A comparative study on the features of breast sclerosing adenosis and invasive ductal carcinoma via ultrasound and establishment of a predictive nomogram

Abstract

Objective: To analyze the clinical and ultrasonic characteristics of breast sclerosing adenosis (SA) and invasive ductal carcinoma (IDC), and construct a predictive nomogram for SA.

Materials and methods: A total of 865 patients were recruited at the Second Hospital of Shandong University from January 2016 to November 2022. All patients underwent routine breast ultrasound examinations before surgery, and the diagnosis was confirmed by histopathological examination following the operation. Ultrasonic features were recorded using the Breast Imaging Data and Reporting System (BI-RADS). Of the 865 patients, 203 (252 nodules) were diagnosed as SA and 662 (731 nodules) as IDC. They were randomly divided into a training set and a validation set at a ratio of 6:4. Lastly, the difference in clinical characteristics and ultrasonic features were comparatively analyzed.

Result: There was a statistically significant difference in multiple clinical and ultrasonic features between SA and IDC (P<0.05). As age and lesion size increased, the probability of SA significantly decreased, with a cut-off value of 36 years old and 10 mm, respectively. In the logistic regression analysis of the training set, age, nodule size, menopausal status, clinical symptoms, palpability of lesions, margins, internal echo, color Doppler flow imaging (CDFI) grading, and resistance index (RI) were statistically significant (P<0.05). These indicators were included in the static and dynamic nomogram model, which showed high predictive performance, calibration and clinical value in both the training and validation sets.

Conclusion: SA should be suspected in asymptomatic young women, especially those younger than 36 years of age, who present with small-size lesions (especially less than 10 mm) with distinct margins, homogeneous internal echo, and lack of blood supply. The nomogram model can provide a more convenient tool for clinicians.

Keywords: BI-RADS; invasive ductal carcinoma; nomogram; sclerosing adenosis; ultrasonic features.

Figure 1

Flowchart of this study.

Figure 2

RCS curve. RCS curve displaying the relationship between age (A) and size (B) with the probability of SA. The gray shaded area represents 95% CI, the black horizontal dashed line represents OR=1, and the black vertical dashed line denotes the cut-off values of age and size.

Figure 3

Static and dynamic nomogram model. The nomogram was constructed based on logistic regression analysis results of ultrasound features to predict the diagnosis of SA, and the dynamic nomogram is available at http://saprediction.shinyapps.io/SAdynamic. The model consisted of age (years), size (mm), menopausal status, clinical symptoms, palpation, margin, internal echo, CDFI grading, and RI.

Figure 4

Ultrasonic cases and their nomograms. (A) A 35-year-old (55 points) female patient, who was premenopausal (15 points), sought medical attention due to breast pain (0 points) and had no evident mass on palpation (22 points). Ultrasound examination revealed a 19 × 17 × 13 mm nodule (82 points) in the left breast, with distinct margins (22 points), heterogeneous (0 points), with a CDFI level of 0-I (18 points), an RI of 0.59 (20 points), and was categorized as BI-RADS 4a. The total score was 234 (55 + 15 + 0+22 + 82 + 22 + 0+18 + 20 = 234). The probability of SA for this nodule was greater than 0.9. Histopathological results: SA. (B) A 65-year-old (25 points) female patient, who was menopausal (0 points), sought medical attention owing to breast pain and a conscious breast nodule (0 points), and the nodule was palpable (0 points). Ultrasound examination delineated a 14×13 ×13 mm nodule (86 points) in the left breast, with indistinct margins (0 points), heterogeneous (0 points), a CDFI level of 0-I (18 points), an RI of 0.73 (0 points), and was classified as BI-RADS 5. The total score was 129 points (25 + 0 + 0+0 + 86 + 0+0 + 18 + 0 = 129 points). The probability of SA for this nodule was less than 0.01. Histopathological results: IDC.

Figure 5

ROC curve of the training set (A) and validation set (B).

Figure 6

Calibration curve of the training set (A) and validation set (B). The calibration curve represents the relationship between the predicted probability (x-axis) and the actual probability (y-axis) of SA, the dashed line on the diagonal portrays the predicted probability=actual probability, and the solid line represents the calibration curve of the nomogram. The curves of the training and validation set were close to the dashed line, indicating high calibration accuracy.

Figure 7

DCA of the training set (A) and validation set (B). In both the training set (threshold 0-0.94) and the validation set (threshold 0-0.96), the nomogram exhibited clinical benefits.