Insights Into Imaging

🫁 CT radiomics combined with H&E pathology enables non-invasive prediction of PD-L1 in non-small cell lung cancer.

📊 Fusion model outperforms single-modality approaches
📈 Higher scores associate with survival and immunotherapy outcomes
🎯 Supports precision immunotherapy decision-making

https://link.springer.com/article/10.1186/s13244-026-02322-4 (Dingpin Huang et al.)

🆕Adding contrast-enhanced magnetic resonance imaging to T2-weighted imaging and diffusion-weighted imaging significantly improves the assessment of vaginal fornix invasion in cervical carcinoma.

📈 Higher diagnostic accuracy and specificity
🤝 Improved agreement between radiologists
🔍 Better visualization of tumor margins and mucosal continuity

https://link.springer.com/article/10.1186/s13244-026-02323-3 (Siqi Wu et al.)