Radiomics has revolutionized the world of medical imaging. The aim of this review is to guide oncologists in radiomics and its applications in diagnosis, prediction of response and damage, prediction of survival and prognosis in lung cancer. In this review, we analyzed published literature on PubMed and MEDLINE with papers published in the last 10 years. We included papers in English language with information about radiomics features, and diagnostic, predictive and prognosis of radiomics in lung cancer. All citations were evaluated for relevant content and validation.
Relevance for Patients: The evolution of technology allows the development of computer algorithms that facilitate the diagnosis and evaluation of response after different oncological treatments and their non-invasive follow-up.
1. Radiation Oncology Department, Ramón y Cajal Hospital, Madrid, Spain
2. Biomedical Engineering Department, Complutense University, Madrid, Spain
3. Medical Physics Department, Ramón y Cajal Hospital, Madrid, Spain
Carolina de la Pinta Alonso
Radiation Oncology Department. Ramón y Cajal Hospital, Madrid, Spain.
Department of Pharmaceutics, Utrecht University, the Netherlands
Department of Pharmaceutics, Jiaxing University Medical College, Zhejiang, China