PT - JOURNAL ARTICLE
AU - LU, Xinyu
TI - An Accurate PET Time Calibration Method With Phantom Position Correction
DP - 2016 May 01
TA - Journal of Nuclear Medicine
PG - 1945--1945
VI - 57
IP - supplement 2
4099 - http://jnm.snmjournals.org/content/57/supplement_2/1945.short
4100 - http://jnm.snmjournals.org/content/57/supplement_2/1945.full
SO - J Nucl Med2016 May 01; 57
AB - 1945Objectives TOF PETs are now commercially available. From the actual acquisition of PET detector signals to the final image reconstruction, due to the unique time delay in each channel, a wide coincidence time window is necessary for true coincidence events. In order to achieve the best timing performance, the time offset must be calculated. Furthermore, accurate time alignment is critical for TOF image reconstruction.Methods In this work, we introduce an weighted linear least squares approach which can robustly estimate the time offsets using data from all possible detector pairs, of which errors can be well controlled. A cylinder phantom (uniform or shell) filled with FDG or Ge68 solution located in the FOV. Here, the phantom position can be off center of FOV, which make phantom positioning easily. All possible effective events from the phantom are collected. Using a simple FBP reconstruction we can get an accurate position of the phantom. The phantom position is used as a correction factor in this method. For each LOR, there exists a time difference spectra, calculating the centroid time difference, variance of the spectra and total event number. The reciprocal of variance divided by total event number is used as the weight factor later. For the whole scanner, a weighted overdetermined equation system is formed for time offsets estimation which can be solved using the pseudo-inverse matrix optimally.Results Using this approach, a time alignment accuracy of better than 10ps can be achieved. This method can handle the condition of phantom 200mm off-centered.Conclusions Depending on the system stability, time offsets should be aligned regularly. This method is relatively simple and robust. It does not require extra hardware. Furthermore, this approach provides a meaningful result within minimum computing time.