A Dynamic Dosimetry System for Prostate Brachytherapy

Abstract

The lack of dynamic dosimetry tools for permanent prostate brachytherapy causes otherwise avoidable problems in prostate cancer patient care. The goal of this work is to satisfy this need in a readily adoptable manner. Using the ubiquitous ultrasound scanner and mobile non-isocentric C-arm, we show that dynamic dosimetry is now possible with only the addition of an arbitrarily configured marker-based fiducial. Not only is the system easily configured from accessible hardware, but it is also simple and convenient, requiring little training from technicians. Furthermore, the proposed system is built upon robust algorithms of seed segmentation, fiducial detection, seed reconstruction, and image registration. All individual steps of the pipeline have been thoroughly tested, and the system as a whole has been validated on a study of 25 patients. The system has shown excellent results of accurately computing dose, and does so with minimal manual intervention, therefore showing promise for widespread adoption of dynamic dosimetry.

Keywords: dynamic dosimetry; mobile non-isocentric C-arm; prostate brachytherapy; transrectal ultrasound.

Figure 1

Workflow of ultrasound-fluoroscopic dynamic dosimetry system

Figure 2

Illustrations of simple cylindrical point-based fiducial. (a) Photograph of fiducial with markers numbered and coordinate system defined. (b) Diagram of C-arm; fiducial coordinate system F should be roughly aligned with world coordinate system W. (c) Photograph of fiducial attached to needle-guiding template via a flexible arm.

Figure 3

Illustration of steps for template matching sub-function in fiducial detection. Red dots are the segmented coordinates (both seeds and fiducial), blue crosses represent the projected fiducial template, and green circles are the closest segmented coordinates. (a) Find the two furthest points in template; (b) register these template points to a pair of segmented coordinates; (c) find the closest segmented coordinates to the registered template, (d) calculate the error using these closest coordinates; the error for this case is high.

Figure 4

Images along the image processing pipeline. (a) Undistorted fluoroscopy image. (b) Image after seed segmentation with segmented points as red dots and suspected overlapping seeds in magenta circles. (c) Image after fiducial segmentation with fiducial points now as green dots. (d) 3D reconstruction of points with seeds as red dots and fiducial as green dots. (e) Slice of ultrasound volume before registration with reconstructed seeds as red dots; (f) Slice of final result with seeds registered to the ultrasound volume.

Figure 5

Intraoperative dosimetry result showing cold spot. TRUS image is overlaid with the registered seed reconstruction (red dots), prostate contour (red line) and the 100% isodose level (green line).