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CT, MR, and ultrasound image artifacts from prostate brachytherapy seed implants: the impact of seed size
Andrew K H Robertson1, Parminder S Basran, Steven D Thomas
1Department of Physics and Astronomy, University of Victoria, Victoria, British Columbia, Canada.
Purpose:
To investigate the effects of brachytherapy seed size on the quality of x-ray computed tomography (CT), ultrasound (US), and magnetic resonance (MR) images and seed localization through comparison of the 6711 and 9011 (125)I sources.
Methods:
For CT images, an acrylic phantom mimicking a clinical implantation plan and embedded with low contrast regions of interest (ROIs) was designed for both the 0.774 mm diameter 6711 (standard) and the 0.508 mm diameter 9011 (thin) seed models (Oncura, Inc., and GE Healthcare, Arlington Heights, IL). Image quality metrics were assessed using the standard deviation of ROIs between the seeds and the contrast to noise ratio (CNR) within the low contrast ROIs. For US images, water phantoms with both single and multiseed arrangements were constructed for both seed sizes. For MR images, both seeds were implanted into a porcine gel and imaged with pelvic imaging protocols. The standard deviation of ROIs and CNR values were used as metrics of artifact quantification. Seed localization within the CT images was assessed using the automated seed finder in a commercial brachytherapy treatment planning system. The number of erroneous seed placements and the average and maximum error in seed placements were recorded as metrics of the localization accuracy.
Results:
With the thin seeds, CT image noise was reduced from 48.5 ± 0.2 to 32.0 ± 0.2 HU and CNR improved by a median value of 74% when compared with the standard seeds. Ultrasound image noise was measured at 50.3 ± 17.1 dB for the thin seed images and 50.0 ± 19.8 dB for the standard seed images, and artifacts directly behind the seeds were smaller and less prominent with the thin seed model. For MR images, CNR of the standard seeds reduced on average 17% when using the thin seeds for all different imaging sequences and seed orientations, but these differences are not appreciable. Automated seed localization required an average (±SD) of 7.0 ± 3.5 manual corrections in seed positions for the thin seed scans and 3.0 ± 1.2 manual corrections in seed positions for the standard seed scans. The average error in seed placement was 1.2 mm for both seed types and the maximum error in seed placement was 2.1 mm for the thin seed scans and 1.8 mm for the standard seed scans.
Conclusions:
The 9011 thin seeds yielded significantly improved image quality for CT and US images but no significant differences in MR image quality.
