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• Clinical Article •
Multiparameter MRI radiomics predicts preoperative peritoneal metastasis in patients with epithelial ovarian cancer
YU Xiaoyu  WU Hui  NIU Guangming  REN Jialiang  YU Na  QIAN Luodan  WU Jing 

Cite this article as: Yu XY, Wu H, Niu GM, et al. Multiparameter MRI radiomics predicts preoperative peritoneal metastasis in patients with epithelial ovarian cancer[J]. Chin J Magn Reson Imaging, 2021, 12(8): 44-48. DOI:10.12015/issn.1674-8034.2021.08.009.


[Abstract] Objective To evaluate the predictive value of radiomics based on multi-parameter magnetic resonance imaging (MP-MRI) for epithelial ovarian cancer (EOC) peritoneal metastasis. Materials andMethods A retrospective collection of 86 patients with EOC was included in the study. All patients underwent axial lipid suppression (FS) T2WI, diffusion weighted imaging (DWI) and dynamic enhancement (DCE) T1WI scans, and then underwent total double appendage resection. Quantitative imaging features were extracted from the preoperative FS-T2WI, DWI and DCE-T1WI images of each patient, and a radiomic model was established to evaluate the ability of radiomic features to distinguish peritoneal metastases. In addition, a clinical model was established. Finally, combined with radiomic characteristics and clinicopathological risk factors, a radiomic nomogram was constructed, and the receiver operating characteristic curve (ROC), area under the curve (AUC), calibration curve and clinical practicality to evaluate the predictive performance of the radiomics nomogram.Results The radiomic model derived from the MP-MRI combined sequence had a higher AUC than the model derived from FS-T2WI, DWI, and DCE-T1WI alone (0.865 vs. 0.749, 0.765, 0.736). The nomogram (AUC=0.953) showed a better diagnostic effect than the clinical model (AUC=0.819) and the omics model (AUC=0.865). The analysis of the decision curve shows that the nomogram has good clinical application value.Conclusions The radiomic nomogram based on the combined sequence of MP-MRI shows good predictive accuracy for peritoneal metastasis. This non-invasive and reliable tool can be used to identify peritoneal metastases in EOC patients before surgery.
[Keywords] epithelial ovarian cancer；peritoneal metastasis；radiomics；magnetic resonance imaging；multiparameter

YU Xiaoyu1   WU Hui1   NIU Guangming1*   REN Jialiang2   YU Na1   QIAN Luodan1   WU Jing1  

1 Department of Radiology, Affiliated Hospital of Inner Mongolia Medical University, Inner Mongolia, Huhhot 010050, China

2 GE Healthcare, Beijing 100176, China

Niu GM, E-mail: Cjr.niuguangming@vip.163.com

Conflicts of interest   None.

ACKNOWLEDGMENTS This work was part of Natural Science Foundation of Inner Mongolia Autonomous Region (No. 2020MS08128).
Received  2021-04-01
Accepted  2021-05-20
DOI: 10.12015/issn.1674-8034.2021.08.009
Cite this article as: Yu XY, Wu H, Niu GM, et al. Multiparameter MRI radiomics predicts preoperative peritoneal metastasis in patients with epithelial ovarian cancer[J]. Chin J Magn Reson Imaging, 2021, 12(8): 44-48. DOI:10.12015/issn.1674-8034.2021.08.009.

