Development and application of a prognostic model based on radiomics and artificial intelligence for patients with lung adenocarcinoma brain metastasis - Takeaways - MDSpire

Development and application of a prognostic model based on radiomics and artificial intelligence for patients with lung adenocarcinoma brain metastasis

  • By

  • Congying Zheng

  • Xinyuan Yang

  • Musen Ye

  • Kai Tang

  • Shubin Wang

  • June 30, 2026

  • 0 min

Share

  • 1

    The study developed a prognostic model integrating radiomics and clinical factors for lung adenocarcinoma patients with brain metastases.

  • 2

    A cohort of 176 patients was divided into training and test sets to evaluate the model's performance using logistic regression and AUC.

  • 3

    Independent prognostic factors identified included EGFR mutation status, number of brain metastases, and Lung-molGPA score.

  • 4

    The radiomics model achieved AUCs of 0.862 in the training set and 0.829 in the test set, indicating strong diagnostic performance.

  • 5

    The combined nomogram demonstrated superior predictive performance with AUC values of 0.904 and 0.874 in the training and test sets, respectively.

Original Source(s)

Development and application of a prognostic model based on radiomics and artificial intelligence for patients with lung adenocarcinoma brain metastasis

  • by Congying Zheng, Xinyuan Yang, Musen Ye, Kai Tang, Shubin Wang

  • June 30, 2026

Related Content

Mixed adenoneuroendocrine carcinoma of the gallbladder: a case report and literature review

Advances in the prevention and treatment of radiation-induced brain necrosis: a narrative review

Impact of metastatic pattern and histologic subtype on PD-(L)1 inhibitor efficacy in HER2-negative advanced gastric and gastroesophageal cancer: a meta-analysis