Exploratory radiomics in computed tomography perfusion of prostate cancer

Abstract

Background/Aim: An evaluation if radiomic features of CT perfusion (CTP) can predict tumor grade and aggressiveness in prostate cancer was performed. Materials and Methods: Forty-seven patients had biopsy-confirmed prostate cancer, and received a CTP. Blood volume (BV), blood flow (BF) and mean transit time (MTT) maps were derived and 1,701 radiomic features were determined per patient. Regression models were built to estimate postsurgical Gleason score (GS), microvessel density (MVD) and distinguish between the different risk groups. Results: Six out of the 47 patients had to be excluded from further analysis. A weak relationship between postsurgical GS and one radiomic parameter was found (R2=0.21, p=0.01). The same parameter combined with MTT inter-quartile range was prognostic for the risk group categorisation (AUC=0.81). Two different radiomic parameters were able to distinguish between low-intermediate risk and high-intermediate risk (AUC=0.77). Four parameters correlated with MVD (R2=0.53, p<0.02). Conclusion: This exploratory study shows the potential of radiomics to classify prostate cancer.