Objective:

To utilize the advantages of digital breast tomosynthesis (DBT) in assessing lesion margins and to explore the relationship between the burr sign of DBT images and Ki-67 proliferation index.

Methods:

DBT imaging data of 99 patients with invasive breast cancer who in the First Affiliated Hospital of Zhengzhou University from March 2022 to

April 2023 were retrospectively included

and all of the patients showed a burr-type mass in DBT images. Lump size

length and width of the burr

coverage of the burr at the tumor margin

and number of burrs were analyzed in 99 cases of breast burr-type lumps

and general clinical data of the patients were collected to compare the differences of each parameter between the Ki-67 proliferation index expression states. Independent predictors of Ki-67 proliferation index were analyzed using multifactorial logistic regression

and the diagnostic efficacy was evaluated using subject working curves.

Results:

The differences in DBT image burr characteristics including burr length and burr width were statistically significant when comparing Ki-67 proliferation index high patients and low patients (

P

＜0.05)

whereas the differences in the number of burrs

age of patients

menopausal status

and size of the mass were not statistically significant (

P

=0.060

P

=0.175

P

=0.507

and

P

=0.050

respectively). Multifactorial logistic regression model analysis showed that burr length (OR=0.036

P

＜0.001) and burr width (OR=8.829

P

＜0.001) were independent predictors of Ki-67 proliferation index. The best diagnostic efficacy was achieved when combining burr length with burr width

with an AUC of 0.897.

Conclusion:

Burr sign analysis in DBT images of breast cancer can be used as a noninvasive predictor of the proliferative activity of malignant tumors to determine patient prognosis.