Development of non-invasive diagnostic medical technologies

非侵入性疾病诊断技术在医学领域发挥着越来越重要的作用。在过去的几年里，基于乳腺组织电磁特性的乳腺癌早期检测越来越受到人们的关注。正常组织和癌症的特性预计是不同的；恶性和良性组织的特性差异可能被用来区分癌症和非癌症病变。卡尔加里大学正在开发一种使用电磁特性检测乳腺癌的方法，组织传感自适应雷达(TSAR)。这项微波技术基于超宽带(UWB)雷达系统。基本上，微波脉冲被传输到乳房并收集反射。由于肿瘤和健康组织的电磁特性不同，预计肿瘤的反射会增加。在去除不需要的信号后，反射被聚焦，以便在三维上定位肿瘤。由于不涉及乳房压迫或电离辐射，因此沙皇方法对患者友好。到目前为止，我们的工作表明沙皇是一项很有前途的技术。我们已经进行了模拟和实验数据的研究。我们已经为实验工作开发了一个实验室原型系统，包括一个简单的乳房模型或体模，一个扫描模型的系统和一个发送和接收脉冲的天线。结果表明，成功地检测和定位了肿瘤模型。沙皇研究的下一步是开发临床原型，本研究项目旨在实现一个适用于扫描志愿者的沙皇系统。该原型包括开发符合人体工程学的患者界面和改进的沙皇成像算法。此外，我们还提出探索沙皇技术在其他疾病诊断和非侵入性传感等领域的应用。

Non-invasive technologies for the diagnosis of disease are playing an increasingly important role in the medical field.  In the past several years, early detection of breast cancer based on the electromagnetic properties of breast tissues has become of increasing interest. The properties of normal tissues and cancers are expected to differ; differences in the properties of malignant and benign tissues may be used to differentiate cancers from non-cancerous lesions.  One approach to breast cancer detection using electromagnetic properties, Tissue Sensing Adaptive Radar (TSAR), is under development at the University of Calgary.  This microwave technology is based on an ultra-wideband (UWB) radar system.  Essentially, short pulses of microwaves are transmitted into the breast and reflections are collected.  Increased reflections are expected from tumours, due to the differences in electromagnetic properties of tumours and healthy tissues. After reduction of unwanted signals, the reflections are focused in order to locate tumours in three dimensions.  The TSAR approach is patient-friendly, as it does not involve breast compression or ionizing radiation.To date, our work indicates that TSAR is a promising technology.  Studies with both simulated and experimental data have been performed.  A laboratory prototype system has been developed for experimental work, consisting of a simple breast model or phantom, a system for scanning the model and an antenna to send and receive pulses.  Results demonstrate successful detection and localization of tumour models.  The next step in TSAR research is development of a clinical prototype, and this research project aims to implement a TSAR system suitable for scanning volunteers.  This prototype includes development of an ergonomic patient interface and improved TSAR imaging algorithms.  In addition, we propose to explore the application of the TSAR technology to areas such as diagnosis of other diseases and non-invasive sensing.