RT Journal Article SR Electronic T1 Texture analysis of 18F-choline uptake in prostate gland of patients with untreated cancer: relationship with risk stratification, additional prostate biopsy findings and patient’s outcome JF Journal of Nuclear Medicine JO J Nucl Med FD Society of Nuclear Medicine SP 1307 OP 1307 VO 61 IS supplement 1 A1 Marco Cuzzocrea YR 2020 UL http://jnm.snmjournals.org/content/61/supplement_1/1307.abstract AB 1307Introduction: PET/CT imaging with 18F-choline for staging prostate cancer patients is currently used in selected cases when there is a high risk of local or distant metastases on the basis of PSA levels, Gleason Score and T grade (Risk Assessment Score: RAS). Radiomic features of PET/CT prostate images could provide additional information to predict the outcome of these high-risk patients. Aim of the study was to assess the relationship between texture analysis of 18F-choline prostate gland uptake and patient’s outcome. Materials and Methods: PET/CT images of 42 males (mean age: 67.6; range: 49-84 yrs) with increased PSA levels (median value 9.3; range: 2.4-329) and histological diagnosis of prostate cancer, were retrospectively evaluated. The radiomic features and metabolic parameters calculated from prostate gland uptake were analyzed for each patient along with RAS. Univariate analysis was performed to assess the relationship of the single parameters with the patient’s outcome expressed in terms of disease free survival and overall survival. The performance of continuous variables was assessed by comparing area under curves (AUC) at ROC analysis. Independent predictors of outcome were also assessed with Cox model multivariate analysis. Results: Among 44 texture features derivable from PET images analysis, 22 were statistically different (p≤0.03) in patients with stable disease and biochemical progression. Significant differences (p<0.01) were also observed in RAS and SUV values. At ROC analysis of radiomic and metabolic features, the best performance for predicting patients outcome was observed when grey level co-occurrence matrix contrast (GLCM_contrast; AUC 0.828; p< 0.001) and grey-level zone length matrix High Gray-level Zone Emphasis (GLZLM_HGZE; AUC=0.858; p<0.001) were used. In particular, a sensitivity (Se), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV) of 77.8, 87.9, 63.6 and 93.5 respectively, was calculated for GLZLM_HGZE (cut-off = 151.4) in the prediction of the different outcome. Similar results was reported for GLCM_contrast (Se 77.8; Sp 84.8; PPV 58.3; NPV 93.3; cut-off= 9.9). At Cox regression, both radiomic parameters were found to be independent variables in the prediction of a different outcome. Conclusions: These preliminary data suggest that texture analysis of prostate 18F-choline uptake is feasible and some radiomic features are related to the prognosis. However, the creation of prognostic/predictive models able to consider the multiplicity of texture features and an increase of the sample size of patents are mandatory.