title: Adaptation of a 3D prostate cancer atlas for transrectal ultrasound guided target-specific biopsy.
abstract: Due to lack of imaging modalities to identify prostate cancer in vivo, current TRUS guided prostate biopsies are taken randomly. Consequently, many important cancers are missed during initial biopsies. The purpose of this study was to determine the potential clinical utility of a high-speed registration algorithm for a 3D prostate cancer atlas. This 3D prostate cancer atlas provides voxel-level likelihood of cancer and optimized biopsy locations on a template space (Zhan et al 2007). The atlas was constructed from 158 expert annotated, 3D reconstructed radical prostatectomy specimens outlined for cancers (Shen et al 2004). For successful clinical implementation, the prostate atlas needs to be registered to each patient's TRUS image with high registration accuracy in a time-efficient manner. This is implemented in a two-step procedure, the segmentation of the prostate gland from a patient's TRUS image followed by the registration of the prostate atlas. We have developed a fast registration algorithm suitable for clinical applications of this prostate cancer atlas. The registration algorithm was implemented on a graphical processing unit (GPU) to meet the critical processing speed requirements for atlas guided biopsy. A color overlay of the atlas superposed on the TRUS image was presented to help pick statistically likely regions known to harbor cancer. We validated our fast registration algorithm using computer simulations of two optimized 7- and 12-core biopsy protocols to maximize the overall detection rate. Using a GPU, patient's TRUS image segmentation and atlas registration took less than 12 s. The prostate cancer atlas guided 7- and 12-core biopsy protocols had cancer detection rates of 84.81% and 89.87% respectively when validated on the same set of data. Whereas the sextant biopsy approach without the utility of 3D cancer atlas detected only 70.5% of the cancers using the same histology data. We estimate 10-20% increase in prostate cancer detection rates when TRUS guided biopsies are assisted by the 3D prostate cancer atlas compared to the current standard of care. The fast registration algorithm we have developed can easily be adapted for clinical applications for the improved diagnosis of prostate cancer.
authors.affiliation: Eigen Inc, Grass Valley, CA, USA.
authors.forename: R
authors.initials: R
authors.lastname: Narayanan
authors.forename: P N
authors.initials: PN
authors.lastname: Werahera
authors.forename: A
authors.initials: A
authors.lastname: Barqawi
authors.forename: E D
authors.initials: ED
authors.lastname: Crawford
authors.forename: K
authors.initials: K
authors.lastname: Shinohara
authors.forename: A R
authors.initials: AR
authors.lastname: Simoneau
authors.forename: J S
authors.initials: JS
authors.lastname: Suri
mesh_terms: D001707:Biopsy, Needle / Q000379:methods*; D003198:Computer Simulation; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D008953:Models, Anatomic; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D012007:Rectum / Q000000981:diagnostic imaging / Q000473:pathology; D013382:Subtraction Technique; D018084:Ultrasonography, Interventional / Q000379:methods*