ArticleBMC medical imaging2020
The role of MRI and clinicopathologic features in predicting the invasive component of biopsy-confirmed ductal carcinoma in situ.
Article in BMC medical imaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed, 26 citations in OpenAlex.
- Breast DCE-MRI morphological features and semi-quantitative parameters associated with upgrade to invasive carcinoma in biopsyproven DCIS.Radiology and oncology · 2026Article
- Dynamic curve type serves as an effective tool for the diagnosis of benign or malignant non-mass enhancements on breast MRI.Oncology letters · 2026Article
- Multicenter development and external validation of clinical-radiomics models to predict surgically confirmed upstaging in biopsy-proven DCIS using DCE-MRI.Journal of applied clinical medical physics · 2026Article
- Predictors and nomogram for upstaging to invasive breast carcinoma in ductal carcinomaGland surgery · 2025Article
- Predictive Performance of Radiomic Features Extracted from Breast MR Imaging in Postoperative Upgrading of Ductal Carcinoma in Situ to Invasive Carcinoma.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Article
- Nonmass lesions on preoperative MRI in breast cancer patients: clinical implications and prognostic significance.Scientific reports · 2025Article
- Florid Lobular Carcinoma In Situ: Imaging Characteristics and Pathologic Upgrade Rates on Surgical Excision.The breast journal · 2025Article
- Correlations of Imaging and Therapy in Breast Cancer Based on Molecular Patterns: An Important Issue in the Diagnosis of Breast Cancer.International journal of molecular sciences · 2024Review
- Quantitative peritumoral magnetic resonance imaging fingerprinting improves machine learning-based prediction of overall survival in colorectal cancer.Exploration of targeted anti-tumor therapy · 2024Article
- A clinical radiomics nomogram preoperatively to predict ductal carcinoma in situ with microinvasion in women with biopsy-confirmed ductal carcinoma in situ: a preliminary study.BMC medical imaging · 2023Article
- Predicting Underestimation of Invasive Cancer in Patients with Core-Needle-Biopsy-Diagnosed Ductal Carcinoma In Situ Using Deep Learning Algorithms.Tomography (Ann Arbor, Mich.) · 2022Article
- Prediction of the histologic upgrade of ductal carcinomaFrontiers in oncology · 2022Article
- Article
- Clinical and imaging characteristics of breast ductal carcinoma in situ with microinvasion.Journal of applied clinical medical physics · 2021Article
- Improving ductal carcinoma in situ classification by convolutional neural network with exponential linear unit and rank-based weighted pooling.Complex & intelligent systems · 2021Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe upgrade rate of biopsy-confirmed ductal carcinoma in situ (DCIS) to invasive carcinoma is up to 50% on final pathology. We investigated MRI and clinicopathologic predictors of the invasive components of DCIS diagnosed by preoperative biopsy and then compared MRI features between patients with DCIS, microinvasive ductal carcinoma (mIDC), and invasive ductal carcinoma (IDC) diagnosed on final pathology.
methodsTwo hundred and one patients with 206 biopsy-confirmed DCIS lesions were enrolled. MRI and clinicopathologic features were used to predict either mIDC or IDC via a cumulative logistic regression analysis. For the lesions detected on MRI, morphologic and kinetic analyses were performed using the Chi-square, Fisher's exact, and Kruskal-Wallis tests.
resultsOf all the lesions, 112 (54.4%) were diagnosed as DCIS, 50 (24.3%) were upgraded to mIDC, and 44 (21.4%) to IDC. The detection on MRI as mass (Odds ratio (OR) = 8.84, 95% confidence interval (CI) = 1.05-74.04, P = 0.045) or non-mass enhancement (NME; OR = 11.17, 95% CI = 1.35-92.36, P = 0.025), negative progesterone receptor (PR; OR = 2.40, 95% CI = 1.29-4.44, P = 0.006), and high Ki-67 level (OR = 2.42, 95% CI = 1.30-4.50, P = 0.005) were significant independent predictors of histologic upgrade. On MRI, 87 (42.2%) lesions appeared as mass and 107 (51.9%) as NME. Irregularly shaped, not-circumscribed, heterogeneous, or rim-enhancing masses with intratumoral high signal intensity or peritumoral edema, clumped or clustered ring-enhancing NMEs, and high peak enhancement were significantly associated with histologic upgrade (P < 0.001).
conclusionMRI detection, negative PR, and high Ki-67 levels are associated with a histologic upgrade in patients with biopsy-confirmed DCIS. Suspicious MRI features are more frequent in such patients.
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