Going Inside: Correlation between External and Internal Respiratory Motion

  • Floris Ernst


In an ideal setting, the target area could be located directly using a non-invasive, high resolution, high speed tracking or imaging modality. Currently, however, there is no single device capable of meeting all these demands. Options available are either invasive, like biplanar fluoroscopy [34-38] or EM tracking [2, 20, 41], are still under development, like US tracking [13, 29, 42], live Magnetic Resonance Imaging (MRI) [17, 21, 26, 27] or monoscopic fluoroscopy [3, 4], or require correlation between external signals and sparsely recorded internal data [23, 25, 32, 33]. Since most of these technologies are not yet available clinically (like live MRI, US tracking, or monoscopic fluoroscopy), cannot be used universally (like EMtracking) or are too invasive (like real-time biplanar fluoroscopy), the main focus is placed on hybrid methods which require external surrogates to fill the gaps between less frequently acquired internal data.


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  1. 1.
    Ahn, S., Yi, B., Suh, Y., Kim, J., Lee, S., Shin, S., Choi, E.: A feasibility study on the prediction of tumour location in the lung from skin motion. The British Journal of Radiology 77, 588–596 (2004). DOI  10.1259/bjr/64800801 CrossRefGoogle Scholar
  2. 2.
    Balter, J.M., Wright, J.N., Newell, L.J., Friemel, B., Dimmer, S., Cheng, Y., Wong, J., Vertatschitsch, E., Mate, T.P.: Accuracy of a wireless localization system for radiotherapy. International Journal of Radiation Oncology, Biology, Physics 61(3), 933–937 (2005). DOI  10.1016/j.ijrobp.2004.11.009 CrossRefGoogle Scholar
  3. 3.
    Berbeco, R.I., Jiang, S.B., Sharp, G.C., Chen, G.T.Y., Mostafavi, H., Shirato, H.: Integrated radiotherapy imaging system (IRIS): design considerations of tumour tracking with linac gantry-mounted diagnostic X-ray systems with flatpanel detectors. Physics in Medicine and Biology 49(2), 243–255 (2004). DOI  10.1088/0031-9155/49/2/005 CrossRefGoogle Scholar
  4. 4.
    Cho, B.C., Suh, Y., Dieterich, S., Keall, P.J.: A monoscopic method for realtime tumour tracking using combined occasional X-ray imaging and continuous respiratory monitoring. Physics in Medicine and Biology 53(11), 2837– 2855 (2008). DOI  10.1088/0031-9155/53/11/006 CrossRefGoogle Scholar
  5. 5.
    DeMenthon, D.F., Davis, L.S.: Model-based object pose in 25 lines of code. International Journal of Computer Vision 15(1–2), 123–141 (1995). DOI  10.1007/bf01450852 CrossRefGoogle Scholar
  6. 6.
    Ernst, F., Bruder, R., Schlaefer, A., Schweikard, A.: Correlation between external and internal respiratory motion: a validation study. International Journal of Computer Assisted Radiology and Surgery 6, epub ahead of print (2011). DOI  10.1007/s11548-011-0653-6
  7. 7.
    Ernst, F., Bruder, R., Schlaefer, A., Schweikard, A.: Validating an svr-based correlation algorithm on human volumetric ultrasound data. In: Proceedings of the 25th International Congress and Exhibition on Computer Assisted Radiology and Surgery (CARS’11), International Journal of Computer Assisted Radiology and Surgery, vol. 6, pp. S59–S60. CARS, Berlin, Germany (2011)Google Scholar
  8. 8.
    Ernst, F., Koch, C., Schweikard, A.: A novel recording tool for education and quality assurance in digital angiography. In: 2010 Annual Meeting of the RSNA (2010)Google Scholar
  9. 9.
    Ernst, F., Martens, V., Schlichting, S., Beˇsirevic¸, A., Kleemann, M., Koch, C., Petersen, D., Schweikard, A.: Correlating chest surface motion to motion of the liver using ε-SVR – a porcine study. In: G.Z. Yang, D.J. Hawkes, D. Rueckert, A. Noble, C. Taylor (eds.) MICCAI 2009, Part II, Lecture Notes in Computer Science, vol. 5762, pp. 356–364. MICCAI, Springer, London (2009). DOI  10.1007/978-3-642-04271-3 44
  10. 10.
    George, R., Vedam, S.S., Chung, T.D., Ramakrishnan, V., Keall, P.J.: The application of the sinusoidal model to lung cancer patient respiratory motion. Medical Physics 32(9), 2850–2861 (2005). DOI  10.1118/1.2001220 CrossRefGoogle Scholar
  11. 11.
