Artificial Intelligence Ultrasound Breast System Predicts Postoperative Recurrence and Metastasis in Breast Cancer

Strategic Insights -

Research conducted by Second People's Hospital in Anhui, People's Republic of China, has demonstrated the feasibility and efficacy of developing a predictive model for postoperative recurrence and metastasis in breast cancer using the Artificial Intelligence Ultrasound Breast System (AIUBS). The study, published in the American Journal of Translational Research, involved 120 breast cancer patients who underwent surgery between January 2022 and December 2023. The research showed that the AIUBS-based predictive model accurately identified lymph node metastasis, estrogen receptor status, and human epidermal growth factor receptor 2 status as significant predictors of postoperative recurrence and metastasis.

Key Takeaways:

  • The AIUBS-based predictive model demonstrated high predictive accuracy, with an Area Under the Curve of 0.77 (95% CI: 0.68-0.85) and an optimal cutoff value of 0.572, confirming its clinical utility.
  • Logistic regression analysis identified lymph node metastasis (OR = 8.17, 95% CI: 3.51-18.99) and estrogen receptor (ER) status (OR = 0.46, 95% CI: 0.21-0.99) as significant predictors of postoperative recurrence and metastasis.
  • Multivariate analysis confirmed lymph node metastasis (OR = 8.81, 95% CI: 3.68-21.07) and ER status (OR = 0.39, 95% CI: 0.16-0.94) as independent predictors.
  • The study's findings provide valuable support for personalized treatment and follow-up decisions in breast cancer patients.
  • The research was conducted by a team of researchers from Second People's Hospital, including Lili Shen, Xiuli Cheng, Xinyu Tang, and Fang Ma.
  • The study's results demonstrate the potential of Artificial Intelligence in improving breast cancer diagnosis and treatment.

Statistics:

  • 120 breast cancer patients participated in the study, with 58 patients experiencing postoperative recurrence and metastasis, and 62 patients showing no recurrence or metastasis.
  • The research was conducted over a period of 14 months, from January 2022 to December 2023.
  • The AIUBS-based predictive model showed an Area Under the Curve of 0.77 (95% CI: 0.68-0.85), indicating its high predictive accuracy.
  • The optimal cutoff value derived from confusion matrix analysis was 0.572, confirming the model's clinical utility.

Sources:

  • American Journal of Translational Research. Development and evaluation of a predictive model for postoperative recurrence and metastasis in breast cancer using an artificial intelligence ultrasound breast system. 2025;17(5):4038-4053.
  • NewsRx. Second People's Hospital Reports Findings in Personalized Medicine (Development and evaluation of a predictive model for postoperative recurrence and metastasis in breast cancer using an artificial intelligence ultrasound breast system). Journal of Engineering. June 30, 2025; p 2770.