Fully 4D list-mode reconstruction applied to respiratory-gated PET scans

Abstract

(18)F-fluoro-deoxy-glucose ((18)F-FDG) positron emission tomography (PET) is one of the most sensitive and specific imaging modalities for the diagnosis of non-small cell lung cancer. A drawback of PET is that it requires several minutes of acquisition per bed position, which results in images being affected by respiratory blur. Respiratory gating techniques have been developed to deal with respiratory motion in the PET images. However, these techniques considerably increase the level of noise in the reconstructed images unless the acquisition time is increased. The aim of this paper is to evaluate a four-dimensional (4D) image reconstruction algorithm that combines the acquired events in all the gates whilst preserving the motion deblurring. This algorithm was compared to classic ordered subset expectation maximization (OSEM) reconstruction of gated and non-gated images, and to temporal filtering of gated images reconstructed with OSEM. Two datasets were used for comparing the different reconstruction approaches: one involving the NEMA IEC/2001 body phantom in motion, the other obtained using Monte-Carlo simulations of the NCAT breathing phantom. Results show that 4D reconstruction reaches a similar performance in terms of the signal-to-noise ratio (SNR) as non-gated reconstruction whilst preserving the motion deblurring. In particular, 4D reconstruction improves the SNR compared to respiratory-gated images reconstructed with the OSEM algorithm. Temporal filtering of the OSEM-reconstructed images helps improve the SNR, but does not achieve the same performance as 4D reconstruction. 4D reconstruction of respiratory-gated images thus appears as a promising tool to reach the same performance in terms of the SNR as non-gated acquisitions while reducing the motion blur, without increasing the acquisition time.

Comparative Assessment of Methods for Estimating Tumor Volume and Standardized Uptake Value in 18F-FDG PET

“…However, our simulations remained too simple in at least 2 regards: neither respiratory motion nor heterogeneity in tumor uptake was modeled. Our results might still be representative of the performance to be expected for images compensated for respiratory motion, such as respiratorygated images with appropriate signal-to-noise ratios (33). Respiratory motion compensation (e.g., based on gated PET/CT) before tumor volume or SUV estimates is certainly more appropriate than optimizing tumor segmentation methods for data corrupted by motion, given the large variability of the motion blur in patients, as a function of the respiratory amplitude or tumor location, for instance.…”

Deep-inspiration breath-hold PET/CT versus free breathing PET/CT and respiratory gating PET for reference: evaluation in 95 patients with lung cancer

“…Many protocols have been used in previous methodological studies of RG PET [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. But, the specifications of the PET/CT system at our institution do not correspond to the four-dimensional CT protocol.…”

Interpolated Average CT for Attenuation Correction in PET—A Simulation Study

“…Lamare et al [15] integrated elastic motion correction into the system matrix in the PET reconstruction process. Grotus et al [16] introduced the 4-D joint-estimation algorithm to form a new 4-D OS-EM reconstruction method for gated PET images.…”