Pre-Invasive (In Situ)

D05WHO Vol. 2

Breast

Prognosis

This section is being prepared by our editorial process.

🔬 Histological Types

📚 Latest Research

2026-09-09

Contrast-Enhanced Cone-Beam Breast CT Features for Differentiation of Breast Lesions with a Ductal Carcinoma In Situ Component.

Guo W, et al

A retrospective study of 222 women (164 in training, 58 in validation) found that contrast-enhanced cone-beam breast CT (CE-CBBCT) features can help differentiate ductal carcinoma in situ (DCIS), DCIS with microinvasion (DCISM), and DCIS with invasive ductal carcinoma (DCIS-IDC), with logistic regression models achieving areas under the ROC curve of 0.815 and 0.810 in the training cohort and 0.785 and 0.817 in the temporally separated validation cohort. Key imaging features distinguishing DCIS from DCISM included the maximum lesion extent perpendicular to ductal orientation (P = 0.014) and the adjacent vessel sign (P = 0.005), while DCISM and DCIS-IDC were separated by degree of enhancement and lesion type (both P < 0.001). These findings suggest CE-CBBCT could become a valuable preoperative tool for assessing invasive status in breast lesions with a DCIS component, potentially guiding surgical planning without additional biopsy. The authors caution that prospective multicenter external validation is required before clinical adoption.

Academic radiology

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2026-09-07

Breast DCE-MRI morphological features and semi-quantitative parameters associated with upgrade to invasive carcinoma in biopsyproven DCIS.

Urban V, et al

A new study of 90 patients with biopsy-proven ductal carcinoma in situ (DCIS) found that dynamic contrast-enhanced breast MRI (DCE-MRI) features can reliably identify which patients harbor occult invasive carcinoma, with 38.9% (35 of 90) confirmed to have invasive disease on final surgical pathology. Multivariate analysis identified three independent predictors of upgrade to invasive carcinoma: non-mass enhancement combined with a mass lesion, delayed-phase time-intensity curve characteristics (plateau or washout patterns), and TIRM (turbo inversion recovery magnitude) hyperintensity on T2-weighted imaging. Notably, TIRM hyperintensity has not been previously reported as an independent predictor in this clinical context, making it a potentially important new imaging biomarker. These findings suggest that pre-surgical DCE-MRI assessment incorporating both morphological and semi-quantitative parameters can meaningfully stratify DCIS patients by their risk of harboring invasive disease, helping guide surgical planning.

Radiology and oncology

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2026-09-05 • AI

Ultrasound Habitat Radiomics for Preoperative Prediction of Invasive Breast Cancer With a DCIS Component: A Dual-center Retrospective Study.

Fan L, et al

An ultrasound-based habitat subregional radiomics model achieved an area under the ROC curve (AUC) of 0.910 (95% CI: 0.883–0.936) when predicting preoperatively whether a breast cancer harbors a concurrent ductal carcinoma in situ (DCIS) component, outperforming both standard imaging and single-region radiomics models in external validation (p < 0.05). The study enrolled 1,063 pathologically confirmed breast cancer patients from two centers, splitting them into a training cohort of 637 and an external validation cohort of 426 patients. By partitioning tumors into three distinct intratumoral habitat subregions via unsupervised clustering and applying a support vector machine classifier, the model captured spatial heterogeneity that single-region approaches miss. This non-invasive tool may help clinicians better stratify patients before surgery, potentially guiding treatment decisions without the need for additional biopsies.

Ultrasound in medicine & biology

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