Ultrasound-Fluoroscopy Registration for Intraoperative Dynamic Dosimetry in Prostate Brachytherapy

  • Ehsan Dehghan
  • Nathanael Kuo
  • Anton Deguet
  • Yi Le
  • Elwood Armour
  • E. Clif Burdette
  • Danny Y. Song
  • Gabor Fichtinger
  • Jerry L. Prince
  • Junghoon Lee
Chapter

Abstract

Low-dose-rate prostate brachytherapy is a treatment option for low- and mid-risk prostate cancer through introduction of radioactive seeds into the prostate. Seed placement deviations are common and associated with postoperative complications. Dynamic dosimetry is a method to accurately localize the true position of the seeds inside the tissue, calculate the delivered dose, and adapt the implant plan accordingly to compensate for seed placement deviations in the operating room. A practical method for dynamic dosimetry relies on localization of the implanted seeds in 3D space from several C-arm images and registering them to a 3D ultrasound volume of the prostate region. In this chapter we introduce a system and workflow for intraoperative dosimetry for prostate brachytherapy. In the suggested workflow, C-arm images are acquired from different angles and are used to reconstruct the seeds in 3D space. For this purpose, we rely on a method based on dimensionality reduced linear programming to match the projections of a seed in different images and localize the seed positions after automatic C-arm pose correction. In the next step of the workflow, the reconstructed seeds are registered to an ultrasound volume of the prostate in a point-to-volume registration scheme. We tested our method on data from 16 patients and compared our dosimetry results with results from Day-1 CT. In comparison, we achieved absolute error of 2.2 ± 1.8 % (mean ± STD) in estimating the percentage of the prostate volume that receives 100 % of the prescribed dose (V100) and absolute error of 10.5 ± 9.5 % in prediction of the minimum dose delivered to 90 % of the prostate (D90).

Keywords

Migration Covariance Assure 

Notes

Acknowledgments

This research was supported in part by the National Institute of Health/National Cancer Institute (NIH/NCI) under grant 2R44CA099374 and grant 1R01CA151395, and in part by the Department of Defense (DOD) under grant W81XWH-05-1-0407. The first author was with the Queen’s University and the Johns Hopkins University while carrying out this research and was supported in part by the Ontario Ministry of Research and Innovation Postdoctoral Fellowship.

