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Liu Z, Hong X, Wang L, Ma Z, Guan F, Wang W, Qiu Y, Zhang X, Duan W, Wang M, Sun C, Zhao Y, Duan J, Sun Q, Liu L, Ding L, Ji Y, Yan D, Liu X, Cheng J, Zhang Z, Li ZC, Yan J. Radiomic features from multiparametric magnetic resonance imaging predict molecular subgroups of pediatric low-grade gliomas. BMC Cancer 2023; 23:848. [PMID: 37697238 PMCID: PMC10496393 DOI: 10.1186/s12885-023-11338-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 08/25/2023] [Indexed: 09/13/2023] Open
Abstract
BACKGROUND We aimed to develop machine learning models for prediction of molecular subgroups (low-risk group and intermediate/high-risk group) and molecular marker (KIAA1549-BRAF fusion) of pediatric low-grade gliomas (PLGGs) based on radiomic features extracted from multiparametric MRI. METHODS 61 patients with PLGGs were included in this retrospective study, which were divided into a training set and an internal validation set at a ratio of 2:1 based on the molecular subgroups or the molecular marker. The patients were classified into low-risk and intermediate/high-risk groups, BRAF fusion positive and negative groups, respectively. We extracted 5929 radiomic features from multiparametric MRI. Thereafter, we removed redundant features, trained random forest models on the training set for predicting the molecular subgroups or the molecular marker, and validated their performance on the internal validation set. The performance of the prediction model was verified by 3-fold cross-validation. RESULTS We constructed the classification model differentiating low-risk PLGGs from intermediate/high-risk PLGGs using 4 relevant features, with an AUC of 0.833 and an accuracy of 76.2% in the internal validation set. In the prediction model for predicting KIAA1549-BRAF fusion using 4 relevant features, an AUC of 0.818 and an accuracy of 81.0% were achieved in the internal validation set. CONCLUSIONS The current study demonstrates that MRI radiomics is able to predict molecular subgroups of PLGGs and KIAA1549-BRAF fusion with satisfying sensitivity. TRIAL REGISTRATION This study was retrospectively registered at clinicaltrials.gov (NCT04217018).
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Grants
- 2019YFC0117704 the National Key R&D Program of China
- 202102310136, 202102310138, 202102310113, 202102310083 the Science and Technology Program of Henan Province
- 202102310136, 202102310138, 202102310113, 202102310083 the Science and Technology Program of Henan Province
- 202102310136, 202102310138, 202102310113, 202102310083 the Science and Technology Program of Henan Province
- 82102149, U20A20171, 61901458, 61571432, 81702465, 8217111948, U1804172, U1904148 the National Natural Science Foundation of China
- 82102149, U20A20171, 61901458, 61571432, 81702465, 8217111948, U1804172, U1904148 the National Natural Science Foundation of China
- 82102149, U20A20171, 61901458, 61571432, 81702465, 8217111948, U1804172, U1904148 the National Natural Science Foundation of China
- 82102149, U20A20171, 61901458, 61571432, 81702465, 8217111948, U1804172, U1904148 the National Natural Science Foundation of China
- 2021B0101420006 the Key-Area Research and Development Program of Guangdong Province
- YXKC2022061 the Excellent Youth Talent Cultivation Program of Innovation in Health Science and Technology of Henan Province
- SBGJ202002062 the Key Program of Medical Science and Technique Foundation of Henan Province
- the National Key R&D Program of China
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Affiliation(s)
- Zhen Liu
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Jian she Dong Road 1, Zhengzhou, 450052, Henan province, China
| | - Xuanke Hong
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Jian she Dong Road 1, Zhengzhou, 450052, Henan province, China
| | - Linglong Wang
- Yanjing Medical College of Capital Medical University, Beijing, China
| | - Zeyu Ma
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Jian she Dong Road 1, Zhengzhou, 450052, Henan province, China
| | - Fangzhan Guan
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Jian she Dong Road 1, Zhengzhou, 450052, Henan province, China
| | - Weiwei Wang
- Department of Pathology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Yuning Qiu
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Jian she Dong Road 1, Zhengzhou, 450052, Henan province, China
| | - Xueping Zhang
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Jian she Dong Road 1, Zhengzhou, 450052, Henan province, China
| | - Wenchao Duan
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Jian she Dong Road 1, Zhengzhou, 450052, Henan province, China
| | - Minkai Wang
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Jian she Dong Road 1, Zhengzhou, 450052, Henan province, China
| | - Chen Sun
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Jian she Dong Road 1, Zhengzhou, 450052, Henan province, China
| | - Yuanshen Zhao
- Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jingxian Duan
- Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Qiuchang Sun
- Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Lin Liu
- China-Japan Union Hospital of Jilin University, Changchun, Jilin, China
| | - Lei Ding
- China-Japan Union Hospital of Jilin University, Changchun, Jilin, China
| | - Yuchen Ji
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Jian she Dong Road 1, Zhengzhou, 450052, Henan province, China
| | - Dongming Yan
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Jian she Dong Road 1, Zhengzhou, 450052, Henan province, China
| | - Xianzhi Liu
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Jian she Dong Road 1, Zhengzhou, 450052, Henan province, China
| | - Jingliang Cheng
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Jian she Dong Road 1, Zhengzhou, 450052, Henan province, China
| | - Zhenyu Zhang
- Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Jian she Dong Road 1, Zhengzhou, 450052, Henan province, China.
| | - Zhi-Cheng Li
- Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
- University of Chinese Academy of Sciences, Beijing, China.
- Shenzhen United Imaging Research Institute of Innovative Medical Equipment, Shenzhen, 518045, China.
| | - Jing Yan
- Department of MRI, The First Affiliated Hospital of Zhengzhou University, Jian she Dong Road 1, Zhengzhou, 450052, Henan province, China.
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