Lung cancer

2023_01

Tumor-infiltrating lymphocyte enrichment predicted by CT radiomics analysis is associated with clinical outcomes of non-small cell lung cancer patients receiving immune checkpoint inhibitors

Park et al.

https://pubmed.ncbi.nlm.nih.gov/36660547/

Highlights

The authors demonstrated that a radiomics system can predict the tumor-infiltrating lymphocyte characteristics in the tumor microenvironment (TME) using only CT scan features. The radiomic system was developed using information from H & E slides about the TME. In this CT radiomics model, predicted TIL enrichment score was significantly associated with immune checkpoint inhibitor outcomes in NSCLC patients

2022_09

Clinical Impact and Generalizability of a Computer-Assisted Diagnostic Tool to Risk-Stratify Lung Nodules With CT

Adams et al.

https://pubmed.ncbi.nlm.nih.gov/36064040/

Highlights

A computer-assisted diagnosis software improved risk classification from chest CTs of screening and incidentally detected lung nodules compared with Lung-RADS. mSI (malignancy Similarity Index) added predictive value independent of existing radiological and clinical variables.