Hipwell John H, Vavourakis Vasileios, Han Lianghao, Mertzanidou Thomy, Eiben Björn, Hawkes David J
Centre for Medical Image Computing, Malet Place Engineering Building, University College London, Gower Street, London WC1E 6BT, UK.
Phys Med Biol. 2016 Jan 21;61(2):R1-31. doi: 10.1088/0031-9155/61/2/R1. Epub 2016 Jan 6.
Breast radiology encompasses the full range of imaging modalities from routine imaging via x-ray mammography, magnetic resonance imaging and ultrasound (both two- and three-dimensional), to more recent technologies such as digital breast tomosynthesis, and dedicated breast imaging systems for positron emission mammography and ultrasound tomography. In addition new and experimental modalities, such as Photoacoustics, Near Infrared Spectroscopy and Electrical Impedance Tomography etc, are emerging. The breast is a highly deformable structure however, and this greatly complicates visual comparison of imaging modalities for the purposes of breast screening, cancer diagnosis (including image guided biopsy), tumour staging, treatment monitoring, surgical planning and simulation of the effects of surgery and wound healing etc. Due primarily to the challenges posed by these gross, non-rigid deformations, development of automated methods which enable registration, and hence fusion, of information within and across breast imaging modalities, and between the images and the physical space of the breast during interventions, remains an active research field which has yet to translate suitable methods into clinical practice. This review describes current research in the field of breast biomechanical modelling and identifies relevant publications where the resulting models have been incorporated into breast image registration and simulation algorithms. Despite these developments there remain a number of issues that limit clinical application of biomechanical modelling. These include the accuracy of constitutive modelling, implementation of representative boundary conditions, failure to meet clinically acceptable levels of computational cost, challenges associated with automating patient-specific model generation (i.e. robust image segmentation and mesh generation) and the complexity of applying biomechanical modelling methods in routine clinical practice.
乳腺放射学涵盖了从常规成像（如X线乳腺摄影、磁共振成像和超声成像（二维和三维））到最新技术（如数字乳腺断层合成）以及用于正电子发射乳腺摄影和超声断层扫描的专用乳腺成像系统等全方位的成像方式。此外，诸如光声成像、近红外光谱和电阻抗断层扫描等新的和实验性的成像方式也正在兴起。然而，乳房是一个高度可变形的结构，这使得在乳腺筛查、癌症诊断（包括图像引导活检）、肿瘤分期、治疗监测、手术规划以及模拟手术效果和伤口愈合等方面，对成像方式进行视觉比较变得极为复杂。主要由于这些明显的非刚性变形带来的挑战，开发能够在乳腺成像方式内部和之间、以及在干预过程中图像与乳房物理空间之间进行配准并因此实现信息融合的自动化方法，仍然是一个活跃的研究领域，尚未将合适的方法转化为临床实践。本综述描述了乳腺生物力学建模领域的当前研究，并确定了相关出版物，其中所得到的模型已被纳入乳腺图像配准和模拟算法中。尽管有这些进展，但仍有一些问题限制了生物力学建模的临床应用。这些问题包括本构建模的准确性、代表性边界条件的实现、未能达到临床上可接受的计算成本水平、与自动生成患者特异性模型（即稳健的图像分割和网格生成）相关的挑战，以及在常规临床实践中应用生物力学建模方法的复杂性。