    Gierga, D.P., Brewer, J., Sharp, G.C., Betke, M., Willett, C.G., Chen, G.T.Y.: The correlation between internal and external markers for abdominal tumors: Implications for respiratory gating. International Journal of Radiation Oncology, Biology, Physics 61(5), 1551–1558 (2005). DOI  10.1016/j.ijrobp.2004.12.013 CrossRefGoogle Scholar
  12. 12.
    Hoisak, J.D.P., Sixel, K.E., Tirona, R., Cheung, P.C.F., Pignol, J.P.: Correlation of lung tumor motion with external surrogate indicators of respiration. International Journal of Radiation Oncology, Biology, Physics 60(4), 1298–1306 (2004). DOI  10.1016/j.ijrobp.2004.07.681 CrossRefGoogle Scholar
  13. 13.
    Hsu, A., Miller, N.R., Evans, P.M., Bamber, J.C.,Webb, S.: Feasibility of using ultrasound for real-time tracking during radiotherapy. Medical Physics 32(6), 1500–1512 (2005). DOI  10.1118/1.1915934 CrossRefGoogle Scholar
  14. 14.
    Jald´en, J., Isaaksson, M.: Temporal prediction and spatial correlation of breathing motion by adaptive filtering. Tech. rep., Stanford University, Stanford, CA (2001)Google Scholar
  15. 15.
    Kanoulas, E., Aslam, J.A., Sharp, G.C., Berbeco, R.I., Nishioka, S., Shirato, H., Jiang, S.B.: Derivation of the tumor position from external respiratory surrogates with periodical updating of the internal/external correlation. Physics in Medicine and Biology 52(17), 5443–5456 (2007). DOI  10.1088/0031- 9155/52/17/023CrossRefGoogle Scholar
  16. 16.
    Khamene, A., Warzelhan, J.K., Vogt, S., Elgort, D., Chefd’Hotel, C., Duerk, J.L., Lewin, J., Wacker, F.K., Sauer, F.: Characterization of internal organ motion using skin marker positions. In: C. Barillot, D.R. Haynor, P. Hellier (eds.) MICCAI 2004, Part II, LNCS, vol. 3217, pp. 526–533. MICCAI, Springer, St. Malo, France (2004)Google Scholar
  17. 17.
    Kirkby, C., Stanescu, T., Rathee, S., Carlone, M., Murray, B., Fallone, B.G.: Patient dosimetry for hybrid mri-radiotherapy systems. Medical Physics 35(3), 1019–1027 (2008). DOI  10.1118/1.2839104 CrossRefGoogle Scholar
  18. 18.
    Kn¨opke, M., Ernst, F.: Flexible Markergeometrien zur Erfassung von Atmungs- und Herzbewegungen an der K¨orperoberfl¨ache. In: D. Bartz, S. Bohn, J. Hoffmann (eds.) 7. Jahrestagung der Deutschen Gesellschaft f¨ur Computer- und Roboterassistierte Chirurgie, vol. 7, pp. 15–16. CURAC, Leipzig, Germany (2008)Google Scholar
  19. 19.
    Koch, N., Liu, H.H., Starkschall, G., Jacobson, M., Forster, K.M., Liao, Z., Komaki, R., Stevens, C.W.: Evaluation of internal lung motion for respiratorygated radiotherapy using MRI: Part I–correlating internal lung motion with skin fiducial motion. International Journal of Radiation Oncology, Biology, Physics 60(5), 1459–1472 (2004). DOI  10.1016/j.ijrobp.2004.05.055 CrossRefGoogle Scholar
  20. 20.
    Kupelian, P.A., Willoughby, T., Mahadevan, A., Djemil, T., Weinstein, G., Jani, S., Enke, C., Solberg, T., Flores, N., Liu, D., Beyer, D., Levine, L.: Multiinstitutional clinical experience with the Calypso system in localization and continuous, real-time monitoring of the prostate gland during external radiotherapy. International Journal of Radiation Oncology, Biology, Physics 67(4), 1088–1098 (2007). DOI  10.1016/j.ijrobp.2006.10.026 CrossRefGoogle Scholar
  21. 21.
    Lagendijk, J.J.W., Raaymakers, B.W., Raaijmakers, A.J.E., Overweg, J., Brown, K.J., Kerkhof, E.M., van der Put, R.W., H˚ardemark, B., van Vulpen, M., van der Heide, U.A.: MRI/linac integration. Radiotherapy and Oncology 86(1), 25–29 (2008). DOI  10.1016/j.radonc.2007.10.034 Google Scholar
  22. 22.
