BI-RADS 3 on Screening Breast Ultrasound: What Is It and What Is the Appropriate Management?

Berg, Wendie A.

doi:10.1093/jbi/wbab060

Cited by 19 publications

(5 citation statements)

References 68 publications

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“…Among those, malignancy was found in 3 patients with a negative predictive value of 98.8%. That result was compatible with the literature [19,20] . According to these results, follow-up of BIRADS 3 lesions at 6-month intervals would be an appropriate approach.…”

Section: Discussionsupporting

confidence: 94%

Pathological correlation of BIRADS 3 and 4 breast lesions

Kalaycı,

Çakır,

Kılıç

2024

Int. J. Surg. Sci.

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Background: BIRADS has become the standard in characterizing the radiological findings of the breast lesions. Compared with other categories, BIRADS 3 and 4 are more difficult to manage. The aim was to present our clinical experience in the evaluation of breast lesions classified as BIRADS 3 and 4. Methods: Female patients who underwent surgical intervention for BIRADS 3 or 4 lesions were included in the study. The primary endpoint was the comparison of preoperative BIRADS scores (BIRADS 3 and 4) and postoperative histopathological results. Results: Data of 373 patients with a mean age of 52.3 years was analyzed. Preoperatively, 249 patients had BIRADS 3 lesions, while 124 patients had BIRADS 4 lesions. The mean age of patients with BIRADS 3 lesions was lower than that of patients in BIRADS 4 group. Thirty-six (14.5%) patients in the BIRADS 3 group and 40 (32.3%) patients in the BIRADS 4 group were above 50 years. Malignancy was detected in 3 (1.2%) and 31 (25%) patients in the BIRADS 3 and BIRADS 4 groups, respectively. BIRADS classification was found to be 91.2% sensitive and 72.6% specific, with an accuracy rate of 74.2%. Positive and negative predictive values were 25% and 98.8% respectively. Conclusions: A high malignancy rate of 25% in the BIRADS 4 patients indicated that preoperative histopathological assessment is mandatory. Although 3% malignancy rate in the BIRADS 3 group was low, it was valuable to show the importance of careful physical examination and detailed family history questioning. The malignancy risk in BIRADS 4 lesions was significantly higher in women above 50 years than in younger women, demonstrating that advanced age is an important risk factor for BC.

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Section: Discussionsupporting

confidence: 94%

Pathological correlation of BIRADS 3 and 4 breast lesions

Kalaycı,

Çakır,

Kılıç

2024

Int. J. Surg. Sci.

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“…The Breast Imaging Reporting and Data System (BI-RADS) is a standardized system of reporting breast pathology encountered on mammography and ultrasound [43]. BI-RADS 3 indicate a malignancy rate less than 2% at 2 years of follow-up, as well as necessity of the 6-month follow-up, BI-RADS 4 is a suspicious abnormality, which can represent the chance of being malignant [44].…”

Section: Discussionmentioning

confidence: 99%

Prevalence and correlates of distress in Chinese women with benign breast disease

Gao,

Wang,

Guo

et al. 2023

Preprint

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Purpose: Breast cancer patients often experience high levels of psychological distress, but there is limited research on the psychological distress status of patients with benign breast diseases. This study aims to investigate the psychological distress levels and influencing factors among patients with benign breast disease (BBD). Methods: A cross-sectional study was conducted on BBD patients admitted to a tertiary medical center in China between November 2022 and May 2023. Patient-reported distress and problems were assessed using the distress thermometer (DT) and the 42-item Problem List by the National Comprehensive Cancer Network. Descriptive statistics, chi-square test or Fisher's exact test, and multivariate logistic regression analyses were performed. Receiver operating characteristic analysis was used to evaluate the diagnostic accuracy of the DT in comparison to the Hospital Anxiety and Depression Scale (HADS) and to determine an optimal cutoff score for the DT in this specific population. Results: Among the 255 BBD patients, the mean psychological distress score was 3.69±1.96. The prevalence of psychological distress (≥4 points) was 52%. The main factors causing psychological distress were worry or anxiety (43.5%), fear (21.2%), pain (7.1%), sleep problems (6.7%), and child care responsibilities (5.1%). Multiple logistic regression analysis revealed that age, education, employment, and BI-RADS classification were factors associated with psychological distress in BBD patients. ROC curve analyses showed that a DT cutoff score of 4 had an area under the ROC curve of 0.88 and 0.7 when compared to HADS-A and HADS-D, respectively, indicating good overall accuracy. Conclusions: Patients with benign breast disease also experience significant psychological burden, which requires attention from healthcare professionals. Targeted health education and psychological counseling should be provided to these patients.

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“…The presence of malignancy was considerably less likely if the patient was rated BI‐RADS3 or lower 6,8,9 . In a combined assessment of multiple reports, the incidence of malignancy was only 0.2% at 6 months in lesions determined to be BI‐RADS3 24 . BI‐RADS4a lesions are defined as having malignancy rates of 2%‐10%, and the actual training and test data used in this study showed a malignancy rate of 5.57%.…”

Section: Discussionmentioning

confidence: 99%

Establishment of a deep‐learning system to diagnose BI‐RADS4a or higher using breast ultrasound for clinical application

et al. 2022

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Although the categorization of ultrasound using the Breast Imaging Reporting and Data System (BI‐RADS) has become widespread worldwide, the problem of inter‐observer variability remains. To maintain uniformity in diagnostic accuracy, we have developed a system in which artificial intelligence (AI) can distinguish whether a static image obtained using a breast ultrasound represents BI‐RADS3 or lower or BI‐RADS4a or higher to determine the medical management that should be performed on a patient whose breast ultrasound shows abnormalities. To establish and validate the AI system, a training dataset consisting of 4028 images containing 5014 lesions and a test dataset consisting of 3166 images containing 3656 lesions were collected and annotated. We selected a setting that maximized the area under the curve (AUC) and minimized the difference in sensitivity and specificity by adjusting the internal parameters of the AI system, achieving an AUC, sensitivity, and specificity of 0.95, 91.2%, and 90.7%, respectively. Furthermore, based on 30 images extracted from the test data, the diagnostic accuracy of 20 clinicians and the AI system was compared, and the AI system was found to be significantly superior to the clinicians (McNemar test, p < 0.001). Although deep‐learning methods to categorize benign and malignant tumors using breast ultrasound have been extensively reported, our work represents the first attempt to establish an AI system to classify BI‐RADS3 or lower and BI‐RADS4a or higher successfully, providing important implications for clinical actions. These results suggest that the AI diagnostic system is sufficient to proceed to the next stage of clinical application.

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BI-RADS 3 on Screening Breast Ultrasound: What Is It and What Is the Appropriate Management?

Cited by 19 publications

References 68 publications

Pathological correlation of BIRADS 3 and 4 breast lesions

Pathological correlation of BIRADS 3 and 4 breast lesions

Prevalence and correlates of distress in Chinese women with benign breast disease

Establishment of a deep‐learning system to diagnose BI‐RADS4a or higher using breast ultrasound for clinical application

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