Department of Radiology, Shanghai First Maternity and Infant Hospital, Shanghai, China , zhong71313852@163.com
Abstract: (182 Views)
Background:To assess the accuracy, specificity, and sensitivity of dynamic contrast-enhanced magnetic resonance imaging (MRI) in assessing lymph node metastasis (LNM) and prognosis after cervical cancer surgery. Materials and Methods: Fifty cervical cancer patients admitted to our hospital from April 2022 to April 2023 were selected. 27 patients were in stage I-IIA and processed radical hysterectomy combined with pelvic lymph node dissection. Twenty-three patients were in stage IIB and beyond and underwent laparotomy with key site biopsy combined with pelvic lymph node biopsy. Postoperative pathological diagnosis was used as the gold standard for diagnosis. All patients underwent MRI scanning, including conventional MRI scanning such as DWI, T2WI, and T1WI of the pelvic cavity. Gadolinium-diethylene triamine pentaacetate (Gd-DTPA) was injected for dynamic contrast-enhanced scanning. The data of postoperative pathological staging, MRI staging, LNM, deep muscle layer invasion, and postoperative recurrence were analyzed. Results: There was no marked difference between MRI staging and postoperative pathological staging (P>0.05). When comparing preoperative clinical staging and MRI staging with postoperative pathological staging as the control group, there was no significant difference in accuracy. Both postoperative pathological diagnosis and MRI diagnosis had high specificity and sensitivity in assessing LNM and deep muscle layer invasion, but the differences were not significant (P>0.05). Conclusion: Dynamic contrast-enhanced MRI examination has high accuracy in assessing lymph node metastasis for cervical cancer patients. It has high sensitivity and specificity in assessing parametrial invasion, LNM, deep muscle layer invasion, and vaginal involvement, as well as has good prognostic value in assessing postoperative recurrence.
1. Perkins RB, Wentzensen N, Guido RS, et al. (2023) Cervical Cancer Screening: A Review. JAMA, 330(6): 547-558. [DOI:10.1001/jama.2023.13174]
2. Zhang H, Qian J, Lin J. (2023) Application of portable vaginal irrigator in patients with cervical cancer undergoing external irradiation combined with intracavitary brachytherapy. International Journal of Radiation Research, 21(3): 499-503. [DOI:10.61186/ijrr.21.3.499]
3. Berek JS, Matias-Guiu X, Creutzberg C, et al. (2023) Endometrial Cancer Staging Subcommittee FWsCC: FIGO staging of endometrial cancer: 2023. Int J Gynaecol, 162(2): 383-394. [DOI:10.1002/ijgo.14923]
4. Yun BS, Lee KB, Lee KH, et al. (2024) Therapeutic effects of surgical debulking of metastatic lymph nodes in cervical cancer IIICr: a trial protocol for a phase III, multicenter, randomized controlled study (KGOG1047/DEBULK trial). J Gynecol Oncol, 35(5):e57. [DOI:10.3802/jgo.2024.35.e57]
5. O'Dowd EL, Merriel SWD, Cheng VWT, et al. (2023) Clinical trials in cancer screening, prevention and early diagnosis (SPED): a systematic mapping review. BMC Cancer, 23(1): 820. [DOI:10.1186/s12885-023-11300-8]
6. Hamdi M, Senan EM, Awaji B, et al. (2023) Analysis of WSI images by hybrid systems with fusion features for early diagnosis of cervical cancer. Diagnostics (Basel), 13(15): 2538. [DOI:10.3390/diagnostics13152538]
7. Abdul-Latif M, Tharmalingam H, Tsang Y, et al. (2023) Functional magnetic resonance imaging in cervical cancer diagnosis and treatment. Clin Oncol, 35(9): 598-610. [DOI:10.1016/j.clon.2023.05.006]
8. Meng H, Guo X, Zhang D (2023) Multimodal magnetic resonance imaging in the diagnosis of cervical cancer and its correlation with the differentiation process of cervical cancer. BMC Med Imaging, 23(1): 144. [DOI:10.1186/s12880-023-01104-4]
