MRI-based peritumoral radiomics analysis for preoperative prediction of lymph node metastasis in early-stage cervical cancer: A multi-center study

被引:37
作者
Shi, Jiaxin [1 ]
Dong, Yue [2 ]
Jiang, Wenyan [3 ]
Qin, Fengying [2 ]
Wang, Xiaoyu [2 ]
Cui, Linpeng [1 ]
Liu, Yan [4 ]
Jin, Ying [4 ]
Luo, Yahong [2 ]
Jiang, Xiran [1 ]
机构
[1] China Med Univ, Sch Intelligent Med, Dept Biomed Engn, Shenyang 110122, Peoples R China
[2] Canc Hosp China Med Univ, Liaoning Canc Hosp & Inst, Dept Radiol, Shenyang 110042, Peoples R China
[3] Canc Hosp China Med Univ, Liaoning Canc Hosp & Inst, Sci Res & Acad Dept, Shenyang 110042, Peoples R China
[4] Affiliated Reprod Hosp China Med Univ, Liaoning Res Inst Family Planning, Shenyang 110031, Peoples R China
关键词
Lymph node metastasis; Cervical cancer; MRI; Radiomics; Nomogram; NOMOGRAM; TUMOR;
D O I
10.1016/j.mri.2021.12.008
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose: To evaluate intra- and preitumoral radiomics on the contrast-enhanced T1-weighted (CE-T1) and T2weighted (T2W) MRI for predicting the LNM, and develop a nomogram for potential clinical uses.Methods: We enrolled 169 cervical cancer cases who underwent CE-T1 and T2W MR scans from two hospitals between Dec. 2015 and Sep. 2021. Intra- and peritumoral features were extracted separately and selected by the least absolute shrinkage and selection operator (LASSO) regression. Radiomics signatures were built using the selected features from different regions. Clinical parameters were evaluated by statistical analysis. The nomogram was developed combining the multi-regional radiomics signature and the most predictive clinical parameters.Results: Five radiomics features were finally selected from the peritumoral regions with 1 and 3 mm distances in the CE-T1 and T2W MRI, respectively. The nomogram incorporating multi-regional combined radiomics signature, MR-reported LN status and tumor diameter achieved the highest AUCs in the training (nomogram vs. combined radiomics signature vs. clinical model, 0.891 vs. 0.830 vs. 0.812), internal validation (nomogram vs. combined radiomics signature vs. clinical model, 0.863 vs. 0.853 vs. 0.816) and external validation (nomogram vs. combined radiomics signature vs. clinical model, 0.804 vs. 0.701 vs. 0.787) cohort. DCA suggested good clinical usefulness of our developed models.Conclusion: The current work suggested clinical potential for intra- and peritumoral radiomics with multi-modal MRI for preoperative predicting LNM.
引用
收藏
页码:1 / 8
页数:8
相关论文
共 32 条
[11]   Lymph Node Assessment in Cervical Cancer: Prognostic and Therapeutic Implications [J].
Gien, L. T. ;
Covens, A. .
JOURNAL OF SURGICAL ONCOLOGY, 2009, 99 (04) :242-247
[12]   Development and Validation of a Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer [J].
Huang, Yan-qi ;
Liang, Chang-hong ;
He, Lan ;
Tian, Jie ;
Liang, Cui-shan ;
Chen, Xin ;
Ma, Ze-lan ;
Liu, Zai-yi .
JOURNAL OF CLINICAL ONCOLOGY, 2016, 34 (18) :2157-+
[13]   Radiomic signature as a predictive factor for lymph node metastasis in early-stage cervical cancer [J].
Kan, Yangyang ;
Dong, Di ;
Zhang, Yuchen ;
Jiang, Wenyan ;
Zhao, Nannan ;
Han, Lu ;
Fang, Mengjie ;
Zang, Yali ;
Hu, Chaoen ;
Tian, Jie ;
Li, Chunming ;
Luo, Yahong .
JOURNAL OF MAGNETIC RESONANCE IMAGING, 2019, 49 (01) :304-310
[14]   Clinical tumor diameter and prognosis of patients with FIGO stage IB1 cervical cancer (JCOG0806-A) [J].
