Radiomic analysis offers a powerful tool for the extraction of clinically relevant information
from radiologic imaging. Radiomics can be used to predict patient outcome through …

Radiomics is a rapidly evolving field of research concerned with the extraction of quantitative
metrics—the so-called radiomic features—within medical images. Radiomic features capture …

Two major treatment strategies employed in non-small cell lung cancer, NSCLC, are
tyrosine kinase inhibitors, TKIs, and immune checkpoint inhibitors, ICIs. The choice of …

Lung cancer is responsible for a large proportion of cancer-related deaths across the globe,
with delayed detection being perhaps the most significant factor for its high mortality rate …

Lung malignancies have been extensively characterized through radiomics and deep
learning. By providing a three-dimensional characterization of the lesion, models based on …

Several reports have shown that radiomic features are affected by acquisition and
reconstruction parameters, thus hampering multicenter studies. We propose a method that …

Tumors are characterized by somatic mutations that drive biological processes ultimately
reflected in tumor phenotype. With regard to radiographic phenotypes, generally …

From diagnostics to prognosis to response prediction, new applications for radiomics are
rapidly being developed. One of the fastest evolving branches involves linking imaging …

Lung cancer accounts for the main proportion of malignancy-related deaths and most
patients are diagnosed at an advanced stage. Immunotherapy and targeted therapy have …

Introduction: In this review we describe recent developments in the field of radiomics along
with current relevant literature linking it to tumor biology. We furthermore explore the …