Abstract
PurposeTo develop and validate a radiomics model for predicting preoperative lymph node (LN) metastasis in high-grade serous ovarian cancer (HGSOC).Materials and MethodsFrom May 2008 to January 2018, a total of 256 eligible HGSOC patients who underwent tumor resection and LN dissection were divided into a training cohort (n=179) and a test cohort (n=77) in a 7:3 ratio. A Radiomics Model was developed based on a training cohort of 179 patients. A radiomics signature (defined as the Radscore) was selected by using the random forest method. Logistics regression was used as the classifier for modeling. An Integrated Model that incorporated the Radscore and CT_reported LN status (CT_LN_report) was developed and presented as a radiomics nomogram. Its performance was determined by the area under the curve (AUC), calibration, and decision curve. The radiomics nomogram was internally tested in an independent test cohort (n=77) and a CT-LN-report negative subgroup (n=179) using the formula derived from the training cohort.ResultsThe AUC value of the CT_LN_report was 0.688 (95% CI: 0.626, 0.759) in the training cohort and 0.717 (95% CI: 0.630, 0.804) in the test cohort. The Radiomics Model yielded an AUC of 0.767 (95% CI: 0.696, 0.837) in the training cohort and 0.753 (95% CI: 0.640, 0.866) in the test. The radiomics nomogram demonstrated favorable calibration and discrimination in the training cohort (AUC=0.821), test cohort (AUC=0.843), and CT-LN-report negative subgroup (AUC=0.82), outperforming the Radiomics Model and CT_LN_report alone.ConclusionsThe radiomics nomogram derived from portal phase CT images performed well in predicting LN metastasis in HGSOC and could be recommended as a new, convenient, and non-invasive method to aid in clinical decision-making.
Highlights
Epithelial ovarian cancer (EOC) has the highest mortality rate among all gynecological malignancies, and approximately twothirds of women are staged as International Federation of Gynecology and Obstetrics (FIGO) III–IV [1]
The area under the curve (AUC) value of the CT_LN_report was 0.688 in the training cohort and 0.717 in the test cohort, with sensitivities of 50 and 48.7%, respectively (Table 2)
65 patients (50.4%; 65 of 129) with Lymph node (LN) metastasis were understaged, and 13 patients (10.2%; 13 of 127) without LN metastasis were overstaged according to the pathologic examination for LN metastasis
Summary
Epithelial ovarian cancer (EOC) has the highest mortality rate among all gynecological malignancies, and approximately twothirds of women are staged as International Federation of Gynecology and Obstetrics (FIGO) III–IV [1]. Lymph node (LN) metastasis in HGSOC patients is observed in up to 75% of patients with stage III–IV disease and in 25% of patients with stage I–II disease [5, 6]. LN metastasis in different sites for ovarian cancer may have not the same impact on progression-free survival (PFS) and overall survival (OS) [11, 18,19,20]. In the study by Gallotta et al [19], the patients with metastatic hepatoceliac lymph nodes (HCLNs) experienced worse PFS than the patients with uninvolved ones, but clinicians often underestimate the true prevalence of disease in this area due to the lack of effective methods before surgery. The gold standard methods for EOC staging are surgery and histopathologic diagnosis, so it is necessary to explore noninvasive methods to predict LN metastatic preoperatively for aiding in clinical decision-making
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