Predicting Invasiveness of Lung Adenocarcinoma from Chest CT with Few-shot Vision-Language Ternary Classification Model - Takeaways - MDSpire

Predicting Invasiveness of Lung Adenocarcinoma from Chest CT with Few-shot Vision-Language Ternary Classification Model

  • By

  • Nan Xu

  • Qianqian He

  • Lu Wang

  • Zhiwen Zhang

  • Qiuju Sheng

  • Shang Gao

  • Shimin Zhang

  • Bosinan Chen

  • Jianing Sun

  • Zhijian Zhang

  • Jie Zhang

  • Jing Qiu

  • Yunan Wang

  • Guanyu Liu

  • Enyu Li

  • Mingke Tian

  • Haotian Wang

  • Jiaping Yu

  • Yan Dong

  • Si Gao

  • Song Chen

  • Fan Yang

  • Zhihui Chang

  • Yue Dong

  • Lina Zhang

  • Jiangdian Song

  • December 20, 2025

  • 0 min

Share

  • 1

    The study involved 848 patients with pathologically confirmed lung adenocarcinoma manifesting as pure ground-glass nodules (pGGNs).

  • 2

    GPT-4o, a vision-language model, outperformed traditional methods in diagnosing pGGN invasiveness with a twenty-shot training approach.

  • 3

    Radiologists using GPT-4o showed improved diagnostic accuracy for pGGN invasiveness, demonstrating high reliability and willingness to use the model.

  • 4

    GPT-4o achieved an average accuracy of 75%, with a sensitivity of 74% and specificity of 86% in detecting pGGN invasiveness.

  • 5

    The study highlights the potential of AI in enhancing noninvasive imaging methods for preoperative evaluation of lung adenocarcinoma.

Original Source(s)

Predicting Invasiveness of Lung Adenocarcinoma from Chest CT with Few-shot Vision-Language Ternary Classification Model

  • by Nan Xu, Qianqian He, Lu Wang, Zhiwen Zhang, Qiuju Sheng, Shang Gao, Shimin Zhang, Bosinan Chen, Jianing Sun, Zhijian Zhang, Jie Zhang, Jing Qiu, Yunan Wang, Guanyu Liu, Enyu Li, Mingke Tian, Haotian Wang, Jiaping Yu, Yan Dong, Si Gao, Song Chen, Fan Yang, Zhihui Chang, Yue Dong, Lina Zhang, Jiangdian Song

  • December 20, 2025

Related Content

ShapeField-lung: continuous shape embedding for early lung cancer detection via pulmonary nodule segmentation

The Importance of Molecular Profiling in Delivering Guideline-Recommended Care—From Genetic Sequencing to Patient Outcomes

Worldwide Impact of Respiratory Cancers in 2022 and Projections for 2050: Incidence and Mortality Data from GLOBOCAN