References

  1. 1.
    Siegel R, Ward E, Brawley O, Jemal A (2011) Cancer statistics, 2011. CA Cancer J Clin 61(4):212–236PubMedCrossRefGoogle Scholar
  2. 2.
    Lagerburg V, Moerland MA, Lagendijk JJ, Battermann JJ (2005) Measurement of prostate rotation during insertion of needles for brachytherapy. Radiother Oncol 77(3):318–323PubMedCrossRefGoogle Scholar
  3. 3.
    Yamada Y, Potters L, Zaider M, Cohen G, Venkatraman E, Zelefsky MJ (2003) Impact of intraoperative edema during transperineal permanent prostate brachytherapy on computer-optimized and preimplant planning techniques. Am J Clin Oncol 26(5):e130–e135PubMedCrossRefGoogle Scholar
  4. 4.
    Nath S, Chen Z, Yue N, Trumpore S, Peschel R (2000) Dosimetric effects of needle divergence in prostate seed implant using I125 and Pd103 radioactive seeds. Med Phys 27(5):1058–1066PubMedCrossRefGoogle Scholar
  5. 5.
    Nag S, Ciezki JP, Cormak R, Doggett S, Dewyngaert K, Edmundson GK, Stock RG, Stone NN, Yan Y, Zelefsky MJ (2001) Intraoperative planning and evaluation of permanent prostate brachytherapy: Report of the American Brachytherapy Society. Int J Radiat Oncol Biol Phys 51(5):1422–1430PubMedCrossRefGoogle Scholar
  6. 6.
    Polo A, Salembier C, Venselaar J, Hoskin P (2010) Review of intraoperative imaging and planning techniques in permanent seed prostate brachytherapy. Radiother Oncol 94(1):12–23PubMedCrossRefGoogle Scholar
  7. 7.
    Wei Z, Gardi L, Downey DB, Fenster A (2006) Automated localization of implanted seeds in 3D TRUS images used for prostate brachytherapy. Med Phys 33(7):2404–2417PubMedCrossRefGoogle Scholar
  8. 8.
    Feleppa EJ, Ramachandran S, Alam SK, Kalisz A, Ketterling JA, Ennis RD, Wuu C-S (2002) Novel methods of analyzing radio-frequency echo signals for the purpose of imaging brachytherapy seeds used to treat prostate cancer. In: Proc. SPIEGoogle Scholar
  9. 9.
    Wen X, Salcudean SE, Lawrence PD (2010) Detection of brachytherapy seeds using 3D transrectal ultrasound. IEEE Trans Biomed Eng 57(10):2467–2477PubMedCrossRefGoogle Scholar
  10. 10.
    Holmes DR III, Robb RA (2004) Improved automated brachytherapy seed localization in trans-urethral ultrasound data. In: Proc. SPIEGoogle Scholar
  11. 11.
    McAleavey S, Rubens D, Parker K (2003) Doppler ultrasound imaging of magnetically vibrated brachytherapy seeds. IEEE Trans Biomed Eng 50(2):252–254PubMedCrossRefGoogle Scholar
  12. 12.
    Mitri F, Trompette P, Chapelon J-Y (2004) Improving the use of vibro-acoustography for brachytherapy metal seed imaging: a feasibility study. IEEE Trans Med Imaging 23(1):1–6PubMedCrossRefGoogle Scholar
  13. 13.
    Han BH, Wallner K, Merrick G, Butler W, Sutlief S, Sylvester J (2003) Prostate brachytherapy seed identification on post-implant TRUS images. Med Phys 30(5):898–900PubMedCrossRefGoogle Scholar
  14. 14.
    Nath R, Bice WS, Butler WM, Chen Z, Meigooni AS, Narayana V, Rivard MJ, Yu Y (2009) AAPM recommendations on dose prescription and reporting methods for permanent interstitial brachytherapy for prostate cancer: report of task group 137. Med Phys 36(11):5310–5322PubMedCrossRefGoogle Scholar
  15. 15.
    Persons TM, Webber RL, Hemler PF, Bettermann W, Daniel Bourland J (2000) Brachytherapy volume visualization. In: Proc. SPIEGoogle Scholar
  16. 16.
    Messaris G, Kolitsi Z, Badea C, Pallikarakis N (1999) Three-dimensional localisation based on projectional and tomographic image correlation: an application for digital tomosynthesis. Med Eng Phys 21(2):101–109PubMedCrossRefGoogle Scholar
  17. 17.
    Tutar IB, Managuli R, Shamdasani V, Cho PS, Pathak SD, Kim Y (2003) Tomosynthesis-based localization of radioactive seeds in prostate brachytherapy. Med Phys 30:3135–3142PubMedCrossRefGoogle Scholar
  18. 18.
    Brunet-Benkhoucha M, Verhaegen F, Reniers B, Lassalle S, Beliveau-Nadeau D, Donath D, Taussky D, Carrier J-F (2009) Clinical implementation of a digital tomosynthesis-based seed reconstruction algorithm for intraoperative postimplant dose evaluation in low dose rate prostate brachytherapy. Med Phys 36(11):5235–5244PubMedCrossRefGoogle Scholar
  19. 19.
