Can second-look ultrasound downgrade MRI-detected lesions? A retrospective study.

PURPOSE: To determine whether MRI-detected suspicious (BIRADS 4 & 5) breast lesions can be downgraded using second-look ultrasound (SLU) and thus reduce unnecessarily performed breast biopsies. MATERIALS METHODS: A retrospective single-center review of consecutive patients, who underwent breast MRI studies during a 12-month time period was performed. 94 patients with 103 lesions undergoing SLU of incidentally detected MRI BI-RADS 4&5 lesions which were not identified on previous ultrasound were included in the study. The SLU detection rate and SLU features of the lesions were assessed. Histology (91/103) or two year follow up (n = 12) were defined as the reference standard for lesion diagnosis. RESULTS: 57 (55.3 %) of the 103 lesions were identified on SLU. 17 of the identified lesions were malignant (29.8 %). Lesions detected on ultrasound presented on MRI as masses in 66.7 % (38/57) and non-mass in 33.3 % (19/57). Our findings showed that it is possible to distinguish between malignant and benign lesions with SLU. The results were significant (p < 0.05) for the following morphological features: shape, orientation, margins, architectural distortion, hyperechoic rim/ edema. All lesions classified as SLU BI-RADS 2 in our study were benign and thus, 30 % of all unnecessary biopsies could potentially have been avoided. Including SLU BI-RADS 3 lesions, this rate increased to 60 %, while yielding one (of 17, 5.8 %) false negative result. All three BI-RADS 5 lesions detected by SLU presented as malignant on ultrasound. CONCLUSION: SLU can potentially downgrade incidental MRI BIRADS 4 lesions. This may reduce the number of unnecessarily performed biopsies by 30-60 %, thus simplifying patient management.

Can we predict lesion detection rates in second-look ultrasound of MRI-detected breast lesions? A systematic analysis.

PURPOSE: To predict detection rates (DR) in second-look ultrasound of MRI-detected breast lesions by systematically combining clinical and anthropomorphic features. METHODS: A total of 104 suspicious breast-lesions, that were initially detected on breast MRI and underwent subsequent SLU from January 2013 through December 2013, were evaluated in this retrospective analysis. All images were reviewed by an experienced radiologist for this study. Both anthropomorphic, spatial and BI-RADS lesion features were recorded. Uni- and multivariate Classification and Regression Trees (CRT) statistics were used to predict SLU DR by these features. RESULTS: Among 104 MRI-detected lesions, 58 (55.8%) showed a correlate on SLU. In univariate analysis, homogeneous fatty or dense fibro-glandular-tissue-composition (FGT) as assessed by ultrasound, segmental non-mass-distribution pattern and small breast size as assessed by MRI were significantly associated with higher DR on SLU. The remaining BI-RADS features did not significantly affect SLU DR according to our data. The predictive model could stratify the likelihood of SLU correlates as high, intermediate and low according to FGT, lesion type, size and position. CONCLUSIONS: By systematically combining the features FGT, lesion type, size and position, we could predict SLU DR of MRI-detected breast lesions. This may help to decide the preferable method for lesion biopsy or follow-up in clinical practice.