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Eur Radiol ; 26(4): 1064-72, 2016 Apr.
Article in English | MEDLINE | ID: mdl-26135000

ABSTRACT

OBJECTIVES: The purpose of our study was to assess whether there is a potential additional value of real-time virtual sonography (RVS) to second-look ultrasound (US) examination and biopsy for breast lesions identified on MRI alone. METHODS: A retrospective review of the records of 70 consecutive patients (78 lesions) with breast abnormalities identified on MRI alone was performed. All suspicious enhancing lesions were subsequently evaluated with second-look US. Lesions not observed on second-look US underwent RVS. Pathological findings were confirmed by subsequent percutaneous biopsy or excision. RESULTS: Of the 78 MRI-detected lesions, second-look US correlation was made in 50 (64 %), including 22 malignant and 28 benign lesions. The remaining 28 lesions (36 %) were scheduled to undergo RVS. Four lesions were not visible on the second breast MRI. The remaining 24 lesions were RVS correlated and underwent RVS-guided biopsy; these included seven malignant and 17 benign lesions. Overall, 74 of 74 (100 %) true MRI-detected lesions were confirmed by histological results without using MRI-guided breast biopsy. The cancer rate was 29 %. CONCLUSIONS: RVS can increase the sonographic detection and biopsy rate of lesions identified on breast MRI alone. KEY POINTS: • All 74 MRI-detected lesions were confirmed without using MRI-guided biopsy. • Four lesions were not visible on second breast MRI. • RVS can increase sonographic detection of lesions identified on breast MRI alone. • RVS-guided breast biopsy can be an alternative to MRI-guided biopsy.


Subject(s)
Breast Neoplasms/diagnostic imaging , Breast Neoplasms/pathology , Magnetic Resonance Imaging/methods , Ultrasonography, Interventional/methods , Ultrasonography, Mammary/methods , Adult , Aged , Aged, 80 and over , Breast/pathology , Breast Diseases/pathology , Female , Humans , Image-Guided Biopsy/methods , Middle Aged , Reproducibility of Results , Retrospective Studies , Sensitivity and Specificity
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