软组织和力场:用于诊断和再生医学的先进三维同步加速器成像技术

Alessandra Giuliani, M. Furlani, Nicole Riberti
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摘要

机械刺激不仅是细胞的调节器,也是细胞外基质活动的调节器,特别是胶原蛋白束的组成、数量和分布。胶原蛋白是人体组织中的主要蛋白质,对组织的机械特性(包括拉伸延展性和压缩行为)做出了贡献。然而,这些组织中的机械力如何转化为机械传导途径--最终驱动生物反应--仍是未知数。在这种情况下,有必要采用三维成像方法来捕捉因高度各向异性和平面外运动而增加的复杂性,尤其是在无序、受伤的状态下。近年来,一种对胶原组织进行三维成像和定量分析的有趣方法得到了推广:该方法基于同步辐射的独特特性;它克服了组织学和传统断层扫描方法的内在局限性,前者只能实现二维特征描述,后者对胶原组织的分辨率较低。在这项研究中,我们的重点是基于同步辐射的相位对比断层成像技术的最新研究,该技术不仅可用于研究人体胶原组织的生理病理,还可用于研究不同组织工程策略的结果。令人鼓舞的结果证明,同步加速器成像技术适用于获取和量化人体胶原组织。此外,在神经网络和深度学习的支持下,同步辐射相位对比图像中以前无法分辨的结构也有可能被量化。特别是,胶原蛋白束可以通过其方向而不仅仅是物理密度来识别,而传统的阈值分割技术则无法做到这一点。纤维取向、曲率和应变的局部变化可能涉及区域应变传递和机械功能的变化,从而对临床产生影响。对这些动力学的理解可以促进发现保持或重建正确组织张力的治疗方法,这是成功调节组织重塑/修复和伤口愈合的关键。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Soft tissues and force fields: advanced 3D synchrotron-based imaging for diagnostics and regenerative medicine
Mechanical stimuli are regulators not only in cells but also in the extracellular matrix activity, with special reference to collagen bundles composition, amount and distribution. Collagen, the major protein in human tissues, contributes to the tissues mechanical properties including ductility under tension and also compressive behavior. However, how mechanical forces in these tissues are translated to mechanotransduction pathways - that ultimately drive the biological response - remains unknown. In this context, 3D imaging methods are necessary to capture the increased complexity that can arise due to high levels of anisotropy and out-of-plane motion, particularly in the disorganized, injured states. An interesting method for 3D imaging and quantitative analysis of collagenous tissues has spread in recent years: it is based on the unique characteristics of synchrotron radiation; it overcome the intrinsic limitations of both histology, achieving only a 2D characterization, and conventional tomographic approaches, poorly resolving the collagenous tissues. In this research, the focus has been placed on our recent researches based on the exploitation of synchrotron-based phase-contrast tomography for the investigation human collagenous tissue physio-pathologies, but also to study the outcome of different tissue-engineering strategies. Encouraging results proved that synchrotron-based imaging is suitable to access and quantify human collagenous tissues. Moreover, with the support of neural networks and deep learning, it is possible to quantify structures in synchrotron phase-contrast images that were not distinguishable before. In particular, collagen bundles can be identified by their orientation and not only by their physical densities, as was made possible using conventional thresholding segmentation techniques. Localised changes in fiber orientation, curvature and strain may involve changes in regional strain transfer and mechanical function, with consequent clinical implications. The comprehension of these kinetics can foster the discovery of therapeutic approaches for the maintaining or re-establishment of correct tissue tensions, as a key to successful and regulated tissues remodeling/repairing and wound healing.
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