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Objectives: To compare the agreement between magnetic resonance imaging (MRI) results and postsurgical pathologic findings for tumor size evaluation in cervical cancer patients before and after neoadjuvant chemotherapy (NACT) treatment. Methods: The study analyzed the agreement between pretreatment MRI results and postsurgical pathologic findings about the tumor size in 100 cervical cancer patients without NACT and 397 cervical cancer patients with NACT, respectively. Results: In general, the agreement between pretreatment MRI results and postsurgical pathologic findings of tumor size was 0.855 (95% confidence interval [CI], 0.763Y0.909) in cervical cancer patients without NACT, whereas the agreement between posttreatment MRI results and postsurgical pathologic findings was 0.503 (95% CI, 0.421Y0.576). Only 62.72% (249/397) of patients who underwent NACT treatment have the same chemotherapy response evaluation results; the J coefficient was 0.384(95% CI, 0.310Y0.457) between posttreatment MRI and postsurgical pathologic findings. We still found International Federation of Gynecology and Obstetrics stage is associated with the chemotherapy response evaluation. Conclusions: Our data suggest that pretreatment MRI can be a surrogate indicator for postsurgical pathologic findings. However, posttreatmentMRI could not be a surrogate indicator for postsurgical pathologic findings. The chemotherapy response evaluation based on onlyMRI is not so reliable. More indicators should be developed for chemotherapy response evaluation. [ABSTRACT FROM AUTHOR]

Epithelial ovarian cancer (EOC) is the most deadly gynecologic malignancy worldwide due to its high recurrence rate after surgery and chemotherapy. There is a critical need for discovery of novel biomarkers for EOC recurrence providing higher prediction power than that of the present ones. Lipids have been reported to associate with development and progression of cancer. In the current study, we aim to identify and validate the lipids which were relevant to the ovarian cancer recurrence based on plasma lipidomics performed by ultra-performance liquid chromatography coupled with mass spectrometry. In order to fulfill this objective, plasma from 70 EOC patients with follow up information was obtained. The results revealed that patients with and without recurrence could be clearly distinguished based on their lipid profiles. Thirty-one lipid metabolites were identified as potential biomarkers for EOC recurrence. The AUC value of these metabolite combinations for predicting EOC recurrence was 0.897. In terms of clinical applicability, LysoPG(20:5) arose as a potential EOC recurrence predictive biomarker to increase the predictive power of clinical predictors from AUC value 0.739 to 0.875. Additionally, we still found that individuals with early relapses (< 6 months) had a distinctive metabolomic pattern compared with late EOC and non-EOC recurrence subjects. Interestingly, decreased levels of triglycerides (TGs) were found to be a specific metabolic feature foreshadowing an early relapse. In conclusion, plasma lipidomics study could be used for predicting EOC recurrences, as well as early and late recurrent cases. The lipid biomarker research improves the predictive power of clinical predictors and the identified biomarkers are of great prognostic and therapeutic potential.