Abstract
Lung cancer is the most lethal cancer in the world. Intensive research is ongoing worldwide to identify new therapies for lung cancer. Several mouse models of lung cancer are being used to study the mechanism of cancer development and to experiment with various therapeutic strategies. However, the absence of a real-time technique to identify the development of tumor nodules in mice lungs and to monitor the changes in their size in response to various experimental and therapeutic interventions hampers the ability to obtain an accurate description of the course of the disease and its timely response to treatments. In this study, a method using a micro-computed tomography (CT) scanner for the detection of the development of lung tumors in a mouse model of lung adenocarcinoma is described. Next, we show that monthly follow-up with micro-CT can identify dynamic changes in the lung tumor, such as the appearance of additional nodules, increase in the size of previously detected nodules, and decrease in the size or complete resolution of nodules in response to treatment. Finally, the accuracy of this real-time assessment method was confirmed with end-point histological quantification. This technique paves the way for planning and conducting more complex experiments on lung cancer animal models, and it enables us to better understand the mechanisms of carcinogenesis and the effects of different treatment modalities while saving time and resources.