Tumor heterogeneity for differentiation between liver tumors and normal liver tissue in 18F-FDG PET/CT - Hartmann, Lynn; Bundschuh, Lena; Zsótér, Norbert; Essler, Markus; Bundschuh, Ralph Alexander (Nuklearmedizin - NuclearMedicine, 2020)
Aim Malignancies show higher spatial heterogeneity than normal tissue. We investigated, if textural parameters from FDG PET describing the heterogeneity function as tool to differentiate between tumor and normal liver tissue.Methods FDG PET/CT scans of 80 patients with liver metastases and 80 patients with results negative upper abdominal organs were analyzed. Metastases and normal liver tissue were analyzed drawing up to three VOIs with a diameter of 25 mm in healthy liver tissue of the tumoral affected and results negative liver, whilst up to 3 metastases per patient were delineated. Within these VOIs 30 different textural parameters were calculated as well as SUV. The parameters were compared in terms of intra-patient and inter-patient variability (2-sided t test). ROC analysis was performed to analyze predictive power and cut-off values.Results 28 textural parameters differentiated healthy and pathological tissue (p < 0.05) with high sensitivity and specificity. SUV showed ability to differentiate but with a lower significance. 15 textural parameters as well as SUV showed a significant variation between healthy tissues out of tumour infested and negative livers. Mean intra- and inter-patient variability of metastases were found comparable or lower for 6 of the textural features than the ones of SUV. They also showed good values of mean intra- and inter-patient variability of VOIs drawn in liver tissue of patients with metastases and of results negative ones.Conclusion Heterogeneity parameters assessed in FDG PET are promising to classify tissue and differentiate malignant lesions usable for more personalized treatment planning, therapy response evaluation and precise delineation of tumors for target volume determination as part of radiation therapy planning.
Keywords: textural analysis; heterogeneity; tissue classification; liver metastases