ArticleJapanese journal of radiology2016
Comparison between borderline ovarian tumors and carcinomas using semi-automated histogram analysis of diffusion-weighted imaging: focusing on solid components.
Article in Japanese journal of radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- mpMRI-based habitat analysis for predicting prognoses in patients with high-grade serous ovarian cancer: a multicenter study.Abdominal radiology (New York) · 2025Article
- Article
- 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
- Differentiation between pleomorphic adenoma and schwannoma in the parapharyngeal space: histogram analysis of apparent diffusion coefficient.Dento maxillo facial radiology · 2023Article
- AI diagnostic performance based on multiple imaging modalities for ovarian tumor: A systematic review and meta-analysis.Frontiers in oncology · 2023Review
- Radiomics nomogram for preoperative differentiation of early-stage serous borderline ovarian tumors and serous malignant ovarian tumors.Frontiers in oncology · 2023Article
- Whole-lesion histogram analysis of apparent diffusion coefficient for the assessment of non-mass enhancement lesions on breast MRI.Journal of clinical imaging science · 2022Article
- Diffusion-weighted imaging-based radiomics in epithelial ovarian tumors: Assessment of histologic subtype.Frontiers in oncology · 2022Article
- Minimal apparent diffusion coefficient value of the solid component to differentiate borderline and malignant ovarian epithelial tumours: a preliminary report.Polish journal of radiology · 2020Article
- Differentiation between solitary fibrous tumors and schwannomas of the head and neck: an apparent diffusion coefficient histogram analysis.Dento maxillo facial radiology · 2019Article
- Conservative treatment of borderline ovarian tumors: a retrospective study.Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologieArticle
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis study aimed to evaluate whether histogram analysis of the apparent diffusion coefficient (ADC) of a solid tumor component could distinguish borderline ovarian tumors from ovarian carcinoma. MATERIALS AND
methodsSixteen pathologically proven borderline tumors and 21 carcinomas were retrospectively examined. Magnetic resonance (1.5-T) image data sets were coregistered, and the solid components of each tumor were semiautomatically segmented. ADC histograms of the solid components were extracted; modes, minimums, means, and 10th, 25th, 50th, 75th, and 90th percentiles of the histograms were compared between the two tumor types, and receiver-operating characteristic (ROC) analysis was performed.
resultsThe mode, minimum, mean, 10th, 25th, 50th, and 75th percentile ADC values of solid components of borderline tumors were significantly larger than those of carcinomas. Among these, the 10th percentile values had the lowest p value (p = 0.0003). At ROC analysis, the area under the curve (AUC) in the 10th percentile was the greatest (0.854), and the best cutoff value in the 10th percentile provided the highest specificity (93.8 %).
conclusionsADC histograms of solid tumor components facilitated the distinction between borderline ovarian tumors and carcinoma. The 10th percentile ADC values had the best diagnostic performance.
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