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4D-CT Lung registration using anatomy-based multi-level multi-resolution optical flow analysis and thin-plate splines

  • Original Article
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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

   The accuracy of 4D-CT registration is limited by inconsistent Hounsfield unit (HU) values in the 4D-CT data from one respiratory phase to another and lower image contrast for lung substructures. This paper presents an optical flow and thin-plate spline (TPS)-based 4D-CT registration method to account for these limitations.

Methods

   The use of unified HU values on multiple anatomy levels (e.g., the lung contour, blood vessels, and parenchyma) accounts for registration errors by inconsistent landmark HU value. While 3D multi-resolution optical flow analysis registers each anatomical level, TPS is employed for propagating the results from one anatomical level to another ultimately leading to the 4D-CT registration. 4D-CT registration was validated using target registration error (TRE), inverse consistency error (ICE) metrics, and a statistical image comparison using Gamma criteria of 1 % intensity difference in \(2\,\hbox {mm}^{3}\) window range.

Results

   Validation results showed that the proposed method was able to register CT lung datasets with TRE and ICE values \(<\)3 mm. In addition, the average number of voxel that failed the Gamma criteria was \(<\)3 %, which supports the clinical applicability of the propose registration mechanism.

Conclusion

   The proposed 4D-CT registration computes the volumetric lung deformations within clinically viable accuracy.

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References

  1. Keall PJ, Mageras GS, Balter JM, Emery RS, Forster KM, Jiang SB, Kapatoes JM, Low DA, Murphy MJ, Murray BR, Ramsey CR, van Herk MB, Vedam SS, Wong JW, Yorke E (2006) The management of respiratory motion in radiation oncology report of AAPM Task Group 76. Med Phys 33(10):3874–3900

    Article  PubMed  Google Scholar 

  2. Bortfeld T, Jiang SB, Rietzel E (2004) Effects of motion on the total dose distribution. Semin Radiat Oncol 14(1):41–51

    Article  PubMed  Google Scholar 

  3. Starkschall G, Britton K, McAleer MF, Jeter MD, Kaus MR, Bzdusek K, Mohan R, Cox JD (2009) Potential dosimetry benefits of four-dimensional radiation treatment planning. Med Phys 73(5):1560–1565

    Google Scholar 

  4. Vinogradskiy YY, Balter P, Followill DS, Alvarez PE, White RA, Starkschall G (2009) Comparing the accuracy of 4D photon dose calculation with 3D calculating using moving and deforming phantoms. Med Phys 36(11):5000–5006

    Article  PubMed  Google Scholar 

  5. Vinogradskiy YY, Balter P, Followill DS, Alvarez PE, White RA, Starkschall G (2009) Verification of four dimensional dose calculations. Med Phys 36(8):3438–3447

    Article  PubMed  Google Scholar 

  6. McClelland JR, Hughes S, Modat M, Qureshi A, Ahmad S, Landau D, Ourselin S, Hawkes DJ (2011) Inter-fraction variations in respiratory motion models. Phys Med Biol 56(2011):251–272

    Google Scholar 

  7. Metaxas DN (1996) Physics-based deformable models: applications to computer vision, graphics, and medical imaging, 1st edn. Kluwer Academic Publishers Norwell, MA

    Google Scholar 

  8. Santhanam AP, Willoughby T, Shah A, Meeks SL, Rolland JP, Kupelian P (2008) Real-time simulation of 4D lung tumor radiotherapy using a breathing model. Lect Notes Comput Sci 2:710–717

    Article  Google Scholar 

  9. Klinder T, Lorenz C, von Berg J, Renisch S, Blaffert T, Ostermann J (2008) 4DCT image-based motion field extraction and analysis. In: SPIE Medical, Imaging. SPIE

  10. Guerrero T, Sanders K, Castillo E, Zhang Y, Bidaut L, Pan T, Komaki R (2006) Dynamic ventilation imaging from four-dimensional computed tomography. Phys Med Biol 51(4):777–791

