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Dual contrast-enhanced ultrasound for diagnosing pathologic nipple discharge associated with papillary lesions
Yanchun Zhao1,2, Songsong Wu2, Zhongtao Bao3
1Department of Ultrasound, The Second Affiliated Hospital of Fujian Medical University, Licheng District, Quanzhou, Fujian, 362000, China.
Background:
The goal of this research study is to determine the efficacy of dual contrast-enhanced ultrasound (US) in evaluating ductal papillary lesions associated with pathological nipple discharge.
Methods:
A prospective multicenter study was conducted between January 2020 and December 2022. All participants were examined using dual contrast-enhanced US and had re-adjustment of BI-RADS classification. Genuine ductal papillary lesions were identified using US features and subsequently subjected to biopsy or excision. Using pathological results and clinical follow-up as the reference standard as a standard reference, we compared the diagnostic efficacy of dual contrast-enhanced US to conventional US in detecting papillary lesions.
Results:
The study included 102 female participants ranging in age from 29 to 80 years (average 47.6 ± 9.4), of whom 87 were retained for analysis. We precisely localized discharging ducts with papillary lesions in 85 patients, with 68 showing varying degrees of enhancement in papillary lesions. Compared to conventional US, dual contrast-enhanced US was more accurate in locating and detecting papillary lesions (P < 0.001). The optimized BI-RADS classification allowed for a more informed prediction of the malignancy risk associated with papillary lesions. Multivariate logistic regression analysis revealed that ductal continuity, the boundary between the nodule and duct, and peak intensity are independent risk factors for malignancy. The area under the curve for detecting malignant papillary lesions was 0.937.
Conclusions:
Dual contrast-enhanced US is effective at precisely locating lactiferous ducts in pathological nipple discharge, detecting and differentiating papillary lesions, and improving the accuracy of BI-RADS classification.
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