Cargando…
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
BACKGROUND: Enrichment of tumor-infiltrating lymphocytes (TIL) in the tumor microenvironment (TME) is a reliable biomarker of immune checkpoint inhibitors (ICI) in non-small cell lung cancer (NSCLC). Phenotyping through computed tomography (CT) radiomics has the overcome the limitations of tissue-ba...
Autores principales: | Park, Changhee, Jeong, Dong Young, Choi, Yeonu, Oh, You Jin, Kim, Jonghoon, Ryu, Jeongun, Paeng, Kyunghyun, Lee, Se-Hoon, Ock, Chan-Young, Lee, Ho Yun |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9844154/ https://www.ncbi.nlm.nih.gov/pubmed/36660547 http://dx.doi.org/10.3389/fimmu.2022.1038089 |
Ejemplares similares
-
Pleomorphic carcinoma of the lung: Prognostic models of semantic, radiomics and combined features from CT and PET/CT in 85 patients
por: Kim, Chohee, et al.
Publicado: (2021) -
Artificial Intelligence–Powered Spatial Analysis of Tumor-Infiltrating Lymphocytes as Complementary Biomarker for Immune Checkpoint Inhibition in Non–Small-Cell Lung Cancer
por: Park, Sehhoon, et al.
Publicado: (2022) -
Artificial Intelligence-Powered Whole-Slide Image Analyzer Reveals a Distinctive Distribution of Tumor-Infiltrating Lymphocytes in Neuroendocrine Neoplasms
por: Cho, Hyung-Gyo, et al.
Publicado: (2022) -
Deep Learning Analysis of CT Images Reveals High-Grade Pathological Features to Predict Survival in Lung Adenocarcinoma
por: Choi, Yeonu, et al.
Publicado: (2021) -
Radiomics-guided deep neural networks stratify lung adenocarcinoma prognosis from CT scans
por: Cho, Hwan-ho, et al.
Publicado: (2021)