Abstract
Purpose
Dynamic dosimetry is becoming the standard to evaluate the quality of radioactive implants during brachytherapy. For this, it is essential to obtain a 3D visualization of the implanted seeds and their relative position to the prostate. A method was developed to obtain a robust and precise segmentation of seeds in C-arm images, and this approach was tested using clinical datasets.
Method
A region-based implicit active contour approach was used to delineate implanted seeds. Then, a template-based matching was employed to segment iodine implants whereas a K-means algorithm is implemented to resolve palladium seed clusters. To validate the method, 55 C-arm images from 10 patients were used for the segmentation of iodine sources, whereas 225 C-arm images from 16 patients were used for the palladium case.
Results
Compared to manual ground truth segmentation of 6,002 iodine seeds and 15,354 palladium seeds, 98.7 % of iodine sources were automatically detected and declustered showing a false-positive rate of only 1.7 %. A total of 98.7 % of palladium sources were automatically detected and declustered with a false-positive rate of only 2.0 %.
Conclusion
An automated segmentation method was developed that is able to perform the identification and annotation processes of seeds on par with a human expert. This method was shown to be robust and suitable for integration in the dynamic dosimetry workflow of prostate brachytherapy interventions.
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Acknowledgments
Gabor Fichtinger was funded by Cancer Care Ontario as Research Chair in Cancer Imaging.
Conflict of interest
Chiara Amat di San Filippo, Gabor Fichtinger, William James Morris, Septimiu E. Salcudean, Ehsan Dehghan, and Pascal Fallavollita declare no conflict of interests.
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Amat di San Filippo, C., Fichtinger, G., Morris, W.J. et al. Intraoperative segmentation of iodine and palladium radioactive sources in C-arm images. Int J CARS 9, 769–776 (2014). https://doi.org/10.1007/s11548-014-0983-2
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DOI: https://doi.org/10.1007/s11548-014-0983-2