    Dehghan E, Moradi M, Wen X, French D, Lobo J, James Morris W, Salcudean SE, Fichtinger G (2011) Prostate implant reconstruction from C-arm images with motion-compensated tomosynthesis. Med Phys 38(10):5290–5302PubMedCrossRefGoogle Scholar
  20. 20.
    Lee J, Liu X, Jain A, Song D, Burdette E, Prince J, Fichtinger G (Dec. 2009) Prostate brachytherapy seed reconstruction with Gaussian blurring and optimal coverage cost. IEEE Trans Med Imaging 28(12):1955–1968PubMedCrossRefGoogle Scholar
  21. 21.
    Narayanan S, Cho P, Marks R (2002) Fast cross-projection algorithm for reconstruction of seeds in prostate brachytherapy. Med Phys 29:1572–1579PubMedCrossRefGoogle Scholar
  22. 22.
    Lam ST, Cho PS, Marks RJ II, Narayanan S (2004) Three-dimensional seed reconstruction for prostate brachytherapy using Hough trajectories. Phys Med Biol 49(4):557–569PubMedCrossRefGoogle Scholar
  23. 23.
    Su Y, Davis BJ, Herman MG, Robb RA (2004) Prostate brachytherapy seed localization by analysis of multiple projections: identifying and addressing the seed overlap problem. Med Phys 31(5):1277–1287PubMedCrossRefGoogle Scholar
  24. 24.
    Kon R, Jain A, Fichtinger G (2006) Hidden seed reconstruction from C-arm images in brachytherapy. In: IEEE international symposium on biomedical imaging: nano to macroGoogle Scholar
  25. 25.
    Lee J, Labat C, Jain AK, Song DY, Burdette EC, Fichtinger G, Prince JL (2011) REDMAPS: reduced-dimensionality matching for prostate brachytherapy seed reconstruction. IEEE Trans Med Imaging 30(1):38–51PubMedCrossRefGoogle Scholar
  26. 26.
    Tubic D, Zaccarin A, Beaulieu L, Pouliot J (2001) Automated seed detection and three-dimensional reconstruction. II. Reconstruction of permanent prostate implants using simulated annealing. Med Phys 28(11):2272–2279PubMedCrossRefGoogle Scholar
  27. 27.
    Jain A, Fichtinger G (2006) C-arm tracking and reconstruction without an external tracker. In: Proc. medical image computing and computer assisted intervention (MICCAI)Google Scholar
  28. 28.
    Dehghan E, Jain AK, Moradi M, Wen X, Morris WJ, Salcudean SE, Fichtinger G (2011) Brachytherapy seed reconstruction with joint-encoded C-arm single-axis rotation and motion compensation. Med Image Anal 15:760–771PubMedCrossRefGoogle Scholar
  29. 29.
    Lee J, Kuo N, Deguet A, Dehghan E, Song DY, Burdette EC, Prince JL (2011) Intraoperative 3D reconstruction of prostate brachytherapy implants with automatic pose correction. Phys Med Biol 56(15):5011–5027PubMedCrossRefGoogle Scholar
  30. 30.
    Jain AK, Mustufa T, Zhou Y, Burdette C, Chirikjian GS, Fichtinger G (2005) FTRAC-A robust fluoroscope tracking fiducial. Med Phys 32(10):3185–3198PubMedCrossRefGoogle Scholar
  31. 31.
    Kuo N, Deguet A, Song DY, Burdette EC, Prince JL, Lee J (2012) Automatic segmentation of radiographic fiducial and seeds from X-ray images in prostate brachytherapy. Med Eng Phys 34(1):64–77PubMedCrossRefGoogle Scholar
  32. 32.
    Otsu N (1979) A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern 9(1):62–66CrossRefGoogle Scholar
  33. 33.
    Seber G (2004) Multivariate observations. Hoboken, NJ, Wiley-InterscienceGoogle Scholar
  34. 34.
    Bertsekas PD (1999) Nonlinear programming, 2nd edn. Athena Scientific, Belmont, MAGoogle Scholar
  35. 35.
    Todor DA, Zaider M, Cohen GN, Worman MF, Zelefsky MJ (2003) Intraoperative dynamic dosimetry for prostate implants. Phys Med Biol 48(9):1153–1171PubMedCrossRefGoogle Scholar
  36. 36.
    Jain A, Deguet A, Iordachita I, Chintalapani G, Vikal S, Blevins J, Le Y, Armour E, Burdette C, Song D, Fichtinger G (2012) Intra-operative 3D guidance and edema detection in prostate brachytherapy using a non-isocentric C-arm. Med Image Anal 16(3):731–743PubMedCrossRefGoogle Scholar
  37. 37.
    French D, Morris J, Keyes M, Goksel O, Salcudian SE (2005) Intraoperative dosimetry for prostate brachytherapy from fused ultrasound and fluoroscopy images. Acad Radiol 12(10):1262–1272PubMedCrossRefGoogle Scholar
  38. 38.
    Su Y, Davis BJ, Furutani KM, Herman MG, Robb RA (2007) Seed localization and TRUS-fluoroscopy fusion for intraoperative prostate brachytherapy dosimetry. Comput Aided Surg 12(1):25–34PubMedGoogle Scholar
  39. 39.
