Literature DB >> 15788607

BI-RADS for sonography: positive and negative predictive values of sonographic features.

Andrea S Hong1, Eric L Rosen, Mary S Soo, Jay A Baker.   

Abstract

OBJECTIVE: The purpose of this study was to assess the positive predictive value (PPV) and negative predictive value (NPV) of features described in the new sonographic BI-RADS lexicon for evaluating solid masses with known histologic diagnoses.
MATERIALS AND METHODS: Sonograms of 403 solid lesions were analyzed by one of three dedicated breast radiologists. Each lesion was described using features from the sonographic BI-RADS lexicon. Lesion description and biopsy results were correlated. PPV and NPV were calculated.
RESULTS: Histologic results showed that 141 (35%) of 403 masses were malignant. Sonographic BI-RADS descriptors showing high predictive value for malignancy include spiculated margin (86%, 19/22), irregular shape (62%, 102/164), and nonparallel orientation (69%, 75/109). Sonographic BI-RADS descriptors highly predictive of benign lesions include circumscribed margin (90%, 160/178), parallel orientation (78%, 228/294), and oval shape (84%, 200/237). For the sonographic BI-RADS features of mass margin, shape, orientation, lesion boundary, echo pattern, and posterior acoustic features, descriptors chosen were significantly (p < 0.001) different for malignant and benign masses.
CONCLUSION: Descriptors from the new sonographic BI-RADS lexicon can be useful in differentiating benign from malignant solid masses.

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Mesh:

Year:  2005        PMID: 15788607     DOI: 10.2214/ajr.184.4.01841260

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  68 in total

1.  A comparison of logistic regression analysis and an artificial neural network using the BI-RADS lexicon for ultrasonography in conjunction with introbserver variability.

Authors:  Sun Mi Kim; Heon Han; Jeong Mi Park; Yoon Jung Choi; Hoi Soo Yoon; Jung Hee Sohn; Moon Hee Baek; Yoon Nam Kim; Young Moon Chae; Jeon Jong June; Jiwon Lee; Yong Hwan Jeon
Journal:  J Digit Imaging       Date:  2012-10       Impact factor: 4.056

2.  Additional diagnostic value of shear-wave elastography and color Doppler US for evaluation of breast non-mass lesions detected at B-mode US.

Authors:  Ji Soo Choi; Boo-Kyung Han; Eun Young Ko; Eun Sook Ko; Jung Hee Shin; Ga Ram Kim
Journal:  Eur Radiol       Date:  2016-01-19       Impact factor: 5.315

3.  Optimized approach to decision fusion of heterogeneous data for breast cancer diagnosis.

Authors:  Jonathan L Jesneck; Loren W Nolte; Jay A Baker; Carey E Floyd; Joseph Y Lo
Journal:  Med Phys       Date:  2006-08       Impact factor: 4.071

Review 4.  A review of breast ultrasound.

Authors:  Chandra M Sehgal; Susan P Weinstein; Peter H Arger; Emily F Conant
Journal:  J Mammary Gland Biol Neoplasia       Date:  2006-04       Impact factor: 2.673

5.  Solid breast mass characterisation: use of the sonographic BI-RADS classification.

Authors:  M Costantini; P Belli; C Ierardi; G Franceschini; G La Torre; L Bonomo
Journal:  Radiol Med       Date:  2007-09-20       Impact factor: 3.469

6.  Potential role of shear-wave ultrasound elastography for the differential diagnosis of breast non-mass lesions: preliminary report.

Authors:  Kyung Hee Ko; Hae Kyoung Jung; So Joong Kim; Hyerin Kim; Jung Hyun Yoon
Journal:  Eur Radiol       Date:  2013-10-02       Impact factor: 5.315

7.  A new automated method for the segmentation and characterization of breast masses on ultrasound images.

Authors:  Jing Cui; Berkman Sahiner; Heang-Ping Chan; Alexis Nees; Chintana Paramagul; Lubomir M Hadjiiski; Chuan Zhou; Jiazheng Shi
Journal:  Med Phys       Date:  2009-05       Impact factor: 4.071

8.  Novel computer-aided diagnosis algorithms on ultrasound image: effects on solid breast masses discrimination.

Authors:  Ying Wang; Hong Wang; Yanhui Guo; Chunping Ning; Bo Liu; H D Cheng; Jiawei Tian
Journal:  J Digit Imaging       Date:  2009-11-10       Impact factor: 4.056

9.  The diagnostic performance of leak-plugging automated segmentation versus manual tracing of breast lesions on ultrasound images.

Authors:  Hui Xiong; Laith R Sultan; Theodore W Cary; Susan M Schultz; Ghizlane Bouzghar; Chandra M Sehgal
Journal:  Ultrasound       Date:  2017-01-25

10.  Quantitative assessment of in vivo breast masses using ultrasound attenuation and backscatter.

Authors:  Kibo Nam; James A Zagzebski; Timothy J Hall
Journal:  Ultrason Imaging       Date:  2013-04       Impact factor: 1.578

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