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Article type: Research Article
Authors: Pan, Lianga; c; * | Shan, Rui-Yingb | Gao, Su-Fangc | Zhou, Yana | Bao, Yuan-Yuana | Fu, Wenjinga
Affiliations: [a] Department of Radiology, Sihong County Sub-Jinting Hospital, Suqian, Jiangsu, China | [b] Department of Gynaecology and Obstetrics, Sihong County Sub-Jinting Hospital, Suqian, Jiangsu, China | [c] Department of Radiology, Suqian Third Hospital, Suqian, Jiangsu, China
Correspondence: [*] Corresponding author: Liang Pan, Department of Radiology, Sihong County Sub-Jinting Hospital, No. 1 Shuanggou West Road, Sihong Economic Development Zone, Suqian, Jiangsu 223900, China. E-mail: [email protected].
Abstract: BACKGROUND: In malignant tumours of the female reproductive system, cervical cancer is second only to breast cancer, seriously threatening the health and safety of most women. OBJECTIVE: To evaluate the clinical value of 3.0 T multimodal nuclear magnetic resonance imaging (MRI) in the International Federation of Gynecology and Obstetrics’ (FIGO) staging of cervical cancer. METHODS: The clinical data of 30 patients with pathologically diagnosed cervical cancer admitted to our hospital from January 2018 to August 2022 were analysed retrospectively. Before treatment, all patients were examined with conventional MRI, diffusion-weighted imaging and multi-directional contrast-enhanced imaging. RESULTS: The accuracy of multimodal MRI in the FIGO staging of cervical cancer (29/30, 96.7%) was significantly higher than the accuracy obtained in a control group (21/30, 70.0%), with a statistically significant difference (p= 0.013). In addition, there was good agreement between two observers applying multimodal imaging (kappa= 0.881) and moderate agreement between two observers in the control group (kappa= 0.538). CONCLUSION: Multimodal MRI can evaluate cervical cancer comprehensively and accurately to enable accurate FIGO staging, providing significant evidence for clinical operation planning and subsequent combined therapy.
Keywords: Multimodal imaging, uterine cervical neoplasms, magnetic resonance imaging
DOI: 10.3233/THC-230252
Journal: Technology and Health Care, vol. 32, no. 2, pp. 823-830, 2024
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