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Multimodal Ultrasound Imaging in Breast Imaging-Reporting and Data System 4 Breast Lesions: A Prediction Model for Malignancy
- Source :
- Ultrasound in Medicine & Biology. 46:3188-3199
- Publication Year :
- 2020
- Publisher :
- Elsevier BV, 2020.
-
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 p0.05). 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.
- Subjects :
- Adult
medicine.medical_specialty
Acoustics and Ultrasonics
Breast imaging
Biophysics
Contrast Media
Breast Neoplasms
Logistic regression
Malignancy
Multimodal Imaging
030218 nuclear medicine & medical imaging
Young Adult
03 medical and health sciences
0302 clinical medicine
Predictive Value of Tests
medicine
Data Systems
Humans
Radiology, Nuclear Medicine and imaging
Aged
Retrospective Studies
Ultrasonography
Radiological and Ultrasound Technology
Receiver operating characteristic
medicine.diagnostic_test
business.industry
Ultrasound
Middle Aged
Models, Theoretical
medicine.disease
Research Design
030220 oncology & carcinogenesis
Cohort
Elasticity Imaging Techniques
Female
Radiology
Elastography
business
Contrast-enhanced ultrasound
Subjects
Details
- ISSN :
- 03015629
- Volume :
- 46
- Database :
- OpenAIRE
- Journal :
- Ultrasound in Medicine & Biology
- Accession number :
- edsair.doi.dedup.....8a83e5bd2d504440ff57985d9c282444