Computerized three-dimensional localization of prostate cancer using contrast-enhanced power Doppler and clustering analysis.
OBJECTIVE
To evaluate the potential benefit of semiautomated localization of prostate cancer using clustering analysis on three-dimensional (3-D) contrast-enhanced power Doppler images.


METHODS
Thirty patients with biopsy-proven prostate cancer and scheduled for radical prostatectomy underwent a 3-D contrast-enhanced power Doppler scan prior to surgery. A 3-D ellipsoid model was manually fitted around the prostate. The model automatically divided the prostate into 12 zones. After calculation of a so-called clustering map, the clustering values of each zone were calculated. They were compared with whole-mount section histopathology. Region-of-interest (ROI) analysis was performed with bootstrapping to evaluate overall performance.


RESULTS
The ROI analysis yielded area under the curve (AUC) values of 0.65 with a corresponding standard error of 0.03.


CONCLUSIONS
Semiautomatic localization based on clustering analysis of blood flow aids in localization of prostate tumors. A clustering map is an easy-to-interpret extension to standard power Doppler images.
van Moerkerk
Hilco
H
Department of Urology, Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands.
Heijmink
Stijn W T P J
SW
Kaa
Christina A Hulsbergen-V D
CA
Barentsz
Jelle O
JO
Witjes
J Alfred
JA
D000368:Aged; D016000:Cluster Analysis; D003287:Contrast Media; D003936:Diagnosis, Computer-Assisted; D006801:Humans; D021621:Imaging, Three-Dimensional; D008297:Male; D008875:Middle Aged; D011471:Prostatic Neoplasms / Q000473:pathology*; D018608:Ultrasonography, Doppler
D003287:Contrast Media