Annals of Nuclear Medicine

, Volume 27, Issue 1, pp 65–73 | Cite as

Dynamic sequence respiratory gated perfusion pulmonary SPECT without external tracking device

  • Kenta Sakaguchi
  • Makoto Hosono
  • Masakazu Otsuka
  • Kohei Hanaoka
  • Kimio Usami
  • Tatsuro Uto
  • Kazunari Ishii
Original Article



The purpose of this study was to develop and evaluate a new method for respiratory gated pulmonary perfusion SPECT (RGPS) based on dynamic acquisition without using an external tracking device (ETD) or list-mode data acquisition.


In the phantom study, our method used a dynamic sequence technique, which was specified by sequences of 50-ms acquisition during 30 s per view of SPECT instead of using an ETD. For this purpose, we created a computer program that identified respiratory phases by calculating the center of activity (COA) in each dynamic frame image. We compared RGPS using the dynamic sequence acquisition (RGPS-DS) and RGPS using ETD (RGPS-ETD) in phantom studies employing a cylinder phantom filled with technetium-99m solution attached to an instrument providing a simple harmonic motion. In the patient study, RGPS-DS was applied to data collected from 3 patients during a routine study of Tc-MAA pulmonary perfusion SPECT.


In the phantom study, the calculation of COA indicated a good agreement between RGPS-DS and RGPS-ETD. With an oscillatory phantom movement amplitude of 30 mm, the amplitudes determined by RGPS-DS and RGPS-ETD (28.36 and 27.58 mm, respectively) were identical on considering a pixel size of 4.66 mm for reconstructed SPECT images. In the patient study, applicability of our method to patient data was demonstrated.


We have showed the feasibility of our method to obtain RGPS without ETD, and conclude that RGPS-DS may be an innovative and efficient technique in respiratory gated pulmonary perfusion SPECT. Further studies with a larger number of patients should demonstrate the accuracy of our method.


Respiration tracking device SPECT Lung Dynamic acquisition 



The authors thank Prof. Tetsuo Ito, Prof. Nobuyuki Sugiura, Dr. Norio Tsuchiya, and Dr. Yoshihiro Komeya for scientific advice, and Hideo Morimoto, Hiroshi Takada, Ryou Inoue, Yuko Shintani, Shuhei Yoshida, and Toshiaki Kurokawa for assistance in data acquisition.

Conflict of interest

The authors declare that they have no conflict of interest and source of funding.

Supplementary material

Supplementary material 1 (MPG 1845 kb)

Supplementary material 2 (MPG 2528 kb)

Supplementary material 3 (MPG 1845 kb)

Supplementary material 4 (MPG 1933 kb)


