ArticleAbdominal radiology (New York)2020
Differentiation of borderline tumors from type I ovarian epithelial cancers on CT and MR imaging.
Article in Abdominal radiology (New York), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 12 citations in OpenAlex.
- A new risk algorithm combining D-dimer and HE4 differentiates borderline tumor from patients with ovarian tumor.Translational cancer research · 2025Article
- Habitat-based radiomics for preoperative differentiation between early-stage serous borderline ovarian tumors and malignant ovarian tumors.Frontiers in oncology · 2025Article
- Role of magnetic resonance imaging to differentiate between borderline and malignant serous epithelial ovarian tumors.Abdominal radiology (New York) · 2024Article
- What is your diagnosis?Journal of the Turkish German Gynecological Association · 2023Article
- Computed Tomography Indicators for Differentiating Stage 1 Borderline Ovarian Tumors from Stage I Malignant Epithelial Ovarian Tumors.Diagnostics (Basel, Switzerland) · 2023Article
- Radiomics nomogram for preoperative differentiation of early-stage serous borderline ovarian tumors and serous malignant ovarian tumors.Frontiers in oncology · 2023Article
- Develop a nomogram to predict overall survival of patients with borderline ovarian tumors.World journal of clinical cases · 2022Article
- An Application of Machine Learning That Uses the Magnetic Resonance Imaging Metric, Mean Apparent Diffusion Coefficient, to Differentiate between the Histological Types of Ovarian Cancer.Journal of clinical medicine · 2021Article
- The Diagnosis, Treatment, Prognosis and Molecular Pathology of Borderline Ovarian Tumors: Current Status and Perspectives.Cancer management and research · 2020Review
- Giant Cystic Mucinous Borderline Tumour of the Ovary in a Young Female: A Rare Case Report.Nigerian medical journal : journal of the Nigeria Medical AssociationArticle
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo investigate the value of CT and MR imaging features in differentiating borderline ovarian tumor (BOT) from type I ovarian epithelial cancer (OEC), which could be significant for suitable clinical treatment and assessment of the prognosis of the patient.
methodsThirty-three patients with BOTs and 35 patients with type I OECs proven by pathology were retrospectively evaluated. The clinico-pathological information (age, premenopausal status, CA-125, and Ki-67) and imaging characteristics were compared between two groups of ovarian tumors. The diagnostic performance of the imaging features was evaluated using receiver operating characteristic analysis. The best predictor variables for type I EOCs were recognized via multivariate analyses.
resultsBOTs are more likely to involve younger patients and frequently show lower CA-125 values and lower proliferation indices (Ki-67 < 15%) than type I OECs. Compared with type I OECs, BOTs were more often purely cystic (15/33, 45.45% vs. 1/35, 2.86%; p < 0.001) and displayed less frequent mural nodules (16/33, 48.48% vs. 28/35, 80.00%; p = 0.007), less frequently unclear margin (3/33, 9.09% vs. 11/35, 31.43%; p = 0.023), smaller solid portion (0.56 ± 2.66 vs. 4.51 ± 3.88; p < 0.001), and thinner walls (0.3 ± 0.17 vs. 0.55 ± 0.24; p < 0.001). The maximum wall thickness presented the largest area under the curve (AUC, 0.848). Multivariate analysis revealed that the solid portion size (OR 10.822, p = 0.002) and maximum wall thickness (OR 9.130, p = 0.001) were independent indicators for the differential diagnosis between the two groups of lesions.
conclusionThe solid portion size and maximum wall thickness significantly influenced the classification of the two groups of ovarian tumors.
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