https://scholars.lib.ntu.edu.tw/handle/123456789/625055
標題: | Machine learning-based evaluation of cancer pain from functional brain images | 作者: | Ogawa, Mayuko Ben, Hui Ono, Yumie WEN-YING LIN |
關鍵字: | cancer pain | evaluation | functional brain image | machine learning | PET | 公開日期: | 1-一月-2021 | 卷: | Annual59 | 期: | Proc | 來源出版物: | Transactions of Japanese Society for Medical and Biological Engineering | 摘要: | Pain management is one of the important treatments of cancer patients. This study aims to develop a classifier of chronic cancer pain patients from their brain metabolic activity measured by FDG-PET. We compared FDG-PET brain images of 74 painful and 29 painless cancer patients to clarify the brain activity specific to chronic pain of cancer. Using the detected brain activity pattern, we further developed a classifier that determines the presence or absence of chronic pain from PET brain images by machine learning methods. The painful cancer patients showed significantly increased activity in the amygdala, hippocampus, and decreased activity in the cingulate gyrus and precuneus (p < 0.001, uncorrected). The proposed classifier was able to identify patients with chronic pain with a sensitivity and specificity of 85.1% and 62.1%, respectively. Further research is required to improve the specificity by selecting better regions of interest and classification algorithms. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/625055 | ISSN: | 18814379 | DOI: | 10.11239/jsmbe.Annual59.780 |
顯示於: | 醫學院附設癌醫中心醫院(臺大癌醫) |
在 IR 系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。