  1. 1.
    Osada H, Machida K, Honda N. Quantification of regional pulmonary flow with 9mTc-MAA SPECT and cine phase contrast MR imaging. Ann Nucl Med. 2002;16(6):423–9.PubMedCrossRefGoogle Scholar
  2. 2.
    Suga K, Kawakami Y, Koike H, Iwanaga H, Tokuda O, Okada M, et al. Lung ventilation-perfusion imbalance in pulmonary emphysema: assessment with automated V/Q quotient SPECT. Ann Nucl Med. 2010;24(4):269–77. doi: 10.1007/s12149-010-0369-7.PubMedCrossRefGoogle Scholar
  3. 3.
    Suga K, Kawakami Y, Zaki M, Yamashita T, Matsumoto T, Matsunaga N. Pulmonary perfusion assessment with respiratory gated 99mTc macroaggregated albumin SPECT: preliminary results. Nucl Med Commun. 2004;25(2):183–93.PubMedCrossRefGoogle Scholar
  4. 4.
    Klein GJ, Reutter BW, Ho MH, Reed JH, Huesman RH. Real-time system for respiratory-cardiac gating in positron tomography. IEEE Trans Nucl Sci. 1998;45(4):2139–43.CrossRefGoogle Scholar
  5. 5.
    McNamara JE, Bruyant P, Johnson K, Feng B, Lehovich A, Gu S, et al. An assessment of a low-cost visual tracking system (VTS) to detect and compensate for patient motion during SPECT. IEEE Trans Nucl Sci. 2008;55(3):992–8. doi: 10.1109/TNS.2008.915688.PubMedCrossRefGoogle Scholar
  6. 6.
    McNamara JE, Pretorius PH, Johnson K, Mukherjee JM, Dey J, Gennert MA, et al. A flexible multicamera visual-tracking system for detecting and correcting motion-induced artifacts in cardiac SPECT slices. Med Phys. 2009;36(5):1913–23.PubMedCrossRefGoogle Scholar
  7. 7.
    Mah D, Hanley J, Rosenzweig KE, Yorke E, Braban L, Ling CC, et al. Technical aspects of the deep inspiration breath-hold technique in the treatment of thoracic cancer. Int J Radiat Oncol Biol Phys. 2000;48(4):1175–85.PubMedCrossRefGoogle Scholar
  8. 8.
    Rosenzweig KE, Hanley J, Mah D, Mageras G, Hunt M, Toner S, et al. The deep inspiration breath-hold technique in the treatment of inoperable non-small-cell lung cancer. Int J Radiat Oncol Biol Phys. 2000;48(1):81–7.PubMedCrossRefGoogle Scholar
  9. 9.
    Suga K, Kawakami Y, Iwanaga H, Tokuda O, Matsunaga N. Automated breath-hold perfusion SPECT/CT fusion images of the lungs. AJR Am J Roentgenol. 2007;189(2):455–63. doi: 10.2214/ajr.06.1290.PubMedCrossRefGoogle Scholar
  10. 10.
    Pazhenkottil AP, Buechel RR, Herzog BA, Nkoulou RN, Valenta I, Fehlmann U, et al. Ultrafast assessment of left ventricular dyssynchrony from nuclear myocardial perfusion imaging on a new high-speed gamma camera. Eur J Nucl Med Mol Imaging. 2010;37(11):2086–92. doi: 10.1007/s00259-010-1507-0.PubMedCrossRefGoogle Scholar
  11. 11.
    Buther F, Dawood M, Stegger L, Wubbeling F, Schafers M, Schober O, et al. List mode-driven cardiac and respiratory gating in PET. J Nucl Med. 2009;50(5):674–81. doi: 10.2967/jnumed.108.059204.PubMedCrossRefGoogle Scholar
  12. 12.
    Rietzel E, Chen GT, Choi NC, Willet CG. Four-dimensional image-based treatment planning: target volume segmentation and dose calculation in the presence of respiratory motion. Int J Radiat Oncol Biol Phys. 2005;61(5):1535–50. doi: 10.1016/j.ijrobp.2004.11.037.PubMedCrossRefGoogle Scholar
  13. 13.
    Okubo M, Nishimura Y, Nakamatsu K, Okumura M, Shibata T, Kanamori S, et al. Static and moving phantom studies for radiation treatment planning in a positron emission tomography and computed tomography (PET/CT) system. Ann Nucl Med. 2008;22(7):579–86. doi: 10.1007/s12149-008-0166-8.PubMedCrossRefGoogle Scholar
  14. 14.
    Bundschuh RA, Martinez-Moeller A, Essler M, Martinez MJ, Nekolla SG, Ziegler SI, et al. Postacquisition detection of tumor motion in the lung and upper abdomen using list-mode PET data: a feasibility study. J Nucl Med. 2007;48(5):758–63. doi: 10.2967/jnumed.106.035279.PubMedCrossRefGoogle Scholar
  15. 15.
    Nehmeh SA, Erdi YE, Ling CC, Rosenzweig KE, Schoder H, Larson SM, et al. Effect of respiratory gating on quantifying PET images of lung cancer. J Nucl Med. 2002;43(7):876–81.PubMedGoogle Scholar
  16. 16.
    Lupi A, Zaroccolo M, Salgarello M, Malfatti V, Zanco P. The effect of 18F-FDG-PET/CT respiratory gating on detected metabolic activity in lung lesions. Ann Nucl Med. 2009;23(2):191–6. doi: 10.1007/s12149-008-0225-1.PubMedCrossRefGoogle Scholar
  17. 17.
    Okubo M, Nishimura Y, Nakamatsu K, Okumura M, Shibata T, Kanamori S, et al. Radiation treatment planning using positron emission and computed tomography for lung and pharyngeal cancers: a multiple-threshold method for [(18)F]fluoro-2-deoxyglucose activity. Int J Radiat Oncol Biol Phys. 2010;77(2):350–6. doi: 10.1016/j.ijrobp.2009.05.025.PubMedCrossRefGoogle Scholar

Copyright information

© The Japanese Society of Nuclear Medicine 2012

Authors and Affiliations

  • Kenta Sakaguchi
    • 1
  • Makoto Hosono
    • 1
  • Masakazu Otsuka
    • 2
  • Kohei Hanaoka
    • 2
  • Kimio Usami
    • 1
  • Tatsuro Uto
    • 2
  • Kazunari Ishii
    • 2
  1. 1.Division of Positron Emission Tomography, Institute of Advanced Clinical MedicineKinki University School of MedicineOsaka-SayamaJapan
  2. 2.Department of RadiologyKinki University School of MedicineOsaka-SayamaJapan

Personalised recommendations