Prediction of IDH mutation status of glioma based on terahertz spectral data

Zhiyan Sun; Xianhao Wu; Rui Tao; Tianyao Zhang; Xing Liu; Jiangfei Wang; Haibin Wan; Shaowen Zheng; Xiaoyan Zhao; Zhaohui Zhang; Pei Yang

doi:10.1016/j.saa.2023.122629

Prediction of IDH mutation status of glioma based on terahertz spectral data

Spectrochim Acta A Mol Biomol Spectrosc. 2023 Jul 5:295:122629. doi: 10.1016/j.saa.2023.122629. Epub 2023 Mar 17.

Authors

Zhiyan Sun¹, Xianhao Wu², Rui Tao¹, Tianyao Zhang³, Xing Liu⁴, Jiangfei Wang⁵, Haibin Wan⁵, Shaowen Zheng², Xiaoyan Zhao⁶, Zhaohui Zhang⁷, Pei Yang¹

Affiliations

¹ Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
² School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China.
³ School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China; Beijing Engineering Research Center of Industrial Spectrum Imaging, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China.
⁴ Department of Pathology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
⁵ Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
⁶ School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China; Shunde Innovation School, University of Science and Technology Beijing, Foshan, China. Electronic address: zhaoxiaoyan@ustb.edu.cn.
⁷ School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China; Beijing Engineering Research Center of Industrial Spectrum Imaging, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China. Electronic address: zhangzhaohui@ustb.edu.cn.

PMID: 36958244
DOI: 10.1016/j.saa.2023.122629

Abstract

Gliomas are the most common type of primary tumor in the central nervous system in adults. Isocitrate dehydrogenase (IDH) mutation status is an important molecular biomarker for adult diffuse gliomas. In this study, we were aiming to predict IDH mutation status based on terahertz time-domain spectroscopy technology. Ninety-two frozen sections of glioma tissue from nine patients were included, and terahertz spectroscopy data were obtained. Through Least Absolute Shrinkage and Selection Operator (LASSO), Principal component analysis (PCA), and Random forest (RF) algorithms, a predictive model for predicting IDH mutation status in gliomas was established based on the terahertz spectroscopy dataset with an AUC of 0.844. These results indicate that gliomas with different IDH mutation status have different terahertz spectral features, and the use of terahertz spectroscopy can establish a predictive model of IDH mutation status, providing a new way for glioma research.

Keywords: Glioma; IDH mutation status; Machine learning; Terahertz spectra.

MeSH terms

Adult
Brain Neoplasms* / genetics
Brain Neoplasms* / pathology
Glioma* / genetics
Glioma* / pathology
Humans
Isocitrate Dehydrogenase / genetics
Magnetic Resonance Imaging / methods
Mutation

Substances

Isocitrate Dehydrogenase