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  • Tumor Size at Magnetic Resonance Imaging Association With Lymph Node Metastasis and Lymphovascular Space Invasion in Resectable Cervical Cancer: A Multicenter Evaluation of Surgical Specimens

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Cervical Cancer
Tumor Size at Magnetic Resonance Imaging Association With Lymph Node Metastasis and Lymphovascular Space Invasion in Resectable Cervical Cancer: A Multicenter Evaluation of Surgical Specimens
  1. Xiao-li Chen, MS*,
  2. Guang-wen Chen, MS†,
  3. Guo-hui Xu, MS*,
  4. Jing Ren, MS*,
  5. Zhen-lin Li, MS‡,
  6. Hong Pu, MS† and
  7. Hang Li, MS†
  1. *Department of Radiology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China;
  2. †Department of Radiology, Affiliated Hospital of Medical School, University of Electronic Science and Technology of China, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital; and
  3. ‡Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.
  1. Address correspondence and reprint requests to Hang Li, MS, Department of Radiology, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, 32# Second Section of First Ring Road, Qingyang District, Chengdu, Sichuan 610070, China. E-mail: lihang111222{at}126.com; Xiao-li Chen, MS, Department of Radiology, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610041, China. E-mail: 20shenbaise{at}163.com.

Abstract

Objective To determine whether gross tumor volume (GTV) and the maximum diameter of resectable cervical cancer at magnetic resonance imaging (MRI) could predict lymph node metastasis (LNM) and lymphovascular space invasion (LVSI).

Materials and Methods A total of 315 consecutive patients with cervical cancer were retrospectively identified. Gross tumor volume and the maximum diameter of tumor were evaluated on MRI. Univariate and multivariate logistic regression analyses were performed to determine whether tumor size could predict LNM and LVSI. Cutoffs of GTV, maximum diameter, and the International Federation of Gynecology and Obstetrics (FIGO) classification of tumor were first investigated in 255 patients (group A) and then validated in an independent cohort of 60 patients (group B) using area under the receiver operating characteristic curve (AUC) analysis for predicting the presence of LNM and LVSI.

Results Univariate analysis showed that GTV and the maximum diameter of tumor could predict LNM and LVSI (all P < 0.0001). Multivariate analyses indicated GTV as an independent risk factor of LNM and LVSI (all P < 0.0001). In group A, GTV, the maximum diameter, and the FIGO stage could identify LNM (AUC, 0.813, 0.741, and 0.69, respectively) and LVSI (AUC, 0.806, 0.751, and 0.684, respectively). In group B, GTV, the maximum diameter, and the FIGO stage could help identify LNM (AUC, 0.902, 0.825, and 0.759, respectively) and LVSI (AUC, 0.771, 0.748, and 0.700, respectively).

Conclusions Gross tumor volume and the maximum diameter of resectable cervical cancer at MRI demonstrated capability in predicting LNM and LVSI, which were more accurate than FIGO stage.

  • MRI
  • Tumor size
  • Cervical cancer
  • Lymph node metastasis
  • Lymphovascular space invasion

This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

https://doi.org/10.1097/IGC.0000000000001327

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    Footnotes

    • This study was supported by the Project of Huimin Technology of Chengdu (No. 2015-HM01-00082-SF and No. 2015-HM01-00164-SF).

    • The authors declare no conflicts of interest or industry supports of the project in this study.

    • Guang-wen Chen, Hong Pu, and Guo-hui Xu contributed equally to this study.