Dong Li, Wijesinghe Philip, Sampson David D, Kennedy Brendan F, Munro Peter R T, Oberai Assad A
Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, TX 78705, USA.
BRITElab, Harry Perkins Institute of Medical Research, QEII Medical Centre, Nedlands and Centre for Medical Research, The University of Western Australia, Crawley, Western Australia, 6009, Australia.
Biomed Opt Express. 2019 Jan 3;10(2):384-398. doi: 10.1364/BOE.10.000384. eCollection 2019 Feb 1.
It is widely accepted that accurate mechanical properties of three-dimensional soft tissues and cellular samples are not available on the microscale. Current methods based on optical coherence elastography can measure displacements at the necessary resolution, and over the volumes required for this task. However, in converting this data to maps of elastic properties, they often impose assumptions regarding homogeneity in stress or elastic properties that are violated in most realistic scenarios. Here, we introduce novel, rigorous, and computationally efficient inverse problem techniques that do not make these assumptions, to realize quantitative volumetric elasticity imaging on the microscale. Specifically, we iteratively solve the three-dimensional elasticity inverse problem using displacement maps obtained from compression optical coherence elastography. This is made computationally feasible with adaptive mesh refinement and domain decomposition methods. By employing a transparent, compliant surface layer with known shear modulus as a reference for the measurement, absolute shear modulus values are produced within a millimeter-scale sample volume. We demonstrate the method on phantoms, on a breast cancer sample , and on human skin . Quantitative elastography on this length scale will find wide application in cell biology, tissue engineering and medicine.
人们普遍认为，在微观尺度上无法获得三维软组织和细胞样本的精确力学性能。基于光学相干弹性成像的现有方法能够在所需分辨率下以及完成该任务所需的体积范围内测量位移。然而，在将这些数据转换为弹性特性图时，它们常常对应力或弹性特性的均匀性做出假设，而在大多数实际情况中这些假设并不成立。在此，我们引入了新颖、严格且计算效率高的反问题技术，这些技术无需做出这些假设，从而实现微观尺度上的定量体积弹性成像。具体而言，我们使用从压缩光学相干弹性成像获得的位移图，迭代求解三维弹性反问题。借助自适应网格细化和区域分解方法，这在计算上变得可行。通过采用具有已知剪切模量的透明柔顺表面层作为测量参考，可在毫米级样本体积内生成绝对剪切模量值。我们在仿体、乳腺癌样本和人体皮肤上展示了该方法。这种长度尺度上的定量弹性成像将在细胞生物学、组织工程和医学中得到广泛应用。
