Respiratory Motion Compensation for PET/CT with Motion Information Derived from Matched Attenuation-Corrected Gated PET Data

Abstract

Respiratory motion degrades the detection and quantification capabilities of PET/CT imaging. Moreover, mismatch between a fast helical CT image and a time-averaged PET image due to respiratory motion results in additional attenuation correction artifacts and inaccurate localization. Current motion compensation approaches typically have 3 limitations: the mismatch among respiration-gated PET images and the CT attenuation correction (CTAC) map can introduce artifacts in the gated PET reconstructions that can subsequently affect the accuracy of the motion estimation; sinogram-based correction approaches do not correct for intragate motion due to intracycle and intercycle breathing variations; and the mismatch between the PET motion compensation reference gate and the CT image can cause an additional CT-mismatch artifact. In this study, we established a motion correction framework to address these limitations. In the proposed framework, the combined emission-transmission reconstruction algorithm was used for phase-matched gated PET reconstructions to facilitate the motion model building. An event-by-event nonrigid respiratory motion compensation method with correlations between internal organ motion and external respiratory signals was used to correct both intracycle and intercycle breathing variations. The PET reference gate was automatically determined by a newly proposed CT-matching algorithm. We applied the new framework to 13 human datasets with 3 different radiotracers and 323 lesions and compared its performance with CTAC and non-attenuation correction (NAC) approaches. Validation using 4-dimensional CT was performed for one lung cancer dataset. For the 10 F-FDG studies, the proposed method outperformed ( < 0.006) both the CTAC and the NAC methods in terms of region-of-interest-based SUV, SUV, and SUV ratio improvements over no motion correction (SUV: 19.9% vs. 14.0% vs. 13.2%; SUV: 15.5% vs. 10.8% vs. 10.6%; SUV ratio: 24.1% vs. 17.6% vs. 16.2%, for the proposed, CTAC, and NAC methods, respectively). The proposed method increased SUV ratios over no motion correction for 94.4% of lesions, compared with 84.8% and 86.4% using the CTAC and NAC methods, respectively. For the 2 F-fluoropropyl-(+)-dihydrotetrabenazine studies, the proposed method reduced the CT-mismatch artifacts in the lower lung where the CTAC approach failed and maintained the quantification accuracy of bone marrow where the NAC approach failed. For theF-FMISO study, the proposed method outperformed both the CTAC and the NAC methods in terms of motion estimation accuracy at 2 lung lesion locations. The proposed PET/CT respiratory event-by-event motion-correction framework with motion information derived from matched attenuation-corrected PET data provides image quality superior to that of the CTAC and NAC methods for multiple tracers.

Improved Alignment of PET and CT Images in Whole-Body PET/CT in Cases of Respiratory Motion During CT

“…promise but has not been tested clinically. (17) In this work, 18 of 46 patients were excluded from the study because of technical errors in acquisition of the respiratory waveforms. Such errors would disappear with the adoption of data driven gating.…”

Improved PET/CT Respiratory Motion Compensation by Incorporating Changes in Lung Density

“…The activity and attenuation maps are, respectively, denoted as λ ∈ C + and μ ∈ C + , where C + = C 0 (R 3 , R + ) is the set of non-negative continuous functions defined on R 3 .…”

“…Commonly used MCIR techniques rely on the previous determination of the deformation fields from gated images, which are then incorporated into the reconstruction [2]. A standard option relies on registering gated PET images reconstructed without attenuation correction [1] or, more recently, with attenuation correction [3] and accurate time-of-flight (TOF) information [4], leading to a reduction in localized image artifacts. A second option exploits CINE-CT images to obtain CT-based deformation fields, which should be more robust because of better contrast and higher resolution.…”

Impact of respiratory motion correction on lesion visibility and quantification in thoracic PET/MR imaging

“…However, extensive knowledge of the body deformation fields in three dimensions (3D) during the entire respiratory cycle needs to be derived from the obtained data. Studies using PET data alone were conducted already [21], but PET is often not sufficient to provide the necessary amount of landmarks for a robust determination of such deformation matrices [22,23]. This particularly applies to radiotracers with comparably low uptake characteristics.…”