Computerized analysis of prostate lesions in the peripheral zone using dynamic contrast enhanced MRI.
A novel automated computerized scheme has been developed for determining a likelihood measure of malignancy for cancer suspicious regions in the prostate based on dynamic contrast-enhanced magnetic resonance imaging (MRI) (DCE-MRI) images. Our database consisted of 34 consecutive patients with histologically proven adenocarcinoma in the peripheral zone of the prostate. Both carcinoma and non-malignant tissue were annotated in consensus on MR images by a radiologist and a researcher using whole mount step-section histopathology as standard of reference. The annotations were used as regions of interest (ROIs). A feature set comprising pharmacokinetic parameters and a T1 estimate was extracted from the ROIs to train a support vector machine as classifier. The output of the classifier was used as a measure of likelihood of malignancy. Diagnostic performance of the scheme was evaluated using the area under the ROC curve. The diagnostic accuracy obtained for differentiating prostate cancer from non-malignant disorders in the peripheral zone was 0.83 (0.75-0.92). This suggests that it is feasible to develop a computer aided diagnosis system capable of characterizing prostate cancer in the peripheral zone based on DCE-MRI.
Vos
Pieter C
PC
Department of Radiology, Radboud University Nijmegen Medical Centre, Geert Grooteplein 18, 6525 GA Nijmegen, The Netherlands. p.vos@rad.umcn.nl
Hambrock
Thomas
T
Hulsbergen-van de Kaa
Christina A
CA
Fütterer
Jurgen J
JJ
Barentsz
Jelle O
JO
Huisman
Henkjan J
HJ
D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005240:Feasibility Studies; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D011471:Prostatic Neoplasms / Q000175:diagnosis* / Q000473:pathology*; D012372:ROC Curve