MRI-Based Radiomics Nomogram for Selecting Ovarian Preservation Treatment in Patients With Early-Stage Endometrial Cancer

被引:11
作者
Yan, Bi Cong [1 ,2 ]
Ma, Xiao Liang [1 ]
Li, Ying [1 ]
Duan, Shao Feng [3 ]
Zhang, Guo Fu [4 ]
Qiang, Jin Wei [1 ]
机构
[1] Fudan Univ, Jinshan Hosp, Dept Ridiol, Shanghai, Peoples R China
[2] Shanghai Jiao Tong Univ Affiliated Peoples Hosp 6, Dept Diagnost & Intervent Radiol, Shanghai, Peoples R China
[3] GE Healthcare, Precis Hlth Inst, Shanghai, Peoples R China
[4] Fudan Univ, Obstet & Gynecol Hosp, Dept Radiol, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
radiomics; nomogram; endometrial cancer; myometrial invasion; ovarian preservation; FATTY LIVER-DISEASE; PREMENOPAUSAL WOMEN; MYOMETRIAL INVASION; INCREASED RISK; YOUNG-WOMEN; OOPHORECTOMY; CARCINOMA; SURVIVAL; CONSERVATION; STATISTICS;
D O I
10.3389/fonc.2021.730281
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background Ovarian preservation treatment (OPT) was recommended in young women with early-stage endometrial cancer [superficial myometrial invasion (MI) and grades (G) 1/2-endometrioid adenocarcinoma (EEC)]. A radiomics nomogram was developed to assist radiologists in assessing the depth of MI and in selecting eligible patients for OPT. Methods From February 2014 to May 2021, 209 G 1/2-EEC patients younger than 45 years (mean 39 +/- 4.3 years) were included. Of them, 104 retrospective patients were enrolled in the primary group, and 105 prospective patients were enrolled in the validation group. The radiomics features were extracted based on multi-parametric magnetic resonance imaging, and the least absolute shrinkage and selection operator algorithm was applied to reduce the dimensionality of the data and select the radiomics features that correlated with the depth of MI in G 1/2-EEC patients. A radiomics nomogram for evaluating the depth of MI was developed by combing the selected radiomics features with the cancer antigen 125 and tumor size. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of the radiomics nomogram and of radiologists without and with the aid of the radiomics nomogram. The net reclassification index (NRI) and total integrated discrimination index (IDI) based on the total included patients to assess the clinical benefit of radiologists with the radiomics nomogram were calculated. Results In the primary group, for evaluating the depth of MI, the AUCs were 0.96 for the radiomics nomogram; 0.80 and 0.86 for radiologists 1 and 2 without the aid of the nomogram, respectively; and 0.98 and 0.98 for radiologists 1 and 2 with the aid of the nomogram, respectively. In the validation group, the AUCs were 0.88 for the radiomics nomogram; 0.82 and 0.83 for radiologists 1 and 2 without the aid of the nomogram, respectively; and 0.94 and 0.94 for radiologists 1 and 2 with the aid of the nomogram, respectively. The yielded NRI and IDI values were 0.29 and 0.43 for radiologist 1 and 0.23 and 0.37 for radiologist 2, respectively. Conclusions The radiomics nomogram outperformed radiologists and could help radiologists in assessing the depth of MI and selecting eligible OPTs in G 1/2-EEC patients.
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页数:11
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共 35 条
[1]   Postmenopausal status and early menopause as independent risk factors for cardiovascular disease: a meta-analysis [J].
Atsma, F ;
Bartelink, MLEL ;
Grobbee, DE ;
van der Schouw, YT .
MENOPAUSE-THE JOURNAL OF THE NORTH AMERICAN MENOPAUSE SOCIETY, 2006, 13 (02) :265-279
[2]   Adnexal Involvement in Endometrial Cancer: Prognostic Factors and Implications for Ovarian Preservation [J].
Baiocchi, Glauco ;
Clemente, Ana Gabriela ;
Mantoan, Henrique ;
da Costa Jr, Wilson Luiz ;
Bovolim, Graziele ;
Guimaraes, Andrea Paiva Gadelha ;
da Costa, Alexandre Andre Balieiro Anastacio ;
De Brot, Louise ;
Faloppa, Carlos Chaves .