    Article  PubMed  Google Scholar 

  11. Zhang GG, Huang T-C, Guerrero T, Lin K-P, Stevens C, Starkschall G, Forster K (2008) Use of three-dimensional optical flow method in mapping 3D anatomic structure and tumor contours across four-dimensional computed tomography data. J Appl Clin Med Phys 9(1):2738

    PubMed  Google Scholar 

  12. Brock KK (2007) A multi-institution deformable registration accuracy study. Int J Radiat Oncol Biol Phys 69(3):S44

    Article  Google Scholar 

  13. Sarrut D, Boldea V, Ayadi M, Badel J-N, Gineset C, Clippe S, Carrie C (2005) Non-rigid registration method to assess reproducibility of breathing-holding with ABC in lung cancer. Int J Radiat Oncol Biol Phys 61(2):594–607

    Article  PubMed  Google Scholar 

  14. Murphy K, van Ginneken B, Pluim JPW, Klien S, Staring M (2008) Quantitative assessment of registration in thoracic CT. In: First international workshop on pulmonary image processing. pp 203–211

  15. Betke M, Hong H, Thomas D, Chekema P, Ko JP (2003) Landmark detection in the chest and registration of lung surfaces with an application to nodule registration. Med Image Anal 7:265–281

    Article  PubMed  Google Scholar 

  16. Yin Y, Hoffman EA, Lin CL (2009) Mass preserving non-rigid registration of CT lung images using cubic b-spline. Med Phys 36(9):4213–4222

    Article  PubMed  PubMed Central  Google Scholar 

  17. Fan L, Chen CW (1999) 3D warping and registration from lung images. In: Medical Imaging. SPIE, pp 459–470

  18. Fan L, Chen CW, Reinhardt JM, Eric AH (2001) Evaluation and application of 3D lung warping and registration model using HRCT images. In: Medical Imaging. SPIE, pp 234–243

  19. Christensen GE, Song JH, Lu W, Naga IE, Daniel AL (2007) Tracking lung tissue motion and expansion/compression with inverse consistent image registration and spirometry. Med Phys 34(6):2155–2167

    Article  PubMed  Google Scholar 

  20. Christensen GE, Johnson H (2001) Consistent image registration. IEEE Trans Med Imaging 20(7):568–572

    Article  PubMed  CAS  Google Scholar 

  21. Christensen GE (2005) Inverse consistent image registration. In: Handbook of biomedical image analysis vol III. pp 219–250

  22. Ding K, Cao K, Christensen GE, Raghavan ML, Hoffman EA, Reinhardt JM (2008) Registration based lung tissue mechanics assessment during tidal breathing. In: Medical Image Analysis. Lecture notes on computer science, pp 63–72

  23. Pan Y, Kumar D, Hoffman EA, Christensen GE, Mclennan G, Song JH, Ross A, Simon BA, Reinhardt JM (2005) Estimation of regional lung expansion via 3D image registration. In: Medical, Imaging. SPIE

  24. Horn BKP, Schunck BG (1981) Determining optical flow. Artif Intell 17:185–204

    Article  Google Scholar 

  25. Lorenzen P, Davis B, Shen J (2004) Model-based symmetric information theoretic large deformation multi-modal image registration. In: International symposium of Biomedical Imaging. pp 72–723

  26. Wu G, Yap P, Kim M, Shen D (2010) TPS-HAMMER: Improving HAMMER registration algorithm by soft correspondence matching and thin plate splines based deformation interpolation. NeuroImage 49:2225–2233

    Article  PubMed  PubMed Central  Google Scholar 

  27. Shen D, Davatzikos C (2002) HAMMER: Hierarchical attribute matching mechanism for elastic registration. IEEE Trans. Med. Imaging 21(11):1421–1439

    Article  PubMed  Google Scholar 

  28. Wu G, Wang Q, Lian J, Shen D (2011) Re-construction of 4D-CT from a single free-breathing 3D-CT by spatial temporal image registration. In: Information Processing in Medical Imaging. pp 686–698

  29. Vik T, Kabus S, von Berg J, Ens K, Dries S, Klinder T, Lorenz C (2008) Validation and comparison of registration methods for free-breathing 4D lung-CT. In: Medical, Imaging. SPIE

