Radiomics describes the extraction of multiple features from medical images, including
molecular imaging modalities, that with bioinformatic approaches, provide additional …

Lung cancer is highly aggressive, which has a high mortality rate. Major types encompass
lung adenocarcinoma, lung squamous cell carcinoma, lung adenosquamous carcinoma …

Purpose Radiomics describes the extraction of multiple, otherwise invisible, features from
medical images that, with bioinformatic approaches, can be used to provide additional …

Radiomics is a recent area of research in precision medicine and is based on the extraction
of a large variety of features from medical images. In the field of radiation oncology …

Non-small-cell lung cancer is the most common type of lung cancer and one of the leading
causes of cancer-related death worldwide. For this reason, advances in diagnosis and …

It is now recognized that intratumoral heterogeneity is associated with more aggressive
tumor phenotypes leading to poor patient outcomes (1). Medical imaging plays a central role …

Radiomics is an evolving field in which the extraction of large amounts of features from
diagnostic medical images may be used to predict underlying molecular and genetic …

Considering the potential of PET imaging for precision medicine and drug development in
lung and other types of cancer, increasing efforts are warranted to standardize PET …

Purpose To evaluate the performances and perspectives of heterogeneity analysis of FDG
PET imaging in oncology. Methods We performed a review of the literature using …

Lung cancer is the most common cancer, worldwide, and a major health issue with a
remarkable mortality rate. 2-[18 F] fluoro-2-deoxy-D-glucose positron emission …