Spatial-Temporal PET Reconstruction with CT-Derived Organ Deformation
Tianfang Li and Lei Xing
Department of Radiation Ocology
Four-dimensional (4D) PET (acquired with gated, dynamic or list mode)
has been used for tumor delineation and evaluation of response to radiotherapy
for a various cancers. However, the quantitative accuracy of 4D PET is limited
due to its poor statistics, since the total coincidence counts in the conventional
3D acquisition are now divided into many phase bins and each of them is treated
as an independent entity in 4D imaging. In this work, we develop a
mathematically rigorous approach to maximally enhance the signal-to-noise ratio
of 4D PET by simultaneously considering the coincidences acquired at all time
points when reconstructing the phase-resolved images. By deformable
registration of 4D-CT images, a patient-specific
motion model was derived and incorporated into our ¡°spatial-temporal PET
reconstruction¡± algorithm based on the
maximum likelihood principle. Via a novel concept of ¡°virtual curved
line-of-response¡±, we show that the PET ¡°4D likelihood¡± can be maximized with a
modified expectation-maximization algorithm. The approach was quantitatively
evaluated with numerical and physical phantom experiments. Five clinical
studies of pancreatic, lung and liver cancer patients were then carried out.
From these studies, it is found that the quantitative accuracy can be reached
usually within 40 iterations and the SNRs can be
increased more than 80% over the regular 4D PET and 35% over 3D PET. The new
spatial-temporal reconstruction formalism allow us to fully take advantage of
the information acquired with combined PET/CT scanner and obtain a substantially
improved 4D PET imaging.