精细三维光声模拟的乳腺肿瘤光声断层扫描表现(会议报告)

M. Dantuma, F. Lucka, J. Jaros, Bradley E. Teeby, B. Cox, S. Manohar
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引用次数: 2

摘要

光声乳房成像已经发展了十多年,并逐步走向临床,研究其在肿瘤检测和诊断中的性能。已经建立了几种类型的系统,它们都有自己的特点和相应的成像性能。不同的研究已经观察到肿瘤外观的变化。一些作品在肿瘤区域看到周围血管,而另一些作品在肿瘤部位显示肿块样外观。这些不同的肿瘤表现可能是由系统特征的偏差引起的,但也可能是由肿瘤的解剖差异引起的。虽然我们仍然可以从体内研究中学到很多东西,但需要精确的模拟研究来全面详细地了解肿瘤的外观。我们开发了一个模拟工具箱来进行三维全乳房光声模拟。为了研究肿瘤的外观,将几个肿瘤模型嵌入mri分割的数字乳房假体中[Y]。Lou等人(2017)],它悬挂在一个充满水的半球形成像箱中。在成像碗的表面放置照明纤维和US探测器。工具箱方便地允许调整激光和探测器的特性。乳房的照明用gpu加速蒙特卡罗模拟模拟[Q]。Fang et al.(2009)。随后的声信号产生和传播用k波(gpu加速,B.E.)建模Treeby et al.(2010)]。最后,重建图像以评估肿瘤的外观。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Breast tumor appearances in photoacoustic tomography from fine 3D optical-acoustic simulations (Conference Presentation)
Photoacoustic breast imaging has been under development for more than a decade now, and is progressively moving towards the clinics to investigate its performance in tumor detection and diagnosis. Several system types have been built, all with their own characteristics and corresponding imaging performances. Different studies have observed variations in tumor appearances. Some works have seen peripheral blood vessels in the tumor region, while others showed mass-like appearances at the tumor site. These varying tumor presentations may be caused by the deviations in system characteristics, but can also be caused by anatomical differences of the tumors. While we can still learn a lot from in-vivo studies, accurate simulation studies are needed to understand the tumor appearances in full detail. We have developed a simulation toolbox to perform 3D full breast photoacoustic simulations. To investigate the tumor appearance, several tumor models are embedded inside a MRI-segmented digital breast phantom [Y. Lou et al (2017)], which is pendant in a hemispherical imaging tank filled with water. Illumination fibers and US detectors are placed on the surface of the imaging bowl. The toolbox easily allows to adjust laser and detector characteristics. Illumination of the breast is simulated with GPU-accelerated Monte Carlo simulations [Q. Fang et al. (2009)]. The subsequent acoustic signal generation and propagation is modeled with k-wave (GPU-accelerated, [B.E. Treeby et al. (2010)]). Finally, images are reconstructed to evaluate the tumor appearance.
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