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Multimodal Ultrasound Imaging in Breast Imaging-Reporting and Data System 4 Breast Lesions: A Prediction Model for Malignancy.
- Source :
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Ultrasound in Medicine & Biology . Dec2020, Vol. 46 Issue 12, p3188-3199. 12p. - Publication Year :
- 2020
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Abstract
- The purpose of this study was to develop, validate and test a prediction model for discriminating malignant from benign breast lesions using conventional ultrasound (US), US elastography of strain elastography and contrast-enhanced ultrasound (CEUS). The study included 454 patients with breast imaging-reporting and data system (BI-RADS) category 4 breast lesions identified on histologic examinations. Firstly, 228 breast lesions (cohort 1) were analyzed by logistic regression analysis to identify the risk factors, and a breast malignancy prediction model was created. Secondly, the prediction model was validated in cohort 2 (84 patients) and tested in cohort 3 (142 patients) by using analysis of the area under the receiver operating characteristic curve (AUC). Univariate regression indicated that age ≥40 y, taller than wide shape on US, early hyperenhancement on CEUS and enlargement of enhancement area on CEUS were independent risk factors for breast malignancy (all p < 0.05). The logistic regression equation was established as follows: p = 1/1+Exp∑[-5.066 + 3.125 x (if age ≥40 y) + 1.943 x (if taller than wide shape) + 1.479 x (if early hyperenhancement) + 4.167 x (if enlargement of enhancement area). The prediction model showed good discrimination performance with an AUC of 0.967 in cohort 1, 0.948 in cohort 2 and 0.920 in cohort 3. By using the prediction model to selectively downgrade category 4a lesions, the re-rated BI-RADS yield an AUC of 0.880 (95% confidence interval [CI], 0.794-0.965) in cohort 2 and 0.870 (95% CI, 0.801-0.939) in cohort 3. The specificity increased from 0.0% (0/35) to 80.0% (28/35) without loss of sensitivity (from 100.0% to 95.9%, p = 0.153) in cohort 2. Similarly, the specificity increased from 0.0% (0/58) to 77.6% (45/58) without loss of sensitivity (from 100.0% to 96.4%, p = 0.081) in cohort 3. Multimodal US showed good diagnostic performance in predicting breast malignancy of BI-RADS category 4 lesions. Although the loss of sensitivity was existing, the addition of multimodal US to US BI-RADS could improve the specificity in BI-RADS category 4 lesions, which reduced unnecessary biopsies. [ABSTRACT FROM AUTHOR]
- Subjects :
- *BREAST
*ULTRASONIC imaging
*MAGNETIC resonance mammography
*BREAST imaging
*PREDICTION models
*RECEIVER operating characteristic curves
*BREAST ultrasound
*EXPERIMENTAL design
*RESEARCH
*PREDICTIVE tests
*MATHEMATICAL models
*RESEARCH methodology
*RETROSPECTIVE studies
*CONTRAST media
*MEDICAL cooperation
*EVALUATION research
*DIAGNOSTIC imaging
*COMPARATIVE studies
*THEORY
*BREAST tumors
Subjects
Details
- Language :
- English
- ISSN :
- 03015629
- Volume :
- 46
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- Ultrasound in Medicine & Biology
- Publication Type :
- Academic Journal
- Accession number :
- 146559745
- Full Text :
- https://doi.org/10.1016/j.ultrasmedbio.2020.08.003