This research project aimed to elucidate the association between clinical variables and lung standardized uptake value (SUV) in pretherapeutic [18F]FDG-PET/CT scans of lung cancer patients. The study examined SUV measurements in non-tumorous regions of the lungs from 240 lung cancer patients, comparing SUVMEAN, SUVMAX, SUV95, and ratios of lung tissue to liver tissue and blood pool SUV with various patient characteristics and comorbidities. The analyzed clinical variables included sex, age, BMI, smoking status, pack years, COPD, tumor stage, previous lung operation, previous lung radiation, pleural effusion (PE), pericardial effusion (PCE), diabetes mellitus type II, asthma, coronary heart disease (CHD) and blood hemoglobin level (Hb). This comprehensive analysis aimed to shed light on the interplay between these clinical factors and lung SUV in lung cancer patients, potentially informing more tailored and effective management strategies for the disease.

This dataset comprises essential components for replicating the research findings presented in my dissertation. Included are a README file offering an overview of the dataset's contents and usage instructions, a cohort file containing the dataset used in the study, and R scripts facilitating the reproduction of the analyses outlined in the dissertation. These resources aim to enhance transparency and reproducibility, enabling fellow researchers to validate and build upon the findings of the original research article: https://doi.org/10.3390/diagnostics14111139