Kato, Tomoyasu ;
Takashima, Atsuo ;
Kasamatsu, Takahiro ;
Nakamura, Kenichi ;
Mizusawa, Junki ;
Nakanishi, Toru ;
Takeshima, Nobuhiro ;
Kamiura, Shoji ;
Onda, Takashi ;
Sumi, Toshiyuki ;
Takano, Masashi ;
Nakai, Hidekatsu ;
Saito, Toshiaki ;
Fujiwara, Kiyoshi ;
Yokoyama, Masatoshi ;
Itamochi, Hiroaki ;
Takehara, Kazuhiro ;
Yokota, Harushige ;
Mizunoe, Tomoya ;
Takeda, Satoru ;
Sonoda, Kenzo ;
Shiozawa, Tanri ;
Kawabata, Takayo ;
Honma, Shigeru ;
Fukuda, Haruhiko ;
Yaegashi, Nobuo ;
Yoshikawa, Hiroyuki ;
Konishi, Ikuo ;
Kamura, Toshiharu .
GYNECOLOGIC ONCOLOGY, 2015, 137 (01) :34-39
[15]   A Combination of Intra- and Peritumoral features on baseline CT scans is Associated with Overall Survival in non-small cell lung cancer patients treated with Immune checkpoint inhibitors: A multi-agent multi-site study [J].
Khorrami, Mohammadhadi ;
Alilou, Mehdi ;
Prasanna, Prateek ;
Patil, Pradnya ;
Velu, Priya ;
Bera, Kaustav ;
Fu, Pingfu ;
Velcheti, Vamsidhar ;
Madabhushi, Anant .
MEDICAL IMAGING 2019: COMPUTER-AIDED DIAGNOSIS, 2019, 10950
[16]   Intratumoral metabolic heterogeneity of cervical cancer [J].
Kidd, Elizabeth A. ;
Grigsby, Perry W. .
CLINICAL CANCER RESEARCH, 2008, 14 (16) :5236-5241
[17]   Uterine Neoplasms, Version 1.2018 Clinical Practice Guidelines in Oncology [J].
Koh, Wui-Jin ;
Abu-Rustum, Nadeem R. ;
Bean, Sarah ;
Bradley, Kristin ;
Campos, Susana M. ;
Cho, Kathleen R. ;
Chon, Hye Sook ;
Chu, Christina ;
Cohn, David ;
Crispens, Marta Ann ;
Damast, Shari ;
Dorigo, Oliver ;
Eifel, Patricia J. ;
Fisher, Christine M. ;
Frederick, Peter ;
Gaffney, David K. ;
George, Suzanne ;
Han, Ernest ;
Higgins, Susan ;
Huh, Warner K. ;
Lurain, John R., III ;
Mariani, Andrea ;
Mutch, David ;
Nagel, Christa ;
Nekhlyudov, Larissa ;
Fader, Amanda Nickles ;
Remmenga, Steven W. ;
Reynolds, R. Kevin ;
Tillmanns, Todd ;
Ueda, Stefanie ;
Wyse, Emily ;
Yashar, Catheryn M. ;
McMillian, Nicole R. ;
Scavone, Jillian L. .
JOURNAL OF THE NATIONAL COMPREHENSIVE CANCER NETWORK, 2018, 16 (02) :170-199
[18]   Radiomics: the bridge between medical imaging and personalized medicine [J].
Lambin, Philippe ;
Leijenaar, Ralph T. H. ;
Deist, Timo M. ;
Peerlings, Jurgen ;
de Jong, Evelyn E. C. ;
van Timmeren, Janita ;
Sanduleanu, Sebastian ;
Larue, Ruben T. H. M. ;
Even, Aniek J. G. ;
Jochems, Arthur ;
van Wijk, Yvonka ;
Woodruff, Henry ;
van Soest, Johan ;
Lustberg, Tim ;
Roelofs, Erik ;
van Elmpt, Wouter ;
Dekker, Andre ;
Mottaghy, Felix M. ;
Wildberger, Joachim E. ;
Walsh, Sean .
NATURE REVIEWS CLINICAL ONCOLOGY, 2017, 14 (12) :749-762
[19]   Akaike's information criterion in generalized estimating equations [J].
Pan, W .
BIOMETRICS, 2001, 57 (01) :120-125
[20]   Peritumoral and intratumoral radiomic features predict survival outcomes among patients diagnosed in lung cancer screening [J].
Perez-Morales, Jaileene ;
Tunali, Ilke ;
Stringfield, Olya ;
Eschrich, Steven A. ;
Balagurunathan, Yoganand ;
Gillies, Robert J. ;
Schabath, Matthew B. .
SCIENTIFIC REPORTS, 2020, 10 (01)