Insights into Imaging (Feb 2023)

Radiomics-based analysis of CT imaging for the preoperative prediction of invasiveness in pure ground-glass nodule lung adenocarcinomas

  • Hui Feng,
  • Gaofeng Shi,
  • Qian Xu,
  • Jialiang Ren,
  • Lijia Wang,
  • Xiaojia Cai

DOI
https://doi.org/10.1186/s13244-022-01363-9
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 12

Abstract

Read online

Key points Radiomics have potentials to differentiate the invasiveness of pGGNs lung adenocarcinoma. Clinical-radiographic feature adds discriminative value to radiomics in pGGNs pathological subtype. Combined clinical-radiographic-radiomic model can successfully stratify patients into noninvasive pGGNs and invasive pGGNs in patients with resectable lung adenocarcinoma.

Keywords