Value of diffusion-weighted imaging in preoperative evaluation and prediction of postoperative supplementary therapy for patients with cervical cancer.

Abstract

BackgroundWith the continuous progress of medical imaging technology, evaluation of cervical cancer is increasingly dependent on imaging methods. Diffusion-weighted imaging (DWI) plays an important role, and apparent diffusion coefficient (ADC) value is a unique quantitative parameter in the research of cervical cancer.MethodsIn this prospective study, a total of 273 patients diagnosed with stage IB1 to IIIC1 cervical cancer based on the International Federation of Gynecology and Obstetrics (FIGO) 2018 staging guidelines who underwent pelvic 3.0T magnetic resonance imaging (MRI), including MRI and DWI, were enrolled, and the diagnostic value of preoperative staging of cervical cancer was compared between the MRI and DWI groups. The DWI group was used to explore the potential association of mean ADC (ADCmean) with different pathological characteristics and receiver operating characteristic (ROC) curves of ADCmean generated to predict the appropriate postoperative supplementary therapy.ResultsThe diagnostic coincidence rate of DWI was higher than that of MRI in preoperative staging of cervical cancer (χ2, P<0.05) and determined as stages IB1 + IB2 + IIA1 (90.91%), IB3 + IIA2 (93.48%), and IIIC1p (95.16%). The DWI staging results were consistent with postoperative pathological staging (Kappa value =0.865, P<0.001). We observed significant differences in ADCmean values in relation to pathological type, histological grade, depth of stromal infiltration, tumor diameter, lymphovascular invasion, and pelvic lymph node metastasis of cervical cancer (all P<0.05). The area under the ROC curve (AUC) was 0.815, with the best predictive value for postoperative supplementary therapy in cervical cancer (sensitivity 80.0%, specificity 74.0%) at ADCmean of 0.910×10−3 mm2/s.ConclusionsThe DWI is a useful tool for preoperative evaluation of cervical cancer. In local cervical lesions, ADCmean varies in relation to different clinicopathological characteristics and a reference index of <0.910×10−3 mm2/s can be effectively applied to predict the need for postoperative supplementary therapy.