B Alekya, Rao Sanjay, Pandya Hardik J
Biomedical and Electronic (10(-6)-10(-9)) Engineering Systems Laboratory, Department of Electronic Systems Engineering, Indian Institute of Science, Bangalore 12, India.
Department of Pediatric Surgery, Mazumdar Shaw Multispecialty Hospital, Narayana Health, Bangalore 99, India.
Clin Biomech (Bristol). 2019 Oct;69:127-140. doi: 10.1016/j.clinbiomech.2019.07.016. Epub 2019 Jul 16.
From cancer diagnosis to detailed characterization of arterial wall biomechanics, the elastic property of tissues is widely studied as an early sign of disease onset. The fibrous structural features of tissues are a direct measure of its health and functionality. Alterations in the structural features of tissues are often manifested as local stiffening and are early signs for diagnosing a disease. These elastic properties are measured ex vivo in conventional mechanical testing regimes, however, the heterogeneous microstructure of tissues can be accurately resolved over relatively smaller length scales with enhanced spatial resolution using techniques such as micro-indentation, microelectromechanical (MEMS) based cantilever sensors and optical catheters which also facilitate in vivo assessment of mechanical properties. In this review, we describe several probing strategies (qualitative and quantitative) based on the spatial scale of mechanical assessment and also discuss the potential use of machine learning techniques to compute the mechanical properties of soft tissues. This work details state of the art advancement in probing strategies, associated challenges toward quantitative characterization of tissue biomechanics both from an engineering and clinical standpoint.
从癌症诊断到动脉壁生物力学的详细表征,组织的弹性特性作为疾病发作的早期迹象被广泛研究。组织的纤维结构特征是其健康状况和功能的直接衡量指标。组织结构特征的改变通常表现为局部硬化,是疾病诊断的早期迹象。这些弹性特性是在传统力学测试方法中离体测量的,然而,使用诸如微压痕、基于微机电系统(MEMS)的悬臂传感器和光学导管等技术,可以在相对较小的长度尺度上以更高的空间分辨率精确解析组织的异质微观结构,这些技术也有助于体内力学性能评估。在这篇综述中,我们基于力学评估的空间尺度描述了几种探测策略(定性和定量),并讨论了使用机器学习技术计算软组织力学性能的潜在用途。这项工作详细介绍了探测策略的最新进展,以及从工程和临床角度对组织生物力学进行定量表征所面临的相关挑战。