Ultrasound-fluoroscopy registration for prostate brachytherapy dosimetry

Ehsan Dehghan, Junghoon Lee, Pascal Fallavollita, Nathanael Kuo, Anton Deguet, Yi Le, E. Clif Burdette, Danny Y. Song, Jerry L. Prince, Gabor Fichtinger

Research output: Contribution to journalArticlepeer-review

Abstract

Prostate brachytherapy is a treatment for prostate cancer using radioactive seeds that are permanently implanted in the prostate. The treatment success depends on adequate coverage of the target gland with a therapeutic dose, while sparing the surrounding tissue. Since seed implantation is performed under transrectal ultrasound (TRUS) imaging, intraoperative localization of the seeds in ultrasound can provide physicians with dynamic dose assessment and plan modification. However, since all the seeds cannot be seen in the ultrasound images, registration between ultrasound and fluoroscopy is a practical solution for intraoperative dosimetry. In this manuscript, we introduce a new image-based nonrigid registration method that obviates the need for manual seed segmentation in TRUS images and compensates for the prostate displacement and deformation due to TRUS probe pressure. First, we filter the ultrasound images for subsequent registration using thresholding and Gaussian blurring. Second, a computationally efficient point-to-volume similarity metric, an affine transformation and an evolutionary optimizer are used in the registration loop. A phantom study showed final registration errors of 0.84 ± 0.45. mm compared to ground truth. In a study on data from 10 patients, the registration algorithm showed overall seed-to-seed errors of 1.7 ± 1.0. mm and 1.5 ± 0.9. mm for rigid and nonrigid registration methods, respectively, performed in approximately 30. s per patient.

Original languageEnglish (US)
Pages (from-to)1347-1358
Number of pages12
JournalMedical image analysis
Volume16
Issue number7
DOIs
StatePublished - Oct 2012

Keywords

  • Fluoroscopy
  • Prostate Brachytherapy
  • Registration
  • Ultrasound

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Graphics and Computer-Aided Design

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