Large aperture and wideband modular ultrasound arrays for the diagnosis of liver cancer

我们的项目有两个基本目标：1)开发模块化大口径、高通道数阵列， 相关的电子产品，并使这些模块广泛提供给学术界，以及2)使用这些 改善腹部超声(US)诊断肝癌，特别是难以成像的肝癌的阵列 病人。原发性肝癌患者的总体5年相对存活率为16%。在许多情况下， 成像用于监测由病毒感染或肝硬变引起的肝病，并检测向 恶性肿瘤，而超声波是唯一推荐的筛查这类癌症风险的方法。 然而，在腹壁厚度大于2.5厘米的患者中，只有33%的病变被检测到。更多 超过三分之二的美国人现在超重或肥胖，通道数阵列更大，阵列占用空间更大 将改善这一人群中的成像以及总体上改善对小病变的检测 人口。我们的方法解决了更高的分辨率(大孔径和带宽)、灵敏度(单一 晶体传感器)、用于超分辨率成像的高帧速率(数百帧/秒可行)、成品率(阵列 由高成品率模块组成)和图像对比度(新的切换功能支持新的波束形成 方法)。横向US分辨率与换能器孔径成反比，因此， 提高分辨率需要增加传感器元件和电子通道的数量，以及 先进的波束形成方法。即使在存在异常组织的情况下，我们也表明对比度 通过扩展的光圈实现，便于对小结构的可视化。我们建议创建个人识别码- 将组合的尺寸为16个元素(方位角)乘32个元素(仰角)的PMN-PT阵列模块 形成大型阵列。用户可选择的ASIC矩阵提供了从以下选项中选择512个元素的机会 在单个模块中，组合立面中的镜像元素或组合中的相邻元素 方位角或仰角。结果，大口径阵列内的4096个元素可以同时被 来自可编程扫描仪的地址。我们的具体目标跨越了大面积阵列的发展 技术，整合该技术以创建适用于腹部的大面积凹形阵列 成像和使用由此产生的技术来检测肝癌。初步工作的结果是 样机阵列和ASIC模块的制作。加州大学戴维斯分校的团队是第一批生产 多频阵列；南加州大学是高频阵列的先驱，目前是Wodicki的大本营(20年 GE在超声ASIC开发方面的经验)，并将与我们合作开发High 通道计数阵列；杜克大学率先开发了使用大孔径的策略； Verasonics是可编程超声系统的领先制造商，将与我们合作开发 并将其分发给超声波社区。这个独特的团队将开发这项技术， 评估它在人体研究中的使用，并将传播这项技术。

Our project has two fundamental goals: 1) develop modular large aperture, high channel count arrays with associated electronics and make these modules widely available to the academic community, and 2) use these arrays to improve abdominal ultrasound (US) for the diagnosis of liver cancer, particularly for difficult to image patients. The overall 5-year relative survival rate for patients with primary liver cancer is 16%. In many cases, imaging is used to monitor liver disease resulting from viral infections or cirrhosis and to detect a transition to malignancy, and ultrasound is the only recommended method for screening such patients at risk for cancer. Yet, in patients with an abdominal wall thickness greater than 2.5 cm, only 33% of lesions were detected. More than 2/3 of Americans are now overweight or obese and larger channel count arrays and larger array footprints will improve imaging within this population as well as improving the detection of small lesions in the general population. Our approach addresses improved resolution (large aperture and bandwidth), sensitivity (single crystal transducers), high frame rate for super-resolution imaging (hundreds of frame/sec feasible), yield (array is composed of high yield modules), and image contrast (new switching capabilities enable new beamformation methods). Lateral US resolution is inversely proportional to the transducer aperture and consequently, improved resolution requires an increased number of transducer elements and electronic channels as well as advanced beam formation methods. Even in the presence of aberrating tissues we show that the contrast achieved from an extended aperture facilitates the visualization of small structures. We propose to create PIN- PMN-PT array modules of dimension 16 elements (azimuth) by 32 elements (elevation) which will be combined to form large arrays. The user selectable ASIC matrices provide the opportunity to select: 512 elements from within a single module, to combine mirrored elements in elevation or to combine neighboring elements in azimuth or elevation. As a result, 4096 elements within the large aperture array can simultaneously be addressed from a programmable scanner. Our specific aims span the development of the large area array technology, the integration of that technology to create large area concave arrays adapted for abdominal imaging and the use of the resulting technology to detect liver cancer. Preliminary work has resulted in the fabrication of prototype array and ASIC modules. The UC Davis team has been one of the first to produce multi-frequency arrays; USC has pioneered high frequency arrays and is currently home to Wodnicki (20 years of experience in ultrasound ASIC development at GE) and will collaborate with us on the development of high channel count arrays; Duke University has pioneered the development of strategies to use large apertures; Verasonics is the leading manufacturer of programmable ultrasound systems and will work with us to develop the technology and to distribute it to the ultrasound community. This unique team will develop the technology, evaluate its use in a human study and will disseminate the technology.