Rizzuto Emanuele, Carosio Silvia, Faraldi Martina, Pisu Simona, Musarò Antonio, Del Prete Zaccaria
Department of Mechanical and Aerospace Engineering, University of Rome La Sapienza, Via Eudossiana 18, 00184 Rome, Italy.
Center for Life Nano Science@Sapienza, Istituto Italiano di Tecnologia, Viale Regina Elena 291, 00161 Rome, Italy.
Appl Bionics Biomech. 2016;2016:7465095. doi: 10.1155/2016/7465095. Epub 2016 Mar 9.
Tissue engineering is a multidisciplinary science based on the application of engineering approaches to biologic tissue formation. Engineered tissue internal organization represents a key aspect to increase biofunctionality before transplant and, as regarding skeletal muscles, the potential of generating contractile forces is dependent on the internal fiber organization and is reflected by some macroscopic parameters, such as the spontaneous contraction. Here we propose the application of digital image correlation (DIC) as an independent tool for an accurate and noninvasive measurement of engineered muscle tissue spontaneous contraction. To validate the proposed technique we referred to the X-MET, a promising 3-dimensional model of skeletal muscle. The images acquired through a high speed camera were correlated with a custom-made algorithm and the longitudinal strain predictions were employed for measuring the spontaneous contraction. The spontaneous contraction reference values were obtained by studying the force response. The relative error between the spontaneous contraction frequencies computed in both ways was always lower than 0.15%. In conclusion, the use of a DIC based system allows for an accurate and noninvasive measurement of biological tissues' spontaneous contraction, in addition to the measurement of tissue strain field on any desired region of interest during electrical stimulation.
组织工程是一门多学科科学,基于工程方法在生物组织形成中的应用。工程组织的内部结构是移植前提高生物功能的一个关键方面,就骨骼肌而言,产生收缩力的潜力取决于内部纤维结构,并由一些宏观参数反映出来,如自发收缩。在此,我们提出将数字图像相关技术(DIC)作为一种独立工具,用于准确、无创地测量工程化肌肉组织的自发收缩。为了验证所提出的技术,我们参考了X-MET,一种很有前景的骨骼肌三维模型。通过高速摄像机采集的图像与定制算法进行关联,并利用纵向应变预测来测量自发收缩。通过研究力响应获得自发收缩参考值。两种方法计算出的自发收缩频率之间的相对误差始终低于0.15%。总之,基于DIC的系统不仅可以在电刺激期间对任何感兴趣的区域进行组织应变场测量,还能准确、无创地测量生物组织的自发收缩。