Whether [18F]FDG PET/CT radiomic features provide information on tumor proliferation beyond conventional PET parameters remains uncertain. We investigated their associations with Ki-67 in untreated primary breast carcinoma using a predefined panel of technically reproducible features. This retrospective, single-center study included 42 women and 19 radiomic features previously selected based on interobserver reproducibility and redundancy, independently of Ki-67. Associations with continuous Ki-67 were evaluated using Spearman correlations, permutation tests, bootstrap confidence intervals, and false discovery rate (FDR) correction, alongside four conventional PET parameters. Five radiomic features showed significant associations with Ki-67 after FDR correction. The strongest association was observed for firstorder_90Percentile (ρ = 0.556; 95% CI, 0.279–0.745; q = 0.002), comparable to that of SUVmax (ρ = 0.565). However, none of these five associations remained significant after adjustment for metabolic tumor volume (MTV), SUVmax, or both, followed by FDR correction. Excluding six small lesions attenuated the correlations for both SUVmax (ρ = 0.440) and firstorder_90Percentile (ρ = 0.427). Although several radiomic features were associated with Ki-67, an independent contribution beyond conventional PET parameters was not demonstrated. These findings require confirmation in independent cohorts.
Gynecologic cancers are among the most common cancers in women and are a significant cause of mortality in women worldwide. FDG-PET images play a critical role in several areas of oncology and are an essential tool for the diagnosis and staging of gynecologic cancer, providing information about tumor metabolism. Aim: The aim of this study was to investigate the relationship between tumor differentiation, type of malignancy, and glucose metabolism in patients with confirmed gynecologic cancer. Materials and Methods We performed a retrospective review of 60 consecutive patients (ages 31-76) with histopathologically confirmed gynecologic cancer who underwent PET-CT in our department between January 2021 and March 2022. Quantitative data on glucose metabolism were collected using the maximum standardized uptake value normalized by lean body mass (SULmax). We reviewed a total of 60 patients with a mean age of 60±9 years, and a median of 62. Results: 14 patients were diagnosed with cervical cancer, 20 with endometrial cancer, and 26 with ovarian cancer; 13 patients had well- differentiated cancer, 11 had moderately differentiated cancer, and 36 had poorly differentiated cancer. A positive correlation was observed between the measured SULmax and the degree of tumor differentiation, indicating higher glucose uptake in poorly differentiated cancer. When examining the relationship between the type of cancer and SULmax, we found that endometrial cancer exhibited the highest mean SULmax (8.36±6.75), followed by ovarian cancer and cervical cancer. Additionally, we noted that glucose uptake was higher in patients aged over 62 years. Regardless of the tumor differentiation, the findings in endometrial cancer showed the highest mean SUVmax values in all grades of tumor differentiation. Conclusion: Our study showed that glucose consumption correlates not only with the degree of differentiation but also with age and type of tumor, with the highest values in patients older than 62 years with endometrial cancer. Given the correlation between glucose consumption and tumor aggressiveness, this finding may be important for prognostic evaluation of patients with gynecologic malignancies.
