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Using an ultrasound-derived model to assist in dosimetry for prostate cancer treatment through brachytherapy

University of British Columbia

Prostate cancer is the most common form of cancer affecting men in Canada. Patients with localized, early stage disease are often treated using prostate brachytherapy, a technique that involves surgically implanting small radioactive capsules or “seeds” in the prostate. Implantation is performed under the guidance of transrectal ultrasound (TRUS) imaging, and treatment is assessed postoperatively for quality assurance purposes. Pelvic CT imaging is used to evaluate the dose delivered to the target; however, it is a challenge to consistently and confidently identify prostate boundaries due to the poor soft tissue contrast on CT. This leads to large variability in CT-defined anatomical contours and calculated dosimetric quality assurance parameters, and has led to increased reliance on other imaging technologies such as MR. Meanwhile, TRUS typically provides high-quality anatomical visualization, but provides insufficient information for dose calculation purposes. We have developed a new method to transfer ultrasound-based contours to CT images using mathematical modeling and a novel registration technique. The prostate model, derived from TRUS contours, is generated via two streams: one assumes a modified ellipsoid shape (model X), and the other performs a straightforward linear interpolation (model Y). Both are manipulated to account for expected deformations such as TRUS-probe compression and edema. Registration from TRUS to CT spatial coordinates is based on matched seed locations. We evaluate the quality of model-generated contours primarily by comparing the measured volume and dosimetric parameters to the observed variability range determined from manual CT contours. In 19 of model X, and 18 of model Y, cases out of 20, volumes produced were within the variability observed from 5 experienced physicians. However, dose parameters agreed in only a moderate number of cases (9–13), partly motivating a region-specific analysis. We found the least agreement in the posterior apex, with model contours tending to be larger. We discuss the possible reasons for this, as well as implications on the role of modeling in an applied clinical setting. Ultimately, the ultrasound-informed model shows promise, and has many benefits relative to other methods, such those based on CT or MR.

Text

2013-08-23

Attribution-NonCommercial-NoDerivs 2.5 Canada

http://hdl.handle.net/2429/44886

Physics

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/2.5/ca/