Lung cancer (LC) incidence represents 11.5% of all new cancers, resulting in 1.72 million deaths worldwide in 2015. With the aim to investigate the capability of the electronic nose (e-nose) technology for detecting and differentiating complex mixtures of volatile organic compounds in biofluids ex-vivo, we enrolled 50 patients with suspected LC and 50 matching controls. Tissue biopsy was taken from suspicious lung mass for histopathological evaluation and blood, exhaled breath, and urine samples were collected from all participants and qualitatively processed using e-nose. Odor-print patterns were further analysed using the principal component analysis (PCA) and artificial neural network (ANN) analysis. Adenocarcinoma, non-small cell LC and squamous cell carcinoma were the predominant pathological types among LC patients. PCA cluster-plots showed a clear distinction between LC patients and controls for all biological samples; where the overall success ratios of classification for principal components #1 and #2 were: 95.46, 82.01, and 91.66% for blood, breath and urine samples, respectively. Moreover, ANN showed a better discrimination between LC patients and controls with success ratios of 95.74, 91.67 and 100% for blood, breath and urine samples, respectively. The e-nose is an easy noninvasive tool, capable of identifying LC patients from controls with great precision.

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miR-155 was highly overexpressed, yet it did not correlate with stages, while miR-486- 5p was extremely underexpressed and significantly correlated with stages of LC. Thus, their detection represents an excellent diagnostic/prognostic tool to support more established techniques linked to LC spread locally and systemically.

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Hyperthermia therapy is a promising therapy for liver cancer treatment that utilizes external electromagnetic waves to heat the tumor zone to preferentially kill or minimize cancer cells. Nevertheless, it’s a challenge to realize localized heating of the cancer tissue without harming the surrounding healthy tissue. This research proposes to utilize nanoparticles as microwave absorbers to enhance microwave imaging and achieve localized hyperthermia therapy. A realistic 3D abdomen model has been segmented using 3D Slicer segmentation software, and then the obtained segmented CAD model exported to Computer Simulation Technology (CST STUDIO) for applying the Finite Element Modeling (FEM). Next investigating both imaging and treatment capability. Finally, the specific absorption rate (SAR) and temperature distribution were computed without nanoparticles and with different types of nanoparticles such as gold (GNPs) and silver nanoparticles at frequency 915 MHz. By comparing the achived results, it was seen that Silver nanoparticles can make a great enhancement in raising the temperature. However, this result was unsatisfactory but, after adding gold nanoparticles the temperature exceed 42°C, at frequency 915 MHz which is achieving the hyperthermia treatment without harming the nearby healthy tissue, GNPs also can achieve a great enhancement in SAR result