Istituto Italiano di Tecnologia, Center for Micro-BioRobotics, Viale Rinaldo Piaggio 34, 56025, Pontedera, Pisa, Italy.
Universitá di Verona, Strada le Grazie 15, 37134, Verona, Italy.
Med Biol Eng Comput. 2019 Apr;57(4):913-924. doi: 10.1007/s11517-018-1931-z. Epub 2018 Nov 27.
The modeling of breast deformations is of interest in medical applications such as image-guided biopsy, or image registration for diagnostic purposes. In order to have such information, it is needed to extract the mechanical properties of the tissues. In this work, we propose an iterative technique based on finite element analysis that estimates the elastic modulus of realistic breast phantoms, starting from MRI images acquired in different positions (prone and supine), when deformed only by the gravity force. We validated the method using both a single-modality evaluation in which we simulated the effect of the gravity force to generate four different configurations (prone, supine, lateral, and vertical) and a multi-modality evaluation in which we simulated a series of changes in orientation (prone to supine). Validation is performed, respectively, on surface points and lesions using as ground-truth data from MRI images, and on target lesions inside the breast phantom compared with the actual target segmented from the US image. The use of pre-operative images is limited at the moment to diagnostic purposes. By using our method we can compute patient-specific mechanical properties that allow compensating deformations. Graphical Abstract Workflow of the proposed method and comparative results of the prone-to-supine simulation (red volumes) validated using MRI data (blue volumes).
乳房变形的建模在医学应用中很有意义,例如图像引导活检,或用于诊断目的的图像配准。为了获取这些信息,需要提取组织的力学特性。在这项工作中,我们提出了一种基于有限元分析的迭代技术,该技术从不同体位(俯卧位和仰卧位)采集的 MRI 图像出发,仅在重力作用下对真实乳房模型进行变形,从而估计出弹性模量。我们分别使用单模态评估和多模态评估来验证该方法。在单模态评估中,我们模拟重力作用生成了四种不同的配置(俯卧位、仰卧位、侧卧位和垂直位),而在多模态评估中,我们模拟了一系列方向变化(从俯卧位到仰卧位)。验证分别在表面点和病变部位使用 MRI 图像的真实数据,以及在乳房模型内的目标病变部位与从 US 图像中分割出的实际目标进行。目前,术前图像的使用仅限于诊断目的。通过使用我们的方法,我们可以计算出患者特定的力学特性,从而补偿变形。