Related Experiment Video For DCIS
Updated: Sep 8, 2026
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Breast DCE-MRI morphological features and semi-quantitative parameters associated with upgrade to invasive carcinoma
Vladimir Urban1, Zorica Milosevic2, Zoran Bukumiric2,3
11Department of Diagnostic Radiology, Institute for Oncology and Radiology of Serbia, Belgrade, Serbia.
Background:
The aim of this study was to identify imaging predictors of upgrade to invasive carcinoma (IC) in patients with biopsy-proven ductal carcinoma in situ (DCIS) based on morphological features and semi-quantitative parameters derived from dynamic contrast-enhanced breast magnetic resonance imaging (DCE-MRI).
Patients And Methods:
Ninety consecutive patients with biopsy-proven DCIS who had positive findings on standard full-protocol breast DCE-MRI and subsequently underwent surgical excision with final postoperative histopathological diagnosis were included. Patients with final postoperative IC were compared with those without IC. Morphological features (lesion type, size, multifocality/multicentricity, T2-weighted (T2W) and turbo inversion recovery magnitude [TIRM] characteristics) and semi-quantitative parameters (wash-in, peak enhancement, delayed phase of the timeintensity curve [TIC], time to peak [TTP], and positive enhancement integral [PEI]) were analyzed.
Results:
Fifty-five patients (61.1%) had no IC, while 35 patients (38.9%) had IC on final histopathology. Patients with IC more frequently demonstrated non-mass enhancement (NME) combined with a mass, larger lesion size, multifocal or multicentric disease, T2W/TIRM hyperintensity, fast wash-in, higher peak enhancement, plateau and washout TIC patterns, higher PEI, and shorter TTP. Multivariate analysis identified NME combined with a mass, delayed-phase TIC characteristics, and TIRM hyperintensity as independent predictors of IC.
Conclusions:
Our study confirmed that prediction models incorporating breast DCE-MRI morphological features and semi-quantitative parameters can stratify patients with biopsy-proven DCIS by their probability of upgrade to IC. TIRM hyperintensity emerged as one of three independent predictors of IC and, to the best of our knowledge, has not been previously reported in this context.