  30. Pflicke H, Sixt M (2009) Preformed portals facilitate dendritic cell entry into afferent lymphatic vessels. J Exp Med 206(13):2925

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  31. Yang D, Brame S, El Naqa I, Aditya A, Wu Y, Goddu SM, Mutic S, Deasy JO, Low DA (2010) DIRART-a software suite for deformable image registration and adaptive radiotherapy research. Med Phys 30(1):67–77

    CAS  Google Scholar 

  32. Low D (2010) Gamma dose distribution evaluation tool. Journal of Physics conference series (250)

  33. Fraass B, Doppke K, Hunt M, Kutcher G, Starkschall G, Stern R, Van Dyke J (1998) American association of physicists in medicine radiation therapy committee task group 53: quality assurance for clinical radiotherapy treatment planning. Med Phys 25(10):1773–1829

    Article  PubMed  CAS  Google Scholar 

  34. Latifi K, Zhang G, Stawicki M, van Elmpt W, Dekker A, Forster K (2013) Validation of three deformable image registration algorithms for the thorax. J Appl Clin Med Phys 14(1):3834

    PubMed  Google Scholar 

  35. Vandemeulebrouche J, Sarrut D, Clarysse P (2007) The POPI-model, a point-validated pixel-based breathing thorax model. International Conference on the Use of Computers in Radiation Therapy

  36. Murphy KJ, van Ginneken B, Reinhardt JM, Kabus S, Ding K, Deng X, Cao K, Du K, Christensen GE, Garcia V, Vercauteren T, Ayache N, Commowick O, Malandain G, Glocker B, Paragios N, Navab N, Gorbunova V, Sporring J, de Bruijne M, Han X, Heinrick MP, Schnabel JA, Jenkinson M, Lorenz C, Modat M, McClelland JR, Ourselin S, Muenzing SEA, Viergever MA, Nigris DD, Collins DL, Arbel T, Peroni M, Li R, Sharp GC, Schmidt-Richberg A, Ehrhardt J, Werner R, Smeets D, Loeckx D, Song G, Tustison N, Avants B, Gee JC, Staring M, Klien S, Stoel BC, Urschler M, Werlberger M, Vandemeulebroucke J, Rit S, Sarrut D, Pluim PW (2011) Evaluation of registration methods on thoracic CT: the Empire 10 challenge. IEEE Trans Med Imaging 30(11):1901–1920

    Google Scholar 

  37. Min Y, Santhanam AP, Neelakkantan H, Ruddy BH, Meeks SL, Kupelian P (2010) A GPU-based framework for modeling real-time 3D lung tumor conformal dosimetry with subject specific lung tumor motion. Phys Med Biol 55(17):5137–5150

    Google Scholar 

  38. Santhanam AP, Min Y, Mudur SP, Rastogi A, Ruddy BH, Shah A, Divo E, Kassab A, Rolland JP, Kupelian P (2010) An inverse hyper-spherical harmonics based formulation for reconstructing 3D volumetric lung deformations. CR MECANIQUE 338(7–8):461–473

    Article  Google Scholar 

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Acknowledgments

This project is supported in part by James and Esther King Grant Florida, National Science Foundation (1200579), and the University of California, Los Angeles.

Conflict of interest

Yugang Min, John Neylon, Amish Shah, Sanford Meeks, Percy Lee, Patrick Kupelian and Anand P. Santhanam declare no conflict of interest.

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Authors and Affiliations

  1. Department of Radiation Oncology, University of California, Los Angeles, CA, USA

    Yugang Min, John Neylon, Percy Lee, Patrick Kupelian & Anand P. Santhanam

  2. Department of Radiation Oncology, MD Anderson Cancer Center, Orlando, FL, USA

    Amish Shah & Sanford Meeks

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  1. Yugang Min
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  2. John Neylon
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Correspondence to Yugang Min.

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Min, Y., Neylon, J., Shah, A. et al. 4D-CT Lung registration using anatomy-based multi-level multi-resolution optical flow analysis and thin-plate splines. Int J CARS 9, 875–889 (2014). https://doi.org/10.1007/s11548-013-0975-7

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  • DOI: https://doi.org/10.1007/s11548-013-0975-7

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