Korean Journal of Radiology

The Korean Society of Radiology (대한영상의학회)
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CT-Based Fagotti Scoring System for Non-Invasive Prediction of Cytoreduction Surgery Outcome in Patients with Advanced Ovarian Cancer

  • Na Young Kim (Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine) ;
  • Dae Chul Jung (Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine) ;
  • Jung Yun Lee (Department of Obstetrics and Gynecology, Institute of Women's Life Medical Science, Yonsei University College of Medicine) ;
  • Kyung Hwa Han (Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine) ;
  • Young Taik Oh (Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University College of Medicine)
  • Received : 2020.12.19
  • Accepted : 2021.03.05
  • Published : 2021.09.01
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Abstract

Objective: To construct a CT-based Fagotti scoring system by analyzing the correlations between laparoscopic findings and CT features in patients with advanced ovarian cancer. Materials and Methods: This retrospective cohort study included patients diagnosed with stage III/IV ovarian cancer who underwent diagnostic laparoscopy and debulking surgery between January 2010 and June 2018. Two radiologists independently reviewed preoperative CT scans and assessed ten CT features known as predictors of suboptimal cytoreduction. Correlation analysis between ten CT features and seven laparoscopic parameters based on the Fagotti scoring system was performed using Spearman's correlation. Variable selection and model construction were performed by logistic regression with the least absolute shrinkage and selection operator method using a predictive index value (PIV) ≥ 8 as an indicator of suboptimal cytoreduction. The final CT-based scoring system was internally validated using 5-fold cross-validation. Results: A total of 157 patients (median age, 56 years; range, 27-79 years) were evaluated. Among 120 (76.4%) patients with a PIV ≥ 8, 105 patients received neoadjuvant chemotherapy followed by interval debulking surgery, and the optimal cytoreduction rate was 90.5% (95 of 105). Among 37 (23.6%) patients with PIV < 8, 29 patients underwent primary debulking surgery, and the optimal cytoreduction rate was 93.1% (27 of 29). CT features showing significant correlations with PIV ≥ 8 were mesenteric involvement, gastro-transverse mesocolon-splenic space involvement, diaphragmatic involvement, and para-aortic lymphadenopathy. The area under the receiver operating curve of the final model for prediction of PIV ≥ 8 was 0.72 (95% confidence interval: 0.62-0.82). Conclusion: Central tumor burden and upper abdominal spread features on preoperative CT were identified as distinct predictive factors for high PIV on diagnostic laparoscopy. The CT-based PIV prediction model might be useful for patient stratification before cytoreduction surgery for advanced ovarian cancer.

Keywords

Acknowledgement

This research was supported by a grant (NRF-2019R1A2C2004746) of the National Research Foundation of Korea funded by the Korean Government (MEST). It was also supported by a faculty research grant of Yonsei University College of Medicine for 2018 (6-2018-0066).

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