An evaluation if radiomic features of CT perfusion (CTP) can predict tumor grade and aggressiveness in prostate cancer was performed.
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 post-surgical Gleason score (GS), microvessel density (MVD) and distinguish between the different risk groups.
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).
This exploratory study shows the potential of radiomics to classify prostate cancer.
Anticancer research. 2018 Mar [Epub]
Stephanie Tanadini-Lang, Marta Bogowicz, Patrick Veit-Haibach, Martin Huellner, Chantal Pauli, Vyoma Shukla, Matthias Guckenberger, Oliver Riesterer
Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland ., Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland., Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland., Institute of Surgical Pathology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.