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Published in:
2020 | OriginalPaper | Chapter
Automatic Classification of Lymph Node Metastasis in Non-Small-Cell Lung Cancer (NSCLC) Patient on F-18-FDG PET/CT
Authors : Tsu-Chi Cheng, Nan-Tsing Chiu, Yu-Hua Fang
Published in: Future Trends in Biomedical and Health Informatics and Cybersecurity in Medical Devices
Publisher: Springer International Publishing
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Abstract
Lung Cancer is a leading cause of death worldwide, and about 85% of lung cancer is non-small cell lung cancer (NSCLC). The staging of lymph nodes in NSCLC patients is extremely important because respective stages require different treatments. FDG-PET/CT is a gold standard for lymph node metastasis staging of NSCLC. However, the results of discriminating lymph node staging on 18F-2-fluoro-2-deoxy-d-glucose (FDG) positron emission tomography (PET)/computed tomography (CT) still needs improvement. In addition to the traditional image parameters of FDG-PET/CT such as standardized uptake value (SUV), there are many other parameters available from FDG-PET/CT images, for example, the lymphatic drainage pathway. For the purpose of a better accuracy on lymph node metastasis diagnosis on NSCLC patient in FDG-PET/CT, this research developed a computer-aided diagnosis (CAD) system to improve the diagnostic efficiency, which achieved an accuracy of 85%, a sensitivity of 82% and a specificity of 85%.