    Orio PF III, Tutar IB, Narayanan S, Arthurs S, Cho PS, Kim Y, Merrick G, Wallner KE (2007) Intraoperative ultrasound-fluoroscopy fusion can enhance prostate brachytherapy quality. Int J Radiat Oncol Biol Phys 69(1):302–307PubMedCrossRefGoogle Scholar
  40. 40.
    Tutar IB, Gong L, Narayanan S, Pathak SD, Cho PS, Wallner K, Kim Y (2008) Seed-based transrectal ultrasound-fluoroscopy registration method for intraoperative dosimetry analysis of prostate brachytherapy. Med Phys 35(3):840–848PubMedCrossRefGoogle Scholar
  41. 41.
    Moradi M, Sara Mahdavi S, Dehghan E, Lobo JR, Deshmukh S, James W, Fichtinger G, Salcudean SE (2012) Seed localization in ultrasound and registration to C-arm fluoroscopy using matched needle tracks for prostate brachytherapy. IEEE Trans Biomed Eng 59(9):2558–2567PubMedCrossRefGoogle Scholar
  42. 42.
    Fallavollita P, Karim-Aghaloo Z, Burdette E, Song D, Abolmaesumi P, Fichtinger G (2010) Registration between ultrasound and fluoroscopy or CT in prostate brachytherapy. Med Phys 37(6):2749–2760PubMedCrossRefGoogle Scholar
  43. 43.
    Dehghan E, Lee J, Fallavollita P, Kuo N, Deguet A, Le Y, Clif Burdette E, Song DY, Prince JL, Fichtinger G (2012) Ultrasound-fluoroscopy registration for prostate brachytherapy dosimetry. Med Image Anal 16(7):1347–1358PubMedCrossRefGoogle Scholar
  44. 44.
    Hansen N (2006) The CMA evolution strategy: a comparing review, vol 192. Springer, Berlin, Heidelberg, pp 75–102Google Scholar
  45. 45.
    Chen TK, Thurston AD, Ellis RE, Abolmaesumi P (2009) A real-time freehand ultrasound calibration system with automatic accuracy feedback and control. Ultrasound Med Biol 35(1):79–93PubMedCrossRefGoogle Scholar
  46. 46.
    Rivard MJ, Coursey BM, DeWerd LA, Hanson WF, Saiful Huq M, Ibbott GS, Mitch MG, Nath R, Williamson JF (2004) Update of AAPM task group No. 43 report: a revised AAPM protocol for brachytherapy dose calculations. Med Phys 31(3):633–674PubMedCrossRefGoogle Scholar
  47. 47.
    Lindsay PE, Van Dyk J, Battista JJ (2003) A systematic study of imaging uncertainties and their impact on 125I prostate brachytherapy dose evaluation. Med Phys 30(7):1897–1908PubMedCrossRefGoogle Scholar
  48. 48.
    Moult E, Fichtinger G, Morris W, Salcudean S, Dehghan E, Fallavollita P (2012) Segmentation of iodine brachytherapy implants in fluoroscopy. Int J Comput Assist Radiol Surg 7(6):871–879PubMedCrossRefGoogle Scholar
  49. 49.
    San Filippo C, Fichtinger G, Morris W, Salcudean T, Dehghan E, Fallavollita P (2013) Declustering n-connected components: an example case for the segmentation of iodine implants in C-arm images. In: Int. conf. information processing in computer-assisted interventions (IPCAI), Heidelberg, GermanyGoogle Scholar
  50. 50.
    Fallavollita P, Burdette EC, Song DY, Abolmaesumi P, Fichtinger G (2011) Technical note: unsupervised C-arm pose tracking with radiographic fiducial. Med Phys 38(4):2241–2245PubMedCrossRefGoogle Scholar
  51. 51.
    Grzeda V, Fichtinger G (2010) C-arm rotation encoding with accelerometers. Int J Comput Assist Radiol Surg 5(4):385–391PubMedCrossRefGoogle Scholar
  52. 52.
    Wolff T, Lasso A, Ebenkamp M, Wintermantel E, Fichtinger G (2013) C-arm angle measurement with accelerometer for brachytherapy — an accuracy study. Int J Comput Assist Radiol Surg:1–8Google Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Ehsan Dehghan
    • 1
  • Nathanael Kuo
    • 2
  • Anton Deguet
    • 3
  • Yi Le
    • 4
  • Elwood Armour
    • 4
  • E. Clif Burdette
    • 5
  • Danny Y. Song
    • 4
  • Gabor Fichtinger
    • 6
  • Jerry L. Prince
    • 7
  • Junghoon Lee
    • 4
  1. 1.Clinical Informatics, Interventional, and Translational Solutions (CIITS)Philips Research North AmericaBriarcliff ManorUSA
  2. 2.Department of Biomedical EngineeringJohns Hopkins UniversityBaltimoreUSA
  3. 3.Laboratory for Computational Sensing and Robotics, Whiting School of EngineeringJohns Hopkins UniversityBaltimoreUSA
  4. 4.Department of Radiation Oncology and Molecular Radiation SciencesJohns Hopkins UniversityBaltimoreUSA
  5. 5.Acoustic MedSystems, Inc.SavoyUSA
  6. 6.School of ComputingQueen’s UniversityKingstonCanada
  7. 7.Department of Electrical and Computer EngineeringJohns Hopkins UniversityBaltimoreUSA

Personalised recommendations