BI-RADS Lexicon for US and Mammography: Interobserver Variability and Positive Predictive Value

Lazarus, Elizabeth; Mainiero, Martha B.; Schepps, Barbara; Koelliker, Susan; Livingston, Linda S.

doi:10.1148/radiol.2392042127

Cited by 441 publications

(367 citation statements)

References 13 publications

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“…Reported agreements of shape, orientation, and boundary have been moderate-to-substantial, and, for margin, have been fair-to-substantial [14][15][16][17]. Our findings also showed moderate agreement in the assessment of shape, orientation, margin, boundary, and calcifications.…”

Section: Discussionsupporting

confidence: 59%

“…Despite the use of ultrasonographic BI-RADS, the interobserver variability of the use of ultrasonographic BI-RADS terminology has shown agreement ranging from slight-tosubstantial [14][15][16][17]. Reported agreements of shape, orientation, and boundary have been moderate-to-substantial, and, for margin, have been fair-to-substantial [14][15][16][17].…”

Section: Discussionmentioning

confidence: 99%

“…Although agreements of these descriptors were relatively higher, only a fair level of agreement was found for the final assessment in this study. The reported kappa agreements in the final assessment category, as fair and substantial, were also relatively low [14][15][16][17]. For determination of the final assessment, a breast US specialist usually attempts to identify a typical benign feature or suspicious finding.…”

Section: Discussionmentioning

confidence: 99%

“…Until the third edition of BI-RADS, the lexicon was only applicable to mammography. Use of mammographic BI-RADS has resulted in unified understanding and implications of various mammographic terms, as well as increased observer agreement in mammographic readings [13,14]. Recent reports on observer variability with the use of ultrasonographic BI-RADS have shown good results with kappa statistic agreement [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

“…Recent reports on observer variability with the use of ultrasonographic BI-RADS have shown good results with kappa statistic agreement [15][16][17]. Although a high level of agreement has been shown for some descriptors, a final assessment showed a low level of agreement (fair agreement) [14,16]. Therefore, this low level agreement in final assessment leads to a lack of consistency in patient management.…”

Section: Introductionmentioning

confidence: 99%

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A Comparison of Logistic Regression Analysis and an Artificial Neural Network Using the BI-RADS Lexicon for Ultrasonography in Conjunction with Introbserver Variability

et al. 2012

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To determine which Breast Imaging Reporting and Data System (BI-RADS) descriptors for ultrasound are predictors for breast cancer using logistic regression (LR) analysis in conjunction with interobserver variability between breast radiologists, and to compare the performance of artificial neural network (ANN) and LR models in differentiation of benign and malignant breast masses. Five breast radiologists retrospectively reviewed 140 breast masses and described each lesion using BI-RADS lexicon and categorized final assessments. Interobserver agreements between the observers were measured by kappa statistics. The radiologists' responses for BI-RADS were pooled. The data were divided randomly into train (n070) and test sets (n0 70). Using train set, optimal independent variables were determined by using LR analysis with forward stepwise selection. The LR and ANN models were constructed with the optimal independent variables and the biopsy results as dependent variable. Performances of the models and radiologists were evaluated on the test set using receiver-operating characteristic (ROC) analysis. Among BI-RADS descriptors, margin and boundary were determined as the predictors according to stepwise LR showing moderate interobserver agreement. Area under the ROC curves (AUC) for both of LR and ANN were 0.87 (95% CI, 0.77-0.94). AUCs for the five radiologists ranged 0.79-0.91. There was no significant difference in AUC values among the LR, ANN, and radiologists (p>0.05). Margin and boundary were found as statistically significant predictors with good interobserver agreement. Use of the LR and ANN showed similar performance to that of the radiologists for differentiation of benign and malignant breast masses.

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Section: Discussionsupporting

confidence: 59%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Comparison of Logistic Regression Analysis and an Artificial Neural Network Using the BI-RADS Lexicon for Ultrasonography in Conjunction with Introbserver Variability

et al. 2012

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Selective Preoperative Magnetic Resonance Imaging in Women With Breast Cancer

Weber¹,

Bellin²,

Milbourn³

et al. 2012

Arch Surg

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Prognostic significance of synaptophysin in stage I of squamous carcinoma and adenocarcinoma of the lung

González-Aragoneses

Moreno-Mata

Cebollero-Presmanes

et al. 2007

Cancer

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BACKGROUND.The prognostic significance of the presence of a neuroendocrine marker (synaptophysin, SY) was analyzed in stage I of squamous carcinoma and adenocarcinoma of the lung.METHODS.A multicentric retrospective study was conducted with immunohistochemical staining in a single center of 318 patients resected for squamous carcinoma or adenocarcinoma in pathologic stage I.RESULTS.In all, 162 cases of squamous carcinoma and 156 cases of adenocarcinoma were identified, which included 105 patients in stage IA (50 patients with squamous carcinoma and 55 patients with adenocarcinoma) and 213 in stage IB (112 with squamous carcinoma and 101 with adenocarcinoma). Eighty‐six tumors showed a presence of SY+ (27%). Univariate analysis showed lower survival rates at 5 years for those patients older than 70 years of age compared with those patients younger than 70 years of age (60.35% vs 70.57%; P = .007) and for those patients with SY+ compared with those with SY− (52.48% vs 72.68%; P = .0017). Patients with SY+ tumors showed a higher rate of recurrence than patients with SY− tumors (50% vs 33.6%; P = .008). Multivariate analysis showed that those patients greater that 70 years of age (hazard ratio [HR], 1.74; 95% confidence interval [CI], 1.14–2.65) and the presence of SY (HR, 2.15; 95% CI, 1.40–3.30) were significant independent prognostic factors associated with a poor outcome.CONCLUSIONS.Stage I of squamous carcinoma and adenocarcinoma of the lung with SY+ has a poor prognosis, with a higher frequency of recurrence and lower survival rates. Cancer 2007. © 2007 American Cancer Society.

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BI-RADS Lexicon for US and Mammography: Interobserver Variability and Positive Predictive Value

Abstract: Interobserver agreement with the new BI-RADS terminology is good and validates the US lexicon. Subcategories 4a, 4b, and 4c are useful in predicting the likelihood of malignancy.

Cited by 441 publications

References 13 publications

A Comparison of Logistic Regression Analysis and an Artificial Neural Network Using the BI-RADS Lexicon for Ultrasonography in Conjunction with Introbserver Variability

A Comparison of Logistic Regression Analysis and an Artificial Neural Network Using the BI-RADS Lexicon for Ultrasonography in Conjunction with Introbserver Variability

Selective Preoperative Magnetic Resonance Imaging in Women With Breast Cancer

Prognostic significance of synaptophysin in stage I of squamous carcinoma and adenocarcinoma of the lung

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