Multiscale three-dimensional modeling of ultrasound cancer imaging

超声成像技术的不断改进为超声在医学成像中扮演新角色创造了机会。 超声的新用途可以带来巨大的医疗保健益处，因为与其他成像技术相比，超声在成本、可及性以及患者安全性和舒适度方面具有优势。 我们的研究团队正在创建一个全面的计算机模拟资源，用于开发提高超声癌症成像能力的方法。 模拟将使用西南安大略高性能计算设施SHARCNET。 将设计和测试软件，以便对肿瘤和周围组织的大体和微观解剖结构进行三维建模，并准确、有效地模拟超声成像的物理过程。 组织和肿瘤模型将被设计用于研究超声技术正在迅速发展的两个主题：乳腺癌检测和癌症研究中使用的小动物的高分辨率成像。 乳腺癌模拟将研究提高超声筛查小肿瘤能力的方法。 这种能力对于40岁以下的患者尤其有价值，因为患乳腺癌的年轻女性通常具有最具侵袭性的肿瘤，而乳房X光检查通常会产生令人不满意的年轻患者图像。 小动物成像模拟将用于定义更可靠的方法，以在实验室中评估新的癌症疗法。 小动物成像有可能通过确保只选择最有前途的药物用于人类患者的临床试验来加速和降低癌症药物开发的成本。 在这两个领域，现有的超声成像计算机和实验模型都依赖于组织物理特性的理想化，而我们的研究团队建立的计算方法中避免了这一点。 我们希望，拟议的模拟平台将提供一个有价值的工具，解决这些和其他具有挑战性的问题，在癌症成像。

The continuing improvement of ultrasound imaging technology creates opportunities for ultrasound to fill new roles in medical imaging. Substantial health care benefits can result from new uses of ultrasound, because ultrasound provides advantages in cost, accessibility, and patient safety and comfort compared to other imaging technologies. Our research team is creating a comprehensive computer simulation resource for use in developing methods to improve the cancer imaging capabilities of ultrasound. The simulations will use a Southwestern Ontario high-performance computing facility, SHARCNET. Software will be designed and tested for three-dimensional modeling of the gross and microscopic anatomy of tumours and surrounding tissues and accurate, efficient simulation of the physics of ultrasound image formation. The tissue and tumour models will be designed for research on two topics where ultrasound technology is rapidly advancing: breast cancer detection and high-resolution imaging of small animals used in cancer research. The breast cancer simulations will investigate methods to improve the ability of ultrasound to screen for small tumours. This capability would be especially valuable for patients younger than 40 years, because young women who develop breast cancer generally have the most aggressive tumours and mammography often produces unsatisfactory images of young patients. The small animal imaging simulations will be used to define more reliable methods to evaluate new cancer therapies in the laboratory. Small animal imaging has the potential to accelerate and reduce the costs of cancer drug development by ensuring that only the most promising drugs are selected for clinical trials in human patients. In both of these areas, existing computer and experimental models for ultrasound imaging rely on idealizations of the physical properties of tissue that are avoided in the computational methods established by our research team. We expect that the proposed simulation platform will provide a valuable tool for addressing these and other challenging issues in cancer imaging.