A nomogram for diagnosis of BI-RADS 4 breast nodules based on three-dimensional volume ultrasound
Abstract Objectives The classification of malignant breast nodules into four categories according to the Breast Imaging Reporting and Data System (BI-RADS) presents significant variability, posing challenges in clinical diagnosis. This study investigates whether a nomogram prediction model incorpora...
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| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-02-01
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| Series: | BMC Medical Imaging |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12880-025-01580-w |
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| Summary: | Abstract Objectives The classification of malignant breast nodules into four categories according to the Breast Imaging Reporting and Data System (BI-RADS) presents significant variability, posing challenges in clinical diagnosis. This study investigates whether a nomogram prediction model incorporating automated breast ultrasound system (ABUS) can improve the accuracy of differentiating benign and malignant BI-RADS 4 breast nodules. Methods Data were collected for a total of 257 nodules with breast nodules corresponding to BI-RADS 4 who underwent ABUS examination and for whom pathology results were obtained from January 2019 to August 2022. The participants were divided into a benign group (188 cases) and a malignant group (69 cases) using a retrospective study method. Ultrasound imaging features were recorded. Logistic regression analysis was used to screen the clinical and ultrasound characteristics. Using the results of these analyses, a nomogram prediction model was established accordingly. Results Age, distance between nodule and nipple, calcification and C-plane convergence sign were independent risk factors that enabled differentiation between benign and malignant breast nodules (all P < 0.05). A nomogram model was established based on these variables. The area under curve (AUC) values for the nomogram model, age, distance between nodule and nipple, calcification, and C-plane convergence sign were 0.86, 0.735, 0.645, 0.697, and 0.685, respectively. Thus, the AUC value for the model was significantly higher than a single variable. Conclusions A nomogram based on the clinical and ultrasound imaging features of ABUS can be used to improve the accuracy of the diagnosis of benign and malignant BI-RADS 4 nodules. It can function as a relatively accurate predictive tool for sonographers and clinicians and is therefore clinically useful. Advances in knowledge statement we retrospectively analyzed the clinical and ultrasound characteristics of ABUS BI-RADS 4 nodules and established a nomogram model to improve the efficiency of the majority of ABUS readers in the diagnosis of BI-RADS 4 nodules. |
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| ISSN: | 1471-2342 |