    McClelland, J.R., Blackall, J.M., Tarte, S., Chandler, A.C., Hughes, S., Ahmad, S., Landau, D.B., Hawkes, D.J.: A continuous 4D motion model from multiple respiratory cycles for use in lung radiotherapy. Medical Physics 33(9), 3348–3358 (2006). DOI  10.1118/1.2222079 CrossRefGoogle Scholar
  23. 23.
    Murphy, M.J.: Tracking moving organs in real time. Seminars in Radiation Oncology 14(1), 91–100 (2004). DOI  10.1053/j.semradonc.2003.10.005 CrossRefGoogle Scholar
  24. 24.
    Murphy, M.J., Isaaksson, M., Jald´en, J.: Adaptive filtering to predict lung tumor breathing motion during imageguided radiation therapy. In: Proceedings of the 16th International Conference and Exhibition on Computer Assisted Radiology and Surgery (CARS’02), vol. 16, pp. 539–544. Paris, France (2002)Google Scholar
  25. 25.
    Ozhasoglu, C., Murphy, M.J., Glosser, G., Bodduluri, M., Schweikard, A., Forster, K.M., Martin, D.P., Adler Jr., J.R.: Real-time tracking of the tumor volume in precision radiotherapy and body radiosurgery – a novel approach to compensate for respiratory motion. In: H.U. Lemke, I. Kiyonari, D. Kunio, M.W. Vannier, A.G. Farman (eds.) Computer-Assisted Radiology and Surgery (CARS 2000), pp. 691–696. Elsevier (2000)Google Scholar
  26. 26.
    Raaijmakers, A.J.E., Raaymakers, B.W., Lagendijk, J.J.W.: Experimental verification of magnetic field dose effects for the MRI-accelerator. Physics in Medicine and Biology 52(14), 4283–4291 (2007). DOI  10.1088/0031- 9155/52/14/017CrossRefGoogle Scholar
  27. 27.
    Raaymakers, B.W., Raaijmakers, A.J.E., Kotte, A.N.T.J., Jette, D., Lagendijk, J.J.W.: Integrating an MRI scanner with a 6 MVradiotherapy accelerator: dose deposition in a transverse magnetic field. Physics in Medicine and Biology 49(17), 4109–4118 (2004). DOI  10.1088/0031-9155/49/17/019 CrossRefGoogle Scholar
  28. 28.
    Richter, L., Bruder, R., Schlaefer, A.: Proper force-torque sensor system for robotized TMS: Automatic coil calibration. In: Proceedings of the 24th International Conference and Exhibition on Computer Assisted Radiology and Surgery (CARS’10), International Journal of Computer Assisted Radiology and Surgery, vol. 5, pp. S422–S423. CARS, Geneva, Switzerland (2010)Google Scholar
  29. 29.
    Sawada, A., Yoda, K., Kokubo, M., Kunieda, T., Nagata, Y., Hiraoka, M.: A technique for noninvasive respiratory gated radiation treatment system based on a real time 3d ultrasound image correlation: A phantom study. Medical Physics 31(2), 245–250 (2004). DOI  10.1118/1.1634482 CrossRefGoogle Scholar
  30. 30.
    Sayeh, S.,Wang, J., Main,W.T., Kilby,W., Maurer Jr., C.R.: Robotic Radiosurgery. Treating Tumors that Move with Respiration, 1st edn., chap. Respiratory motion tracking for robotic radiosurgery, pp. 15–30. Springer, Berlin (2007). DOI  10.1007/978-3-540-69886-9
  31. 31.
    Schweikard, A., Glosser, G., Bodduluri, M., Murphy, M.J., Adler Jr., J.R.: Robotic Motion Compensation for Respiratory Movement during Radiosurgery. Journal of Computer-Aided Surgery 5(4), 263–277 (2000). DOI  10.3109/10929080009148894 CrossRefGoogle Scholar
  32. 32.
    Schweikard, A., Shiomi, H., Adler Jr., J.R.: Respiration tracking in radiosurgery. Medical Physics 31(10), 2738–2741 (2004). DOI  10.1118/1.1774132 CrossRefGoogle Scholar
  33. 33.
