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Updated: Feb 15, 2026

Computed Tomography-guided Time-domain Diffuse Fluorescence Tomography in Small Animals for Localization of Cancer Biomarkers
Published on: July 17, 2012
Exploratory Radiomics in Computed Tomography Perfusion of Prostate Cancer
Stephanie Tanadini-Lang1, Marta Bogowicz2, Patrick Veit-Haibach3,4
1Department of Radiation Oncology, University Hospital Zurich, University of Zurich, Zurich, Switzerland stephanie.tanadini-lang@usz.ch.
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 post-surgical 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.
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