BMC Cancer (Jan 2023)
Risk stratification and prognostic value of multi-modal MRI-based radiomics for extranodal nasal-type NK/T-cell lymphoma
- Yu-Ting Zhao,
- Si-Ye Chen,
- Xin Liu,
- Yong Yang,
- Bo Chen,
- Yong-Wen Song,
- Hui Fang,
- Jing Jin,
- Yue-Ping Liu,
- Hao Jing,
- Yuan Tang,
- Ning Li,
- Ning-Ning Lu,
- Shu-Lian Wang,
- Han Ouyang,
- Chen Hu,
- Jin Liu,
- Zhi Wang,
- Fan Chen,
- Lin Yin,
- Qiu-Zi Zhong,
- Kuo Men,
- Jian-Rong Dai,
- Shu-Nan Qi,
- Ye-Xiong Li
Affiliations
- Yu-Ting Zhao
- State Key Laboratory of Molecular Oncology and Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC)
- Si-Ye Chen
- State Key Laboratory of Molecular Oncology and Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC)
- Xin Liu
- State Key Laboratory of Molecular Oncology and Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC)
- Yong Yang
- State Key Laboratory of Molecular Oncology and Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC)
- Bo Chen
- State Key Laboratory of Molecular Oncology and Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC)
- Yong-Wen Song
- State Key Laboratory of Molecular Oncology and Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC)
- Hui Fang
- State Key Laboratory of Molecular Oncology and Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC)
- Jing Jin
- State Key Laboratory of Molecular Oncology and Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC)
- Yue-Ping Liu
- State Key Laboratory of Molecular Oncology and Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC)
- Hao Jing
- State Key Laboratory of Molecular Oncology and Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC)
- Yuan Tang
- State Key Laboratory of Molecular Oncology and Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC)
- Ning Li
- State Key Laboratory of Molecular Oncology and Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC)
- Ning-Ning Lu
- State Key Laboratory of Molecular Oncology and Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC)
- Shu-Lian Wang
- State Key Laboratory of Molecular Oncology and Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC)
- Han Ouyang
- Department of Diagnostic Imaging, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC)
- Chen Hu
- Division of Biostatistics and Bioinformatics, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine
- Jin Liu
- Blot Info & Tech (Beijing) Co. Ltd
- Zhi Wang
- Blot Info & Tech (Beijing) Co. Ltd
- Fan Chen
- Department of Radiation Oncology, Affiliated Hospital of Qinghai University
- Lin Yin
- Department of Radiation Oncology, Affiliated Hospital of Qinghai University
- Qiu-Zi Zhong
- Department of Radiation Oncology, Beijing Hospital, National Geriatric Medical Center
- Kuo Men
- State Key Laboratory of Molecular Oncology and Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC)
- Jian-Rong Dai
- State Key Laboratory of Molecular Oncology and Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC)
- Shu-Nan Qi
- State Key Laboratory of Molecular Oncology and Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC)
- Ye-Xiong Li
- State Key Laboratory of Molecular Oncology and Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital,, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC)
- DOI
- https://doi.org/10.1186/s12885-023-10557-3
- Journal volume & issue
-
Vol. 23,
no. 1
pp. 1 – 11
Abstract
Abstract Background Magnetic resonance imaging (MRI) performs well in the locoregional assessment of extranodal nasal-type NK/T-cell lymphoma (ENKTCL). It’s important to assess the value of multi-modal MRI-based radiomics for estimating overall survival (OS) in patients with ENKTCL. Methods Patients with ENKTCL in a prospectively cohort were systemically reviewed and all the pretreatment MRI were acquisitioned. An unsupervised spectral clustering method was used to identify risk groups of patients and radiomic features. A nomogram-revised risk index (NRI) plus MRI radiomics signature (NRI-M) was developed, and compared with the NRI. Results The 2 distinct type I and II groups of the MRI radiomics signatures were identified. The 5-year OS rates between the type I and type II groups were 87.2% versus 67.3% (P = 0.002) in all patients, and 88.8% versus 69.2% (P = 0.003) in early-stage patients. The discrimination and calibration of the NRI-M for OS prediction demonstrated a better performance than that of either MRI radiomics or NRI, with a mean area under curve (AUC) of 0.748 and 0.717 for predicting the 5-year OS in all-stages and early-stage patients. Conclusions The NRI-M model has good performance for predicting the prognosis of ENKTCL and may help design clinical trials and improve clinical decision making.
Keywords