Rationale and Objectives
The sonographic appearance of benign and malignant breast nodules overlaps to some
extent, and we aimed to assess the performance of the Gail model as an adjunctive
tool to ultrasound (US) Breast Imaging Reporting and Data System (BI-RADS) for predicting
the malignancy of nodules.
Materials and Methods
From 2018 to 2019, 2607 patients were prospectively enrolled by 35 health care facilities.
An individual breast cancer risk was assessed by the Gail model. Based on B-mode US,
color Doppler, and elastography, all nodules were evaluated according to the fifth
edition of BI-RADS, and these nodules were all confirmed later by pathology.
Results
We demonstrated that the Gail model, age, tumor size, tumor shape, growth orientation,
margin, contour, acoustic shadowing, microcalcification, presence of duct ectasia,
presence of architectural distortion, color Doppler flow, BI-RADS, and elastography
score were significantly related to breast cancer (all p < 0.001). The sensitivity, specificity, positive predictive value, negative predictive
value, accuracy, and area under the curve (AUC) for combining the Gail model with
the BI-RADS category were 95.6%, 91.3%, 85.0%, 97.6%, 92.8%, and 0.98, respectively.
Combining the Gail model with the BI-RADS showed better diagnostic efficiency than
the BI-RADS and Gail model alone (AUC 0.98 vs 0.80, p < 0.001; AUC 0.98 vs 0.55, p < 0.001) and demonstrated a higher specificity than the BI-RADS (91.3% vs 59.4%,
p < 0.001).
Conclusion
The Gail model could be used to differentiate malignant and benign breast lesions.
Combined with the BI-RADS category, the Gail model was adjunctive to US for predicting
breast lesions for malignancy. For the diagnosis of malignancy, more attention should
be paid to high-risk patients with breast lesions.
Key Words
To read this article in full you will need to make a payment
Purchase one-time access:
Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online accessOne-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:
Subscribe to Academic RadiologyAlready a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
References
- Breast cancer in China.Lancet Oncol. 2014; 15: e279-e289
- Differences in mammographic density between Asian and Caucasian populations: a comparative analysis.Breast Cancer Res Treat. 2017; 161: 353-362
- A review of supplemental screening ultrasound for breast cancer: certain populations of women with dense breast tissue may benefit.Acad Radiol. 2016; 23: 1604-1609
- A multi-centre randomised trial comparing ultrasound vs mammography for screening breast cancer in high-risk Chinese women.Br J Cancer. 2015; 112: 998-1004
- Ultrasound as an adjunct to mammography for breast cancer screening: a health technology assessment.Ont Health Technol Assess Ser. 2016; 16: 1-71
- Ultrasound imaging technologies for breast cancer detection and management: a review.Ultrasound Med Biol. 2018; 44: 37-70
- Assessing Risk Category of Breast Cancer by Ultrasound Imaging Characteristics.Ultrasound Med Biol. 2018; 44: 815-824
- Breast imaging reporting and data system. Breast imaging atlas.5th edition. Author, Reston, VA2013
- Prognostic importance of ultrasound BI-RADS classification in breast cancer patients.Jpn J Clin Oncol. 2015; 45: 411-415
- Ultrasound positive predictive values by BI-RADS categories 3-5 for solid masses: An independent reader study.Eur Radiol. 2017; 27: 4307-4315
- Projecting individualized probabilities of developing breast cancer for white females who are being examined annually.J Natl Cancer Inst. 1989; 81: 1879-1886
National Cancer Institute: Breast cancer risk assessment tool. Availble at: http://www.cancer.gov/bcrisktool/Default.aspx. [Accessed October 1, 2019]
- Doppler ultrasound color flow imaging in the study of breast cancer: preliminary findings.Ultrasound Med Biol. 1990; 16: 553-559
- The Gail model predicts breast cancer in women with suspicious radiographic lesions.Am J Surg. 2005; 190: 526-529
- Validation of the Gail et al. model of breast cancer risk prediction and implications for chemoprevention.J Natl Cancer Inst. 2001; 93: 358-366
- Validating and improving models for projecting the absolute risk of breast cancer.J Natl Cancer Inst. 2001; 93: 334e5
- Breast elastography: how to perform and integrate into a "best-practice" patient treatment algorithm.J Ultrasound Med. 2020; 39: 7-17
- Strain elastography ultrasound: an overview with emphasis on breast cancer diagnosis.Diagnostics (Basel). 2013; 3: 117-125
- Could ultrasonic elastography help the diagnosis of small (≤2 cm) breast cancer with the usage of sonographic BI-RADS classification?.Eur J Radiol. 2012; 81: 3216-3221
- Role and clinical usefulness of elastography in small breast masses.Acad Radiol. 2011; 18: 74-80
Article info
Publication history
Published online: December 28, 2020
Accepted:
December 1,
2020
Received in revised form:
November 29,
2020
Received:
August 8,
2020
Identification
Copyright
© 2020 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
