的力学性能和多项式校正来解决样品的异质性和有限厚度问题。此外，AFM测量受尖端缺陷和生物样品粘弹性性质的影响，需要仔细的数据处理并考虑加载条件。此外，使用力学性能分布的定量方法适用于组织分类和评估治疗引起的纳米力学性能变化。作为本综述的一部分，还介绍了将基于AFM的力学性能用作监测治疗结果的工具，包括抗纤维化药物治疗和光动力疗法。通过分析治疗前后的纳米力学性能分布，AFM为优化治疗策略提供了见解，强化了其在个性化癌症护理中的作用，并扩大了其在研究和临床环境中的应用。
