The Egyptian Journal of Radiology and Nuclear Medicine (Jun 2024)

Contrast enhanced digital mammography as a predictor of breast cancer in patient with pathological nipple discharge

  • Lamiaa M. R. Khalaf,
  • Mostafa A. M. El-Sharkawy,
  • Mohamed Zedan,
  • Khaled Rezk,
  • Marwa Mosaed,
  • Hosam M. Kamel

DOI
https://doi.org/10.1186/s43055-024-01296-x
Journal volume & issue
Vol. 55, no. 1
pp. 1 – 13

Abstract

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Abstract Background Pathological nipple discharge (PND) commonly caused by benign diseases, but occasionally it signifies a major medical concern. Ultrasonography, in addition to mammography, is regarded as the standard imaging modality in the diagnosis of PND but their sensitivity in some cases are low, subsequently we used a contrast enhanced mammography (CEDM) as supplementary diagnostic modality in patients with PND. The purpose of our study was to investigate the diagnostic efficacy of CEDM in evaluating PND patients, added values of incorporating the CEDM in the diagnostic workup of patients with PND and to demonstrate its diagnostic significance as a predictor of malignancy in these patients as there have been few studies that have addressed the role of CEDM in the evaluation of PND. Results Forty seven patients with PND were enrolled in this prospective study and underwent CEDM. The CEDM had high specificity (83.2%) compared to the combined sonomammography (SM) (59.3%), as there was a decrease in the number of false positive cases detected by the CEDM (6 cases) compared to the combined SM (11 cases). Combined (SM) had a moderate degree of agreement (55%, P = 0.01) with the final diagnosis, whereas CEDM had a strong degree of agreement (75%, P < 0.001). Additionally, the combined SM reported 76.6% accuracy with an area under the curve of 0.8, whereas the CEDM had 87.2% accuracy with an area under the curve of 0.89. Conclusions CEDM had higher specificity, positive predictive value, and accuracy than SM in PND patients, along with its stronger agreement with the final pathology results, subsequently reduce the rate of false positive cases and the rate of recall back, making it a highly accurate malignancy predictor in those patients and can be an invaluable diagnostic imaging tool for identifying associated malignancies.

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