Up to recently, accounting for missing data in PET reconstruction has been used to rescue (remove artifacts and restore quantitation on) studies when a few block detectors were out of specification. Initially developed for data acquired in step-and-shoot (S&S) mode on interleaved bed positions, this concept is extended for data acquired in Continuous Bed Motion (CBM) mode. Total-body imaging could be achieved either using CBM over a FOV covering the whole patient in several passes. When fast dynamic information is required, extending the axial FOV of the scanner is preferred despite its prohibitive cost. In that context, sparse detector configurations (with many missing blocks or even missing rings) could be proposed (investigated) which offer a very long axial FOV at the cost of a decreased sensitivity. It should be noted that missing data correction is possible without time of flight (TOF). Since images reconstructed with TOF have lower statistical variations and improved lesion detectability compared to those from non-TOF PET, we take advantage of the good TOF timing resolution (215 ps) of the Biograph Vision PET scanner to study imaging geometries populated with sparse detector configurations. These configurations were evaluated using data from both phantoms and clinical patient studies acquired in both S&S and CBM modes. Recent improvements in SiPM based hardware and electronics have resulted in improving the TOF timing resolution to 215 picoseconds. In CBM mode, all virtual lines of response (LOR) have some sensitivity, as the missing LOR, not measured due to the sparse imaging geometry, were acquired by other blocks as the bed is moving. Hence, a sparse configuration acquiring in CBM mode was found to provide more accurate results compared to S&S mode. One drawback of using a sparse detector configuration is an increase in the scan time needed to acquire the same number of counts as that of a complete configuration. The closed form equations to calculate the increase in scan time needed to compensate for the lower sensitivity, tracer decay and patient size were derived.
[1]
M. Conti.
Why is TOF PET reconstruction a more robust method in the presence of inconsistent data?
,
2011,
Physics in medicine and biology.
[2]
N J Pelc,et al.
Utilization of Cross‐Plane Rays for Three‐Dimensional Reconstruction by Filtered Back‐Projection
,
1979,
Journal of computer assisted tomography.
[3]
M E Casey,et al.
Continuous bed motion on clinical scanner: design, data correction, and reconstruction.
,
2014,
Physics in medicine and biology.
[4]
D. Townsend,et al.
An Assessment of the Impact of Incorporating Time-of-Flight Information into Clinical PET/CT Imaging
,
2010,
Journal of Nuclear Medicine.
[5]
J. Karp,et al.
Performance of Philips Gemini TF PET/CT scanner with special consideration for its time-of-flight imaging capabilities.
,
2007,
Journal of nuclear medicine : official publication, Society of Nuclear Medicine.