Introduction Lung cancer ranks second in new cancer cases and first in cancer-related
deaths worldwide. Precision medicine is working on altering treatment approaches and …

Background: Although many works have supported the utility of PET radiomics, several
authors have raised concerns over the robustness and replicability of the results. This study …

Objective To investigate radiomics features extracted from PET and CT components of 18F-
FDG PET/CT images integrating clinical factors and metabolic parameters of PET to predict …

Simple Summary PET enables quantitative assessment of tumour biology in vivo.
Accumulation of F-18 fluorodeoxyglucose (FDG) may reflect tumour metabolic activity …

Radiomics is an upcoming field in nuclear oncology, both promising and technically
challenging. To summarize the already undertaken work on supradiaphragmatic neoplasia …

Purpose Our objective was to establish a random forest model and to evaluate its predictive
capability of the treatment effect of neoadjuvant chemotherapy–radiation therapy. Methods …

Radiomics uses quantitative medical imaging features to predict clinical outcomes.
Currently, in a new clinical application, finding the optimal radiomics method out of the wide …

Lung cancer, the most frequently diagnosed cancer worldwide, is the leading cause of
cancer-associated deaths. In recent years, significant progress has been achieved in basic …

Backgrounds: We aimed to evaluate the predictive efficacy of baseline 18F-FDG PET/CT-
based radiomics analysis for EGFR mutation status, mutation site, and the survival benefit of …

Purpose To determine whether integration of data on body composition and radiomic
features obtained using baseline 18 F-FDG positron emission tomography/computed …