ANNALS OF SURGICAL ONCOLOGY, 2020, 27 (08) :2822-2826
[3]   Deep learning for the determination of myometrial invasion depth and automatic lesion identification in endometrial cancer MR imaging: a preliminary study in a single institution [J].
Chen, Xiaojun ;
Wang, Yida ;
Shen, Minhua ;
Yang, Bingyi ;
Zhou, Qing ;
Yi, Yinqiao ;
Liu, Weifeng ;
Zhang, Guofu ;
Yang, Guang ;
Zhang, He .
EUROPEAN RADIOLOGY, 2020, 30 (09) :4985-4994
[4]   Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging [J].
Cheng, Nai-Ming ;
Yao, Jiawen ;
Cai, Jinzheng ;
Ye, Xianghua ;
Zhao, Shilin ;
Zhao, Kui ;
Zhou, Wenlan ;
Nogues, Isabella ;
Huo, Yuankai ;
Liao, Chun-Ta ;
Wang, Hung-Ming ;
Lin, Chien-Yu ;
Lee, Li-Yu ;
Xiao, Jing ;
Lu, Le ;
Zhang, Ling ;
Yen, Tzu-Chen .
CLINICAL CANCER RESEARCH, 2021, 27 (14) :3948-3959
[5]   Risk of myocardial infarction after oophorectomy and hysterectomy [J].
Falkeborn, M ;
Schairer, C ;
Naessén, T ;
Persson, I .
JOURNAL OF CLINICAL EPIDEMIOLOGY, 2000, 53 (08) :832-837
[6]   Preoperative quantitative dynamic contrast-enhanced MRI and diffusion-weighted imaging predict aggressive disease in endometrial cancer [J].
Fasmer, Kristine E. ;
Bjornerud, Atle ;
Ytre-Hauge, Sigmund ;
Gruner, Renate ;
Tangen, Ingvild L. ;
Werner, Henrica M. J. ;
Bjorge, Line ;
Salvesen, Oyvind O. ;
Trovik, Jone ;
Krakstad, Camilla ;
Haldorsen, Ingfrid S. .
ACTA RADIOLOGICA, 2018, 59 (08) :1010-1017
[7]   Repeatability and reproducibility of MRI-based radiomic features in cervical cancer [J].
Fiset, Sandra ;
Welch, Mattea L. ;
Weiss, Jessica ;
Pintilie, Melania ;
Conway, Jessica L. ;
Milosevic, Michael ;
Fyles, Anthony ;
Traverso, Alberto ;
Jaffra, David ;
Metser, Ur ;
Xie, Jason ;
Han, Kathy .
RADIOTHERAPY AND ONCOLOGY, 2019, 135 :107-114
[8]   Development and Validation of a Deep Learning CT Signature to Predict Survival and Chemotherapy Benefit in Gastric Cancer [J].
Jiang, Yuming ;
Jin, Cheng ;
Yu, Heng ;
Wu, Jia ;
Chen, Chuanli ;
Yuan, Qingyu ;
Huang, Weicai ;
Hu, Yanfeng ;
Xu, Yikai ;
Zhou, Zhiwei ;
Fisher, George A., Jr. ;
Li, Guoxin ;
Li, Ruijiang .
ANNALS OF SURGERY, 2021, 274 (06) :E1153-E1161
[9]   Ovarian preservation in young women with endometrial cancer of endometrioid histology [J].
Kinjyo, Yoshino ;
Kudaka, Wataru ;
Ooyama, Takuma ;
Inamine, Morihiko ;
Nagai, Yutaka ;
Aoki, Yoichi .
ACTA OBSTETRICIA ET GYNECOLOGICA SCANDINAVICA, 2015, 94 (04) :430-434
[10]   A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research [J].
Koo, Terry K. ;
Li, Mae Y. .
JOURNAL OF CHIROPRACTIC MEDICINE, 2016, 15 (02) :155-163