Feasibility study on detecting lung tumour in multilayer thorax model using ultra-wideband microwave imaging

Abstract

The constant exposure to pathogens and carcinogenic substances through inhaled gases makes the lungs very vulnerable to diseases such as asthma, tuberculosis and cancer. Available statistics revealed there were 14.1 million cases of cancer reported worldwide in the year 2012 and out of this figure, 13% were attributed to new cases of lung cancer. Despite the high figures of the new cases of detected lung cancer, many other cases would have passed undetected as symptoms of early stages of lung cancer are common with other diseases of the lungs such as tuberculosis. Lung cancer is the leading cause of death related cancers worldwide as the cancer of the lung is very difficult to cure. Screening for lung cancer is not routinely done and although X-ray and computer tomography scan can detect small sized cancers in the lungs, they are not required until symptoms have advanced in patients. Other methods for lung cancer screening like biopsies and bronchoscopies are only required when suspicious irregularities are observed in images generated from X-ray. In recent times however, microwave imaging techniques are being proposed for detection of various forms of cancer. The detection of cancer using microwaves in the frequency range of 300 MHz to 30 GHz is possible iin the premise that the dielectric properties of tumour tissues are different from the normal host tissues. These contrasts in dielectric properties are being explored in microwave tomography, ultra-wideband (UWB) microwave imaging radar, radiometry, and thermoacoustic tomography. This thesis presents a study in using confocal microwave imaging technique which itself is a form of the UWB microwave imaging radar to detect millimetre sized tumour in the human lungs. The detection system comprises of a human thorax modelled as multilayer tissues of lung, bone, muscle, fat and skin; a 10 mm tumour; a UWB antenna connected to a vector network analyser; and a proposed modified delay and sum (mDAS) imaging algorithm for signal processing and image reconstruction purposes. Reconstructed microwave images show the possibility of detecting tumours in lung in both simulation and experimental procedures. Using a proposed location error approximation, errors of tumour location in the microwave images was less than 3 cm. The proposed mDAS was compared to the standard delay and sum (DAS) imaging algorithm using signal to clutter ratio, and it was found that the mDAS has a 2-3 dB better resolution in the microwave images. Microwave imaging techniques may not necessarily replace other known gold standards for cancer detection, but will definitely be a first step in diagnosis and will be complementary to other detection systems. The imaging technique presented in this report can be adjudged to be fast as the image reconstruction was about 120 seconds on a standard computer; it was safe from non-ionizing radiations and also, it was easy to perform.