Registration between ultrasound and fluoroscopy or CT in prostate brachytherapy.
OBJECTIVE
In prostate brachytherapy, transrectal ultrasound (TRUS) is used to visualize the anatomy, while implanted seeds can be visualized by fluoroscopy. Intraoperative dosimetry optimization is possible using a combination of TRUS and fluoroscopy, but requires localization of the fluoroscopy-derived seed cloud, relative to the anatomy as seen on TRUS. The authors propose to develop a method of registration of TRUS images and the implants reconstructed from fluoroscopy.


METHODS
A phantom was implanted with 48 seeds then imaged with TRUS and CT. Seeds were reconstructed from CT yielding a cloud of seeds. Fiducial-based ground-truth registration was established between the TRUS and CT. TRUS images are filtered, compounded, and registered to the reconstructed implants by using an intensity-based metric. The authors evaluated a volume-to-volume and point-to-volume registration scheme. In total, seven TRUS filtering techniques and three image similarity metrics were analyzed. The method was also tested on human subject data captured from a brachytherapy procedure.


RESULTS
For volume-to-volume registration, noise reduction filter and normalized correlation metrics yielded the best result: An average of 0.54 +/- 0.11 mm seed localization error relative to ground truth. For point-to-volume registration, noise reduction combined with beam profile filter and mean squares metrics yielded the best result: An average of 0.38 +/- 0.19 mm seed localization error relative to the ground truth. In human patient data, C-arm fluoroscopy images showed 81 radioactive seeds implanted inside the prostate. A qualitative analysis showed clinically correct agreement between the seeds visible in TRUS and reconstructed from intraoperative fluoroscopy imaging. The measured registration error compared to the manually selected seed locations by the clinician was 2.86 +/- 1.26 mm.


CONCLUSIONS
Fully automated registration between TRUS and the reconstructed seeds performed well in ground-truth phantom experiments and qualitative observation showed adequate performance on early clinical patient data.
Fallavollita
P
P
School of Computing, Queen's University, Ontario K7L 3N6, Canada. pascal@cs.queensu.ca
Aghaloo
Z Karim
ZK
Burdette
E C
EC
Song
D Y
DY
Abolmaesumi
P
P
Fichtinger
G
G
D001918:Brachytherapy; D005471:Fluoroscopy / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D008297:Male; D011471:Prostatic Neoplasms / Q000175:diagnosis* / Q000532:radiotherapy*; D011881:Radiotherapy, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*; D014463:Ultrasonography / Q000379:methods*