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Proceedings Paper

Non-invasive genotype prediction of chromosome 1p/19q co-deletion by development and validation of an MRI-based radiomics signature in lower-grade gliomas
Author(s): Yuqi Han; Zhen Xie; Yali Zang; Shuaitong Zhang; Dongsheng Gu; Jingwei Wei; Chao Li; Hongyan Chen; Jiang Du; Di Dong; Jie Tian; Dabiao Zhou
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Paper Abstract

To pre-operatively and non-invasively predict 1p/19q co-deletion in grade II and III (lower-grade) glioma based on a radiomics method using magnetic resonance imaging (MRI). We obtained 105 patients pathologically diagnosed with lower-grade glioma. We extracted 647 MRI-based features from T2-weighted images and selected discriminative features by lasso logistic regression approaches on the training cohort (n=69). Radiomics, clinical, and combined models were constructed separately to verify the predictive performance of the radiomics signature. The predictability of the three models were validated on a time-independent validation cohort (n = 36). Finally, 7 discriminative radiomic features were used constructed radiomics signature, which demonstrated satisfied performance on both the training and validation cohorts with AUCs of 0.822 and 0.731, respectively. Particularly, the combined model incorporating the radiomics signature and the clinic-radiological factors achieved the best discriminative capability with AUCs of 0.911 and 0.866 for training and validation cohorts, respectively.

Paper Details

Date Published: 13 March 2019
PDF: 6 pages
Proc. SPIE 10950, Medical Imaging 2019: Computer-Aided Diagnosis, 109502B (13 March 2019); doi: 10.1117/12.2511501
Show Author Affiliations
Yuqi Han, Xidian Univ. (China)
Institute of Automation (China)
Beijing Key Lab. of Molecular Imaging (China)
Zhen Xie, Beijing Tiantan Hospital, Capital Medical Univ. (China)
Yali Zang, Institute of Automation (China)
Beijing Key Lab. of Molecular Imaging (China)
Univ. of Chinese Academy Sciences (China)
Shuaitong Zhang, Institute of Automation (China)
Beijing Key Lab. of Molecular Imaging (China)
Univ. of Chinese Academy of Sciences (China)
Dongsheng Gu, Institute of Automation (China)
Beijing Key Lab. of Molecular Imaging (China)
Univ. of Chinese Academy of Sciences (China)
Jingwei Wei, Institute of Automation (China)
Beijing Key Lab. of Molecular Imaging (China)
Univ. of Chinese Academy of Sciences (China)
Chao Li, Beijing Tiantan Hospital, Capital Medical Univ. (China)
Hongyan Chen, Beijing Neurosurgical Institute, Capital Medical Univ. (China)
Jiang Du, Capital Medical Univ. (China)
Di Dong, Institute of Automation (China)
Univ. of Chinese Academy of Sciences (China)
Jie Tian, Institute of Automation (China)
Univ. of Chinese Academy of Sciences (China)
Dabiao Zhou, Beijing Tiantan Hospital, Capital Medical Univ. (China)
China National Clincal Research Ctr. for Neurological Diseases (China)


Published in SPIE Proceedings Vol. 10950:
Medical Imaging 2019: Computer-Aided Diagnosis
Kensaku Mori; Horst K. Hahn, Editor(s)

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