Related Experiment Video For Breast cancer
Updated: Aug 16, 2026

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Comparative study of Adjunct Imaging Modalities in Dense breast (AdMoB-D study)
Gurasis Singh Boparai1, Ekta Dhamija2, Aarosh Dhamija1
1Department of Radio-diagnosis and Interventional Radiology, AIIMS, New Delhi, 110029, India.
Objectives:
To compare the diagnostic accuracy of contrast-enhanced mammography (CEM) with digital mammography (DM), digital breast tomosynthesis (DBT) and ultrasonography (USG) for breast cancer detection in dense breasts.
Methods:
This prospective study was conducted between January 2023 and 2025 including DM with ACR- C or D category parenchymal density. Imaging findings were categorized using the ACR BI-RADS assessment where BI-RADS scores 4 and 5 were considered suspicious for malignancy. Histopathology was reference standard for such lesions and imaging follow-up for categories 1 to 3. Sensitivity, specificity, positive and negative predictive value (NPV), likelihood & odds ratios, ROC analysis, and kappa statistics were calculated.
Results:
In 100 females (mean age, 45 ± 7.2 years), CEM demonstrated the highest sensitivity (97.9%) and NPV (97.7%), outperforming DM as well as DBT (p < 0.001). Subgroup analysis was performed for diagnostic (n = 56) and surveillance cohort (n = 44). In the former, CEM achieved 100% sensitivity and identified additional multifocal, multicentric, or contralateral disease in 12 patients. It also demonstrated higher specificity (94.3%) and strongest association with malignancy in surveillance group. Agreement with histopathology was highest for CEM (κ 0.80).
Conclusion:
CEM demonstrates superior diagnostic accuracy than conventional mammographic techniques in dense breasts, with excellent sensitivity, NPV and agreement with histopathology.
Advances In Knowledge:
CEM improves cancer detection and disease extent assessment in dense breasts, enabling confident exclusion of malignancy and more accurate staging. Its high diagnostic performance supports use as practical adjunct, particularly in resource-limited settings.
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