Prediction of postoperative residual primary ovarian neoplasm or metastatic lesion close to rectum of serous ovarian carcinoma based on clinical and MR T1-DEI features

Author:

Zhang Wenfei1,Li Juncai2,Chen Qiao3,Jin Hongliang4,Zhou Linyi5,Liu Li1ORCID

Affiliation:

1. Department of Radiology, The People's Hospital of Yubei District of Chongqing City, Chongqing, PR China

2. Department of Surgery, The People's Hospital of Yubei District of Chongqing City, Chongqing, PR China

3. School of Public Health, Chongqing Medical University, Chongqing, PR China

4. Department of Osteology, The People's Hospital of Yubei District of Chongqing City, Chongqing, PR China

5. Department of Radiology, Daping Hospital, Army Medical Center, Army Medical University, Chongqing, PR China

Abstract

Background The optimal primary debulking surgery outcome of serous ovarian carcinoma (SOC) is greatly affected by primary ovarian neoplasm or metastatic lesion close to the rectum. Purpose To study the risk factors affecting postoperative residual primary ovarian neoplasm or metastatic lesion close to the rectum of SOC. Material and Methods The clinical and MRI data of 164 patients with SOC eligible from institution A (training and test groups) and 36 patients with SOC eligible from institution B (external validation group) were collected and retrospectively analyzed. The clinical data included age, serum carbohydrate antigen 125 (CA-125), human epididymis protein 4, and neutrophil-to-lymphocyte ratio (NLR). Magnetic resonance imaging (MRI) data included ovarian mass distribution, maximum diameter of ovarian mass, ovarian mass features, degree of rectal invasion of the primary ovarian neoplasm or metastatic lesion, and amount of ascites. A model was established using multivariate logistic regression. Results By univariate and multivariate logistic regressions, CA-125 ( P = 0.024, odds ratio [OR] = 3.798, 95% confidence interval [CI] = 1.24–13.32), NLR ( P = 0.037, OR = 3.543, 95% CI = 1.13–12.72), and degree of rectal invasion of the primary ovarian neoplasm or metastatic lesion ( P < 0.001, OR = 37.723, 95% CI = 7.46–266.88) were screened as independent predictors. The area under the curve values of the model in the training, test, and external validation groups were 0.860, 0.764, and 0.778, respectively. Conclusion The clinical-radiological model based on T1-weighted dual-echo MRI can be used non-invasively to predict postoperative residual ovarian neoplasm or metastasis close to SOC in the rectum.

Publisher

SAGE Publications

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