A Novel Method for Respiratory Motion Gated With Geometric Sensitivity of the Scanner in 3D PET

PET image quality can be significantly affected by respiratory motion artifacts. To improve image quality, surveillance systems have been developed to track the movements of the subject during scanning. Gating techniques utilizing the tracking information, are able to compensate for subject motion, thereby improving lesion detection. In this paper, we present a gating method that utilizes the Geometric Sensitivity Gating (GSG) of a 3D-PET scanner system operating in list event acquisition mode. As a result of the non-uniform geometric sensitivity, the count rate from a given organ, will depend on the axial location of the organ. Consequently the respiratory phase can be determined from count rate changes which are determined by suitable temporal resolution from the list-mode data stream. The GSG method has several advantages over existing methods; it only uses LOR events. It is non-invasive, no additional hardware device systems and patient preparation required. Using GATE (GEANT4 Application Tomographic Emission) and NCAT (NURBs(Non Uniform Rational B-Splines) Cardiac Torso) software packages, realistic simulations of respiratory motion demonstrate that GSG can be used for respiratory gating. The validation on clinical data demonstrates that GSG is able to reduce respiratory motion artifacts.

[1]  C. Ling,et al.  Effect of respiratory gating on reducing lung motion artifacts in PET imaging of lung cancer. , 2002, Medical physics.

[2]  Dale L Bailey,et al.  Externally triggered gating of nuclear medicine acquisitions: a useful method for partitioning data , 2005, Physics in medicine and biology.

[3]  R. Huesman,et al.  Fine-scale motion detection using intrinsic list mode PET information , 2001, Proceedings IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA 2001).

[4]  M Bloom,et al.  Data acquisition , 1986 .

[5]  Moshi Geso,et al.  The Application of GATE and NCAT to Respiratory Motion Simulation in Allegro PET , 2006, 2006 IEEE Nuclear Science Symposium Conference Record.

[6]  G J Kutcher,et al.  Deep inspiration breath-hold technique for lung tumors: the potential value of target immobilization and reduced lung density in dose escalation. , 1999, International journal of radiation oncology, biology, physics.

[7]  William Paul Segars,et al.  Development of a new dynamic NURBS-based cardiac-torso (NCAT) phantom , 2001 .

[8]  A Ferraz,et al.  Autonomous thyroid nodules. I. A clinical classification and the use of a diagnostic index. , 1972, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[9]  P.H. Pretorius,et al.  Correction of the respiratory motion of the heart by tracking of the center of mass of thresholded projections: a simulation study using the dynamic MCAT phantom , 2001, 2001 IEEE Nuclear Science Symposium Conference Record (Cat. No.01CH37310).

[10]  C Lartizien,et al.  GATE: a simulation toolkit for PET and SPECT. , 2004, Physics in medicine and biology.

[11]  Paul Kinahan,et al.  Attenuation correction for a combined 3D PET/CT scanner. , 1998, Medical physics.

[12]  E. Potchen,et al.  Assessment of hepatic respiratory excursion. , 1972, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[13]  M. V. van Herk,et al.  Precise and real-time measurement of 3D tumor motion in lung due to breathing and heartbeat, measured during radiotherapy. , 2002, International journal of radiation oncology, biology, physics.

[14]  C. L. Le Rest,et al.  Validation of a Monte Carlo simulation of the Philips Allegro/GEMINI PET systems using GATE , 2006, Physics in medicine and biology.

[15]  Yuji Nakamoto,et al.  Clinically significant inaccurate localization of lesions with PET/CT: frequency in 300 patients. , 2003, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[16]  Suleman Surti,et al.  Imaging characteristics of a 3-dimensional GSO whole-body PET camera. , 2004, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[17]  K. Langen,et al.  Organ motion and its management. , 2001, International journal of radiation oncology, biology, physics.

[18]  M. V. van Herk,et al.  Respiratory correlated cone beam CT. , 2005, Medical physics.

[19]  Frederic H Fahey,et al.  Data acquisition in PET imaging. , 2002, Journal of nuclear medicine technology.

[20]  John B. West,et al.  Respiratory Physiology - the Essentials , 1979 .

[21]  M Alber,et al.  An algorithm for automatic determination of the respiratory phases in four-dimensional computed tomography. , 2006, Physics in medicine and biology.