1
Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020[J]. CA Cancer J Clin, 2020, 70(1): 7-30. DOI: 10.3322/caac.21590.
2
Scalici JM, Arapovic S, Saks EJ, et al. Mesothelium expression of vascular cell adhesion molecule-1 (VCAM-1) is associated with an unfavorable prognosis inepithelial ovarian cancer (EOC)[J]. Cancer, 2017, 123(6): 977-984. DOI: 10.1002/cncr.30415.
3
Ahmed N, Stenvers KL. Getting to know ovarian cancer ascites: Opportunities for targeted therapy-based translational research[J]. Front Oncol, 2013, 3(3): 256. DOI: 10.3389/fonc.2013.00256.
4
Gillies RJ, Kinahan PE, Hricak H, et al. Radiomics: Images are more than pictures, they are data[J]. Radiology, 2016, 278(2): 563-577. DOI: 10.1148/radiol.2015151169.
5
Gao WB, Deng PF, Yang QX, et al. A feasibility study of radiomics based on dynamic contrast enhanced magnetic resonance imaging in identifying benign and malignant breast mass[J]. J Clin Radiol, 2020, 39(4): 674-679.
6
Mu JH, Zhang YW, Wu ZG. Application of different radiomics dignostic models based on conventional MR images in the preprotive grading of brain gliomag[J]. Chin J Magn Resonan Imaging, 2020, 11(1): 55-59. DOI: 10.12015/issn.1674-8034.2020.01.012.
7
Ma Y, Zhao LP, Huang G. Research progress of neoadjuvant radiotherapy and chemotherapy for rectal cancer based on magnetic resonance imaging radiology[J]. Chin J of Magn Resonan Imaging, 2020, 11(10): 947-949. DOI: 10.12015/issn.1674-8034.2020.10.029.
8
Dong D, Tang L, Li Z Y, et al. Development and validation of an individualized nomogram to identify occult peritoneal metastasis in patients with advanced gastric cancer[J]. Ann Oncol, 2019, 30(3): 431-438. DOI: 10.1093/annonc/mdz001.
9
Liu SL, He J, Liu S, et al. Radiomics analysis using contrast-enhanced CT for preoperative prediction of occult peritoneal metastasis in advanced gastric cancer[J]. Eur Radiol, 2020, 30(1): 239-246. DOI: 10.1007/s00330-019-06368-5.
10
Lu HW, Huo CY, Xu MC, et al. Interpretation of "2020NCCN clinical practice guidelines for ovarian cancer including fallopian tube cancer and primary peritoneal cancer (first edition)"[J]. Chin J Pract Gynecol Obstetrics, 2020, 36(4): 340-348. DOI: 10.19538/j.fk2020040113.
11
Qian LD, Ren JL, Liu AS, et al. MR imaging of epithelial ovarian cancer: a combined model to predict histologic subtypes[J]. Eur Radiol, 2020, 30(11): 5815-5825. DOI: 10.1007/s00330-020-06993-5
12
Guo HL, Ling H, Zhu YC, et al. Comparison between multi-slice spiral CT and magnetic resonance imaging in the diagnosis of peritoneal metastasis in primary ovarian carcinoma[J]. Onco Targets Ther, 2018, 11: 1087-1094. DOI: 10.2147/OTT.S147700.
13
Grabowska-Derlatka L, Derlatka P, Szeszkowski W, et al. Diffusion-weighted imaging of small peritoneal implants in "Potentially" early-stage ovarian cancer[J]. Biomed Res Int, 2016, 2016: 9254742. DOI: 10.1155/2016/9254742.
14
Rubini G, Altini C, Notaristefano A, et al. Role of 18F-FDG PET/CT in diagnosing peritoneal carcinomatosis in the restaging of patient with ovarian cancer as compared to contrast enhanced CT and tumor marker Ca-125[J]. Rev Esp Med Nucl Imagen Mol, 2014, 33(1): 22-27. DOI: 10.1016/j.remn.2013.06.008.
15
Smorgick N, Barel O, Halperin R, et al. Laparoscopic removal of adnexal cysts: is it possible to decrease inadvertent intraoperative rupture rate?[J]. Am J Obstet Gynecol, 2009, 200(3): 237. DOI: 10.1016/j.ajog.2008.10.030.
16
Zivanovic O, Sonoda Y, Diaz JP, et al. The rate of port-site metastases after 2251 laparoscopic procedures in women with underlying malignant disease[J]. Gynecol Oncol, 2008, 111(3): 431-437. DOI: 10.1016/j.ygyno.2008.08.024.
17
Zhang B, Tian J, Dong D, et al. Radiomics features of multiparametric MRI as novel prognostic factors in advanced nasopharyngeal carcinoma[J]. Clin Cancer Res, 2017, 23(15): 4259-4269. DOI: 10.1158/1078-0432.CCR-16-2910.
18
Nie K, Shi LM, Chen Q, et al. Rectal cancer: Assessment of neoadjuvant chemoradiation outcome based on radiomics of multiparametric MRI[J]. Clin Cancer Res, 2016, 22(21): 5256-5264. DOI: 10.1158/1078-0432.CCR-15-2997.
19
Thrall MM, DeLoia JA, Gallion H, et al. Clinical use of combined positron emission tomography and computed tomography (FDG-PET/CT) in recurrent ovarian cancer[J]. Gynecol Oncol, 2007, 105(1): 17-22. DOI: 10.1016/j.ygyno.2006.10.060.
20
Bilici A, Ustaalioglu BBO, Seker M, et al. Clinical value of FDG PET/CT in the diagnosis of suspected recurrent ovarian cancer: is there an impact of FDG PET/CT on patient management?[J]. Eur J Nucl Med Mol Imaging, 2010, 37(7): 1259-1269. DOI: 10.1007/s00259-010-1416-2.
21
Chen DX, Liu ZYZ, Liu WJ, et al. Predicting postoperative peritoneal metastasis in gastric cancer with serosal invasion using a collagen nomogram[J]. Nat Commun, 2021, 12(1): 179. DOI: 10.1038/s41467-020-20429-0.
22
Arakawa K, Kawai K, Ishihara S, et al. Prognostic significance of peritoneal metastasis in stage Ⅳ colorectal cancer patients with R0 resection: A multicenter, retrospective study[J]. Dis Colon Rectum, 2017, 60(10): 1041-1049. DOI: 10.1097/DCR.0000000000000858.
23
Werner ME, Karve S, Sukumar R, et al. Folate-targeted nanoparticle delivery of chemo- and radiotherapeutics for the treatment of ovarian cancer peritoneal metastasis[J]. Biomaterials, 2011, 32(33): 8548-8554. DOI: 10.1016/j.biomaterials.2011.07.067.

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