Institute of Mechanical, Process and Energy Engineering, School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, EH14 4AS, UK.
Med Biol Eng Comput. 2020 Jun;58(6):1369-1381. doi: 10.1007/s11517-020-02168-y. Epub 2020 Apr 11.
Variation in mechanical properties is a useful marker for cancer in soft tissue and has been used in clinical diagnosis for centuries. However, to develop such methods as instrumented palpation, there remain challenges in using the mechanical response during palpation to quantify tumor load. This study proposes a computational framework of identification and quantification of cancerous nodules in soft tissue without a priori knowledge of its geometry, size, and depth. The methodology, using prostate tissue as an exemplar, is based on instrumented palpation performed at positions with various indentation depths over the surface of the relevant structure (in this case, the prostate gland). The profile of force feedback results is then compared with the benchmark in silico models to estimate the size and depth of the cancerous nodule. The methodology is first demonstrated using computational models and then validated using tissue-mimicking gelatin phantoms, where the depth and volume of the tumor nodule is estimated with good accuracy. The proposed framework is capable of quantifying a tumor nodule in soft tissue without a priori information about its geometry, thus presenting great promise in clinical palpation diagnosis for a wide variety of solid tumors including breast and prostate cancer. Graphical abstract This study proposes a computational framework of quantification of cancerous nodules in soft tissue. The methodology is based on instrumental palpation performed at positions with various indentation depths. The profile of force feedback results is then compared with the benchmark in silico models to estimate the size and depth of the cancerous nodule.
力学性能的变化是软组织癌症的一个有用标志物，几个世纪以来一直用于临床诊断。然而，为了开发仪器触诊等方法，仍然存在利用触诊过程中的力学响应来定量肿瘤负荷的挑战。本研究提出了一种在没有关于其几何形状、大小和深度的先验知识的情况下识别和量化软组织中癌性结节的计算框架。该方法以前列腺组织为例，基于在相关结构（在这种情况下为前列腺）表面上具有不同压入深度的位置进行仪器触诊。然后将力反馈结果的曲线与基准的计算机模型进行比较，以估计癌性结节的大小和深度。该方法首先使用计算模型进行演示，然后使用组织模拟明胶体模进行验证，其中肿瘤结节的深度和体积具有很好的准确性。所提出的框架能够在没有关于其几何形状的先验信息的情况下对软组织中的肿瘤结节进行定量，因此在包括乳腺癌和前列腺癌在内的各种实体瘤的临床触诊诊断中具有很大的应用前景。
