The Outcome of Locally Advanced Cervical Cancer in Patients Treated with Neoadjuvant Chemotherapy Followed by Radical Hysterectomy and Primary Surgery

Radiomics analysis for prediction of lymph node metastasis after neoadjuvant chemotherapy based on pretreatment MRI in patients with locally advanced cervical cancer

Background

This study aims to develop and validate a pretreatment MRI-based radiomics model to predict lymph node metastasis (LNM) following neoadjuvant chemotherapy (NACT) in patients with locally advanced cervical cancer (LACC).

Methods

Patients with LACC who underwent NACT from two centers between 2013 and 2022 were enrolled retrospectively. Based on the lymph node (LN) status determined in the pathology reports after radical hysterectomy, patients were categorized as LN positive or negative. The patients from center 1 were assigned as the training set while those from center 2 formed the validation set. Radiomics features were extracted from pretreatment sagittal T2-weighted imaging (Sag-T2WI), axial diffusion-weighted imaging (Ax-DWI), and the delayed phase of dynamic contrast-enhanced sagittal T1-weighted imaging (Sag-T1C) for each patient. The K-best and least absolute shrinkage and selection operator (LASSO) methods were employed to reduce dimensionality, and the radiomics features strongly associated with LNM were selected and used to construct three single-sequence models. Furthermore, clinical variables were incorporated through multivariate regression analysis and fused with the selected radiomics features to construct the clinical-radiomics combined model. The diagnostic performance of the models was assessed using receiver operating characteristic (ROC) curve analysis. The clinical utility of the models was evaluated by the area under the ROC curve (AUC) and decision curve analysis (DCA).

Results

A total of 282 patients were included, comprising 171 patients in the training set, and 111 patients in the validation set. Compared to the Sag-T2WI model (AUC, 95%CI, training set, 0.797, 0.722-0.782; validation set, 0.648, 0.521-0.776) and the Sag-T1C model (AUC, 95%CI, training set, 0.802, 0.723-0.882; validation set, 0.630, 0.505-0.756), the Ax-DWI model exhibited the highest diagnostic performance with AUCs of 0.855 (95%CI, 0.791-0.919) in training set, and 0.753 (95%CI, 0.638-0.867) in validation set, respectively. The combined model, integrating selected features from three sequences and FIGO stage, surpassed predictive ability compared to the single-sequence models, with AUC of 0.889 (95%CI, 0.833-0.945) and 0.859 (95%CI, 0.781-0.936) in the training and validation sets, respectively.

Conclusions

The pretreatment MRI-based radiomics model, integrating radiomics features from three sequences and clinical variables, exhibited superior performance in predicting LNM following NACT in patients with LACC.

A Retrospective Study of Chemotherapy and 3D-Image-Guided Afterloading Intracavitary Radiotherapy in Locally Advanced Cervical Cancer

Aim

To investigate the value of neoadjuvant chemotherapy combined with 3D-image-guided afterloading intracavitary radiotherapy in locally advanced cervical cancer (LACC).

Methods

Patients with cervical cancer admitted to our hospital from January 1, 2020 to January 1, 2021 were retrieved and analyzed. Cases treated with neoadjuvant chemotherapy and 3D-image-guided afterloading intracavitary radiotherapy were assigned into the observation group (OG), while cases with neoadjuvant chemotherapy alone were assigned into the control group (CG). The short-term effects were determined by RECIST 1.1. Total effective rate (TR) = complete remission (CR) + partial remission (PR). The serum levels of squamous epithelial cell carcinoma antigen (SCC-Ag), glycoantigen 125 (CA125), carcinoembryonic antigen (CEA), and vascular endothelial growth factor (VEGF) were assessed. In view of the difference between tumor markers and diameters before and after treatment, the correlation between them was analyzed by Pearson test. The adverse events were compared, and the amount of operative bleeding and operation time were evaluated. Cox regression analysis was conducted to assess the influencing factors of 1-year disease-free survival time.

Results

Sixty-seven patients were retrieved, including 30 cases in the OG and 37 cases in the CG. There were no significant differences in age, pathological type, tumor size, FIGO stage, past medical history, or smoking history between the two groups (P > 0.05). The TR of patients in the OG was higher than that in the CG (P < 0.05). The SCC-Ag, CA125, CEA, and VEGF levels in the OG decreased markedly after treatment (P < 0.001). The difference in SCC-Ag, CA125, CEA, and VEGF was positively correlated with the difference in tumor diameter before and after treatment (P < 0.05). The incidence of adverse events revealed no obvious difference between the OG and CG (P > 0.05). Cox regression analysis showed that FIGO stage and treatment regimens were independent prognostic factors for 1-year disease-free survival (P < 0.05).

Conclusion

Neoadjuvant chemotherapy combined with 3D-image-guided afterloading intracavitary radiotherapy can improve the TR rate and 1-year disease-free survival of LACC patients without increasing the incidence of adverse events.