Simultaneous automatic segmentation of multiple needles using 3D ultrasound for high-dose-rate prostate brachytherapy.
OBJECTIVE
Sagittally reconstructed 3D (SR3D) ultrasound imaging shows promise for improved needle localization for high-dose-rate prostate brachytherapy (HDR-BT); however, needles must be manually segmented intraoperatively while the patient is anesthetized to create a treatment plan. The purpose of this article was to describe and validate an automatic needle segmentation algorithm designed for HDR-BT, specifically capable of simultaneously segmenting all needles in an HDR-BT implant using a single SR3D image with ~5 mm interneedle spacing.


METHODS
The segmentation algorithm involves regularized feature point classification and line trajectory identification based on the randomized 3D Hough transform modified to handle multiple straight needles in a single image simultaneously. Needle tips are identified based on peaks in the derivative of the signal intensity profile along the needle trajectory. For algorithm validation, 12 prostate cancer patients underwent HDR-BT during which SR3D images were acquired with all needles in place. Needles present in each of the 12 images were segmented manually, providing a gold standard for comparison, and using the algorithm. Tip errors were assessed in terms of the 3D Euclidean distance between needle tips, and trajectory error was assessed in terms of 2D distance in the axial plane and angular deviation between trajectories.


RESULTS
In total, 190 needles were investigated. Mean execution time of the algorithm was 11.0 s per patient, or 0.7 s per needle. The algorithm identified 82% and 85% of needle tips with 3D errors ≤3 mm and ≤5 mm, respectively, 91% of needle trajectories with 2D errors in the axial plane ≤3 mm, and 83% of needle trajectories with angular errors ≤3°. The largest tip error component was in the needle insertion direction.


CONCLUSIONS
Previous work has indicated HDR-BT needles may be manually segmented using SR3D images with insertion depth errors ≤3 mm and ≤5 mm for 83% and 92% of needles, respectively. The algorithm shows promise for reducing the time required for the segmentation of straight HDR-BT needles, and future work involves improving needle tip localization performance through improved image quality and modeling curvilinear trajectories.
Department of Medical Biophysics, University of Western Ontario, London, Ontario, N6A 5C1, Canada.|Imaging Research Laboratories, Robarts Research Institute, University of Western Ontario, London, Ontario, N6A 5K8, Canada.
William Thomas
WT
Hrinivich
Department of Medical Biophysics, University of Western Ontario, London, Ontario, N6A 5C1, Canada.|Department of Oncology, University of Western Ontario, London, Ontario, N6A 4L6, Canada.|London Regional Cancer Program, London, Ontario, N6A 5W9, Canada.
Douglas A
DA
Hoover
Department of Medical Biophysics, University of Western Ontario, London, Ontario, N6A 5C1, Canada.|Department of Oncology, University of Western Ontario, London, Ontario, N6A 4L6, Canada.|London Regional Cancer Program, London, Ontario, N6A 5W9, Canada.
Kathleen
K
Surry
Imaging Research Laboratories, Robarts Research Institute, University of Western Ontario, London, Ontario, N6A 5K8, Canada.
Chandima
C
Edirisinghe
Imaging Research Laboratories, Robarts Research Institute, University of Western Ontario, London, Ontario, N6A 5K8, Canada.
Jacques
J
Montreuil
Department of Oncology, University of Western Ontario, London, Ontario, N6A 4L6, Canada.|London Regional Cancer Program, London, Ontario, N6A 5W9, Canada.
David
D
D'Souza
Department of Medical Biophysics, University of Western Ontario, London, Ontario, N6A 5C1, Canada.|Imaging Research Laboratories, Robarts Research Institute, University of Western Ontario, London, Ontario, N6A 5K8, Canada.|Department of Oncology, University of Western Ontario, London, Ontario, N6A 4L6, Canada.|Department of Physics and Astronomy, University of Western Ontario, London, Ontario, N6A 3K7, Canada.
Aaron
A
Fenster
Department of Medical Biophysics, University of Western Ontario, London, Ontario, N6A 5C1, Canada.|Department of Oncology, University of Western Ontario, London, Ontario, N6A 4L6, Canada.|London Regional Cancer Program, London, Ontario, N6A 5W9, Canada.|Department of Physics and Astronomy, University of Western Ontario, London, Ontario, N6A 3K7, Canada.
Eugene
E
Wong
D000465:Algorithms; D016477:Artifacts; D001331:Automation; D001918:Brachytherapy / Q000295:instrumentation*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D009339:Needles; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D011829:Radiation Dosage; D011879:Radiotherapy Dosage; D013997:Time Factors; D014463:Ultrasonography
3D ultrasound; high-dose-rate brachytherapy; needle segmentation; prostate brachytherapy; randomized Hough transform