10. Benjamin J, O'Leary C, Hur S, et al. (2023) Imaging and interventions for lymphatic and lymphatic-related disorders. Radiology, 307(3): e220231. [DOI:10.1148/radiol.220231]
11. Long X, He M, Yang L, et al. (2023) Validation of the 2018 FIGO staging system for predicting the prognosis of patients with stage IIIC cervical cancer. Clin Med Insights Oncol, 17: 11795549221146652. [DOI:10.1177/11795549221146652]
12. Chen H, Tian X, Luan Y, et al. (2023) Highly expressed circ_0000285 from serum and cervical exfoliated cells as a novel biomarker for the diagnosis of early stage-cervical cancer. J Obstet Gynaecol, 43(1): 2196344. [DOI:10.1080/01443615.2023.2196344]
13. Kassa R, Irene Y, Woldetsadik E, et al. (2023) Survival of women with cervical cancer in East Africa: a systematic review and meta-analysis. J Obstet Gynaecol, 43(2): 2253308. [DOI:10.1080/01443615.2023.2253308]
14. Zhong L, Chen Z, Shu H, et al. (2024) Multi-scale tokens-aware transformer network for multi-region and multi-sequence MR-to-CT synthesis in a single model. IEEE Trans Med Imaging, 43(2): 794-806. [DOI:10.1109/TMI.2023.3321064]
15. Xiao ML, Wei Y, Zhang J, et al. (2022) MRI Texture analysis for preoperative prediction of lymph node metastasis in patients with nonsquamous cell cervical carcinoma. Acad Radiol, 29(11): 1661-1671. [DOI:10.1016/j.acra.2022.01.005]
16. Xiao ML, Qian T, Fu L, et al. (2024) Deep learning nomogram for the identification of deep stromal invasion in patients with early-stage cervical adenocarcinoma and adenosquamous carcinoma: a multicenter study. J Magn Reson Imaging, 59(4): 1394-1406. [DOI:10.1002/jmri.28882]
17. Lee MS, Moon MH, Kim TM, et al. (2023) Contrast-enhanced MRI in women with endometrial cancer: dynamic versus single-phase acquisitions. Clin Med Insights Oncol, 17: 11795549231207833. [DOI:10.1177/11795549231207833]
18. Li XX, Liu B, Cui Y, et al. (2024) Intravoxel incoherent motion diffusion-weighted imaging and dynamic contrast-enhanced MRI for predicting parametrial invasion in cervical cancer. Abdom Radiol (NY), 49(9): 3232-3240. [DOI:10.1007/s00261-024-04339-z]
19. Liu Q, Jiang N, Hao Y, et al. (2023) Identification of lymph node metastasis in pre-operation cervical cancer patients by weakly supervised deep learning from histopathological whole-slide biopsy images. Cancer Med, 12(17): 17952-17966. [DOI:10.1002/cam4.6437]
20. Bizzarri N, Di Berardino S, Benkortbi K, et al. (2024) External beam radiotherapy boost versus surgical debulking followed by radiotherapy for the treatment of metastatic lymph nodes in cervical cancer: A systematic review and meta-analysis. Eur J Surg Oncol, 50(4): 108013. [DOI:10.1016/j.ejso.2024.108013]
21. Lee KY, Rim J, Choi JA, et al. (2023) High-Resolution Finger MRI: What should you look for in trauma of the fingers? J Korean Soc Radiol, 84(5): 1031-1046. [DOI:10.3348/jksr.2022.0123]
22. Leung SN, Chandra SS, Lim K, et al. (2024) Automatic segmentation of tumour and organs at risk in 3D MRI for cervical cancer radiation therapy with anatomical variations. Phys Eng Sci Med, 47(3):919-928. [DOI:10.1007/s13246-024-01415-y]
23. Jha A, Patel M, Ling A, et al. (2024) Diagnostic performance of [(68)Ga]DOTATATE PET/CT, [(18)F]FDG PET/CT, MRI of the spine, and whole-body diagnostic CT and MRI in the detection of spinal bone metastases associated with pheochromocytoma and paraganglioma. Eur Radiol, 34(10):6488-6498. [DOI:10.1007/s00330-024-10652-4]
24. Shu Q, He X, Chen X, et al. (2023) Head-to-head comparison of 18 F-FDG and 68 Ga-FAPI-04 PET/CT for radiological evaluation of cervical cancer. Clin Nucl Med, 48(11): 928-932. [DOI:10.1097/RLU.0000000000004833]
Zheng C, Peng Y, Zhang Z, Zhang X. Analysis of the accuracy of dynamic contrast-enhanced magnetic resonance imaging in assessing lymph node metastasis and prognosis in cervical cancer patients. Int J Radiat Res 2025; 23 (2) :407-411 URL: http://ijrr.com/article-1-6400-en.html