Dataset related to article "Prognostic Impact of Intratumoral Heterogeneity Based on Fractal Geometry Analysis in Operated NSCLC Patients"

This record contains raw data related to article "Prognostic Impact of Intratumoral Heterogeneity Based on Fractal Geometry Analysis in Operated NSCLC Patients" PURPOSE: To determine the heterogeneity of glucose uptake applying fractal analysis on positron emission tomography/computed tomography (PET/CT) with 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG) images in patients with non-small cell lung carcinoma (NSCLC) before surgery, and to assess whether this heterogeneity was associated with disease-free survival (DFS). PROCEDURES: [¹⁸F]FDG PET/CT scans of 113 patients' prior surgery were retrospectively revised. PET DICOM images were analyzed for fractal geometry using a ad hoc software to automatically determine the following indexes: (a) mean intensity value (MIV), (b) standard deviation (SD), (c) relative dispersion (RD), (d) three-dimensional (3D) histogram of the fractal dimension (3D HIST FR DIM), and (e) fractal dimension in 3D (3D-FD). All the fractal indexes were subsequently compared with metabolic parameters and disease-free survival (DFS). RESULTS: We found a significant correlation between 3D-FD and SUVmax, SUVmean, MTV, and TLG. Additionally, positive correlations between MIV, SD, and all metabolic parameters were also detected. Patients with high 3D-FD tumor (≥ 1.62) showed significantly higher values of SUVmax, SUVmean, MTV, and TLG than those with lower 3D-FD. In univariate analysis, median 3D-FD and median TLG were significantly associated with DFS (p = 0.04 and p = 0.03, respectively). These findings were confirmed on log-rank test. On multivariate analysis, among age, stage disease, histotype, 3D-FD, and metabolic parameters, only 3D-FD was identified as independent prognostic factor for DFS (p = 0.032; HR 0.418, 95 % CI 0.189-0.926). 3D-FD was different between adenocarcinoma and squamous cell carcinoma (1.60 versus 1.88, p = 0.014), and 3D-FD value was found higher in advanced stage disease. CONCLUSIONS: Metabolic heterogeneity determined applying fractal principles on PET images can be considered as a novel imaging biomarker for survival in patients with NSCLC.