    Seppenwoolde, Y., Berbeco, R.I., Nishioka, S., Shirato, H., Heijmen, B.: Accuracy of tumor motion compensation algorithm from a robotic respiratory tracking system: A simulation study. Medical Physics 34(7), 2774–2784 (2007). DOI  10.1118/1.2739811 CrossRefGoogle Scholar
  34. 34.
    Shimizu, S., Shirato, H., Kitamura, K., Ogura, S., Akita-Dosaka, H., Tateishi, U., Watanabe, Y., Fujita, K., Shimizu, T., Miyasaka, K.: Fluoroscopic real-time tumor-tracking radiation treatment (RTRT) can reduce internal margin (IM) and set-up margin (SM) of planning target volume (PTV) for lung tumors. In: Proceedings of the 42nd annual ASTRO meeting, International Journal of Radiation Oncology, Biology, Physics, vol. 48, pp. 166–167 (2000). DOI  10.1016/s0360-3016(00)80127-3
  35. 35.
    Shimizu, S., Shirato, H., Kitamura, K., Shinohara, N., Harabayashi, T., Tsukamoto, T., Koyanagi, T., Miyasaka, K.: Use of an implanted marker and realtime tracking of the marker for the positioning of prostate and bladder cancers. International Journal of Radiation Oncology, Biology, Physics 48(5), 1591– 1597 (2000). DOI  10.1016/s0360-3016(00)00809-9 CrossRefGoogle Scholar
  36. 36.
    Shimizu, S., Shirato, H., Ogura, S., Akita-Dosaka, H., Kitamura, K., Nishioka, T., Kagei, K., Nishimura, M., Miyasaka, K.: Detection of lung tumor movement in real-time tumor-tracking radiotherapy. International Journal of Radiation Oncology, Biology, Physics 51(2), 304–310 (2001). DOI  10.1016/s0360- 3016(01)01641-8CrossRefGoogle Scholar
  37. 37.
    Shirato, H., Shimizu, S., Kunieda, T., Kitamura, K., van Herk, M., Kagei, K., Nishioka, T., Hashimoto, S., Fujita, K., Aoyama, H., Tsuchiya, K., Kudo, K., Miyasaka, K.: Physical aspects of a real-time tumor-tracking system for gated radiotherapy. International Journal of Radiation Oncology, Biology, Physics 48(4), 1187 – 1195 (2000). DOI  10.1016/s0360-3016(00)00748-3 CrossRefGoogle Scholar
  38. 38.
    Shirato, H., Shimizu, S., Shimizu, T., Nishioka, T., Miyasaka, K.: Real-time tumour-tracking radiotherapy. The Lancet 353(9161), 1331 – 1332 (1999). DOI  10.1016/s0140-6736(99)00700-x CrossRefGoogle Scholar
  39. 39.
    Vedam, S.S., Kini, V.R., Keall, P.J., Ramakrishnan, V., Mostafavi, H., Mohan, R.: Quantifying the predictability of diaphragm motion during respiration with a noninvasive external marker. Medical Physics 30(4), 505–513 (2003). DOI  10.1118/1.1558675 CrossRefGoogle Scholar
  40. 40.
    West, J.B.: Respiratory Physiology: The Essentials, 8th edn. Lippincott Williams & Wilkins (2008)Google Scholar
  41. 41.
    Willoughby, T.R., Kupelian, P.A., Pouliot, J., Shinohara, K., Aubin, M., III, M.R., Skrumeda, L.L., Balter, J.M., Litzenberg, D.W., Hadley, S.W.,Wei, J.T., Sandler, H.M.: Target localization and real-time tracking using the Calypso 4D localization system in patients with localized prostate cancer. International Journal of Radiation Oncology, Biology, Physics 65(2), 528–534 (2006). DOI  10.1016/j.ijrobp.2006.01.050 Google Scholar
  42. 42.
    Wu, J., Dandekar, O., Nazareth, D., Lei, P., D’Souza, W.D., Shekhar, R.: Effect of ultrasound probe on dose delivery during real-time ultrasound-guided tumor tracking. In: 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS’06), pp. 3799–3802 (2006). DOI  10.1109/iembs.2006.260076
  43. 43.
    Yan, H., Yin, F.F., Zhu, G.P., Ajlouni, M., Kim, J.H.: Adaptive prediction of internal target motion using external marker motion: a technical study. Physics in Medicine and Biology 51(1), 31–44 (2006). DOI  10.1088/0031-9155/51/1/003 CrossRefGoogle Scholar

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© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Floris Ernst
    • 1
  1. 1.Institute for Robotics and Cognitive SystemsUniversity of LübeckLübeckGermany

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