Institutional Repository of Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
| Preoperative Prediction of Malignant Transformation of Sinonasal Inverted Papilloma Using MR Radiomics | |
Yan, Yang1; Liu, Yujia2,3; Tao, Jianhua1 ; Li, Zheng1; Qu, Xiaoxia1; Guo, Jian1; Xian, Junfang1
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| Source Publication | FRONTIERS IN ONCOLOGY
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| ISSN | 2234-943X |
| 2022-03-23 | |
| Volume | 12Pages:10 |
| Corresponding Author | Xian, Junfang(cjr.xianjunfang@vip.163.com) |
| Abstract | PurposeAccurate preoperative prediction of the malignant transformation of sinonasal inverted papilloma (IP) is essential for guiding biopsy, planning appropriate surgery and prognosis of patients. We aimed to investigate the value of MRI-based radiomics in discriminating IP from IP-transformed squamous cell carcinomas (IP-SCC). MethodsA total of 236 patients with IP-SCC (n=92) or IP (n=144) were enrolled and divided into a training cohort and a testing cohort. Preoperative MR images including T1-weighted, T2-weighted, and contrast enhanced T1-weighted images were collected. Radiomic features were extracted from MR images and key features were merged into a radiomic model. A morphological features model was developed based on MR morphological features assessed by radiologists. A combined model combining radiomic features and morphological features was generated using multivariable logistic regression. For comparison, two head and neck radiologists were independently invited to distinguish IP-SCC from IP. The area under the receiver operating characteristics curve (AUC) was used to assess the performance of all models. ResultsA total of 3948 radiomic features were extracted from three MR sequences. After feature selection, we saved 15 key features for modeling. The AUC, sensitivity, specificity, and accuracy on the testing cohort of the combined model based on radiomic and morphological features were respectively 0.962, 0.828, 0.94, and 0.899. The diagnostic ability of the combined model outperformed the morphological features model and also outperformed the two head and neck radiologists. ConclusionsA combined model based on MR radiomic and morphological features could serve as a potential tool to accurately predict IP-SCC, which might improve patient counseling and make more precise treatment planning. |
| Keyword | inverted papilloma (IP) squamous cell carcinoma sinonasal cancer radiomics magnetic resonance imaging |
| DOI | 10.3389/fonc.2022.870544 |
| WOS Keyword | SQUAMOUS-CELL CARCINOMA ; MANAGEMENT ; DIAGNOSIS ; FEATURES ; OUTCOMES |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | National Key Ramp;D Program of China[2017YFA0205200] ; National Key Ramp;D Program of China[2017YFC1308700] ; National Key Ramp;D Program of China[2017YFA0700401] ; National Key Ramp;D Program of China[2017YFC1309100] ; National Natural Science Foundation of China[82022036] ; National Natural Science Foundation of China[91959130] ; National Natural Science Foundation of China[81971776] ; National Natural Science Foundation of China[81771924] ; National Natural Science Foundation of China[62027901] ; National Natural Science Foundation of China[81930053] ; National Natural Science Foundation of China[81227901] ; Beijing Natural Science Foundation[L182061] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB 38040200] ; Chinese Academy of Sciences[GJJSTD20170004] ; Chinese Academy of Sciences[QYZDJ-SSW-JSC005] ; Project of High-Level Talents Team Introduction in Zhuhai City (Zhuhai)[HLHPTP201703] ; Youth Innovation Promotion Association CAS[2017175] ; Beijing Municipal Administration of HospitalsAscent Plan[DFL20190203] ; Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support[ZYLX201704] ; High Level Health Technical Personnel of Bureau of Health in Beijing[2014-2-005] |
| Funding Organization | National Key Ramp;D Program of China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Chinese Academy of Sciences ; Project of High-Level Talents Team Introduction in Zhuhai City (Zhuhai) ; Youth Innovation Promotion Association CAS ; Beijing Municipal Administration of HospitalsAscent Plan ; Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support ; High Level Health Technical Personnel of Bureau of Health in Beijing |
| WOS Research Area | Oncology |
| WOS Subject | Oncology |
| WOS ID | WOS:000780731400001 |
| Publisher | FRONTIERS MEDIA SA |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ia.ac.cn/handle/173211/48364 |
| Collection | 中国科学院分子影像重点实验室 |
| Corresponding Author | Xian, Junfang |
| Affiliation | 1.Capital Med Univ, Beijing Tongren Hosp, Dept Radiol, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 3.Chinese Acad Sci, Chinese Acad Sci Key Lab Mol Imaging, Inst Automat, Beijing, Peoples R China |
| Recommended Citation GB/T 7714 | Yan, Yang,Liu, Yujia,Tao, Jianhua,et al. Preoperative Prediction of Malignant Transformation of Sinonasal Inverted Papilloma Using MR Radiomics[J]. FRONTIERS IN ONCOLOGY,2022,12:10. |
| APA | Yan, Yang.,Liu, Yujia.,Tao, Jianhua.,Li, Zheng.,Qu, Xiaoxia.,...&Xian, Junfang.(2022).Preoperative Prediction of Malignant Transformation of Sinonasal Inverted Papilloma Using MR Radiomics.FRONTIERS IN ONCOLOGY,12,10. |
| MLA | Yan, Yang,et al."Preoperative Prediction of Malignant Transformation of Sinonasal Inverted Papilloma Using MR Radiomics".FRONTIERS IN ONCOLOGY 12(2022):10. |
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