Institutional Repository of Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
A deep learning radiomics analysis for identifying sinus invasion in patients with meningioma before operation using tumor and peritumoral regions | |
Sun, Kai1,2; Zhang, Jing3; Liu, Zhenyu2,4; Qiu, Qi2; Gao, Han5; Liu, Panpan6; Chen, Kuntao3; Wei, Wei2; Wang, Liang6; Zhang, Junting6; Zhou, Junlin7; Tian, Jie1,2,4,5 | |
发表期刊 | EUROPEAN JOURNAL OF RADIOLOGY |
ISSN | 0720-048X |
2022-04-01 | |
卷号 | 149页码:7 |
通讯作者 | Wang, Liang(saintage7@126.com) ; Zhang, Junting(zhangjunting2003@aliyun.com) ; Zhou, Junlin(ery_zhoujl@lzu.edu.cn) ; Tian, Jie(jie.tian@ia.ac.cn) |
摘要 | Background: For patients with meningioma, surgical procedures are different because of the status of sinus invasion. However, there is still no suitable technique to identify the status of sinus invasion in patients with meningiomas. We aimed to build a deep learning radiomics model to identify sinus invasion before surgery.& nbsp;Methods: A total of 1048 patients with meningiomas were retrospectively enrolled from two hospitals. T1 enhanced-weighted (T1c) and T2-weighted MRI data for each patient were collected. Tumors and their corresponding peritumors were analyzed. Four ResNet50 models were built with different types of regions of interest (ROIs) (tumor and peritumor) and different modal images (T1c and T2) to predict the status of sinus invasion. Several data enhancement methods were applied before ResNet50 model building. The final model was generated by combining four ResNet50 models.& nbsp;Results: The models with a combination of tumors and peritumors using multimodal images achieved the highest predictive performance (AUC = 0.884, ACC = 78.1%) in the independent test cohort. The Delong test proved that the model built with combination ROIs achieved significantly higher performance than the model built only with tumors. The net reclassification improvement and integrated discrimination improvement tests both proved that including peritumor ROIs in the tumor ROIs could significantly improve the prediction ability.& nbsp;Conclusion: In the current study, the deep learning model showed potential for identifying sinus invasion before surgery in patients with meningioma. Including peritumors could significantly improve predictive performance. |
关键词 | Sinus invasion Meningioma ResNet50 Peritumoral Preoperative identification |
DOI | 10.1016/j.ejrad.2022.110187 |
关键词[WOS] | PREOPERATIVE EVALUATION ; VENOUS SYSTEMS ; VENOGRAPHY ; OUTCOMES |
收录类别 | SCI |
语种 | 英语 |
WOS研究方向 | Radiology, Nuclear Medicine & Medical Imaging |
WOS类目 | Radiology, Nuclear Medicine & Medical Imaging |
WOS记录号 | WOS:000784005600005 |
出版者 | ELSEVIER IRELAND LTD |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48388 |
专题 | 中国科学院分子影像重点实验室 |
通讯作者 | Wang, Liang; Zhang, Junting; Zhou, Junlin; Tian, Jie |
作者单位 | 1.Xidian Univ, Engn Res Ctr Mol & Neuro Imaging, Sch Life Sci & Technol, Minist Educ, Xian, Shaanxi, Peoples R China 2.Inst Automat, CAS Key Lab Mol Imaging, Beijing, Peoples R China 3.Zunyi Med Univ, Affiliated Hosp 5, Dept Radiol, Zhuhai, Peoples R China 4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 5.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med & Engn, Beijing 100191, Peoples R China 6.Capital Med Univ, Beijing Tiantan Hosp, Dept Neurosurg, Nansihuan Xilu 119, Beijing, Peoples R China 7.Lanzhou Univ, Hosp 2, Dept Radiol, Cuiyingmen 82, Lanzhou 730030, Peoples R China |
推荐引用方式 GB/T 7714 | Sun, Kai,Zhang, Jing,Liu, Zhenyu,et al. A deep learning radiomics analysis for identifying sinus invasion in patients with meningioma before operation using tumor and peritumoral regions[J]. EUROPEAN JOURNAL OF RADIOLOGY,2022,149:7. |
APA | Sun, Kai.,Zhang, Jing.,Liu, Zhenyu.,Qiu, Qi.,Gao, Han.,...&Tian, Jie.(2022).A deep learning radiomics analysis for identifying sinus invasion in patients with meningioma before operation using tumor and peritumoral regions.EUROPEAN JOURNAL OF RADIOLOGY,149,7. |
MLA | Sun, Kai,et al."A deep learning radiomics analysis for identifying sinus invasion in patients with meningioma before operation using tumor and peritumoral regions".EUROPEAN JOURNAL OF RADIOLOGY 149(2022):7. |
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