Motion correction of rodent thoracic PET image using radioactive bead and MRI image

PET image of tumor located in thoracic region was affected by various organ motions such as respiration and heartbeat. Thoracic motion is difficult to estimate and correct accurately using external measurement or anatomical image solely. The aim of this study was to compare the accuracy of motion correction using PET fiducial mark and 3D MRI image. The radioactive bead for PET fiducial mark was realized from molecular sieve contained 0.37 MBq F-18 and placed in thoracic region. PET study was performed using a small animal PET scanner after IV injection of FDG. MRI study was performed using 3-T clinical MRI system with 3D T1-VIBE (TR/TE=5.67/1.42 ms) sequence. Motion corrected PET image was created by mutual information registration with B-Spline interpolation to the mean image after first realignment. FWHM of lung and liver region in static PET image was 4.77±0.87 and 4.81±0.45, respectively. Measured FWHM of lung region in motion corrected PET image using PET fiducial mark and 3D VIBE MRI was measured 4.22±0.09 and 4.59±0.06, respectively. In case of liver region, FWHM was measured 4.47±0.16 and 4.65±0.25 respectively. The improvement of resolution was observed by proper correction method. In this study PET correction was implemented by motion information extracted from various images. These results suggest motion correction would be possible without external device or fiducial mark using MRI motion data. Motion correction using MRI should be considered acquisition method and organ region in accordance with motion characteristics.

[1]  Kyung-Han Lee,et al.  Development of a motion correction system for respiratory-gated PET study , 2004, IEEE Symposium Conference Record Nuclear Science 2004..

[2]  E. Zerhouni,et al.  Human heart: tagging with MR imaging--a method for noninvasive assessment of myocardial motion. , 1988, Radiology.

[3]  T Schaeffter,et al.  Thoracic respiratory motion estimation from MRI using a statistical model and a 2-D image navigator , 2012, Medical Image Anal..

[4]  George T. Y. Chen,et al.  Four-dimensional image-based treatment planning: Target volume segmentation and dose calculation in the presence of respiratory motion. , 2005, International journal of radiation oncology, biology, physics.

[5]  Tobias Schaeffter,et al.  Simultaneous PET–MR acquisition and MR-derived motion fields for correction of non-rigid motion in PET , 2010, Annals of nuclear medicine.

[6]  Xiaoyi Jiang,et al.  Motion Correction in Dual Gated Cardiac PET Using Mass-Preserving Image Registration , 2012, IEEE Transactions on Medical Imaging.

[7]  C. Ling,et al.  Effect of respiratory gating on quantifying PET images of lung cancer. , 2002, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[8]  G. Cheon,et al.  Anesthesia condition for (18)F-FDG imaging of lung metastasis tumors using small animal PET. , 2008, Nuclear medicine and biology.

[9]  G El Fakhri,et al.  Nonrigid PET motion compensation in the lower abdomen using simultaneous tagged-MRI and PET imaging. , 2011, Medical physics.

[10]  Jung Woo Yu,et al.  Region adaptive PET gating using internal motion estimation , 2011, 2011 IEEE Nuclear Science Symposium Conference Record.