Body Motion Detection and Correction in Cardiac PET: Phantom and Human Studies

Overview

Journal Med Phys

Specialty Biophysics

Date 2019 Sep 12

PMID 31508827

Citations 12

Authors

Tao Sun

Yoann Petibon

Paul K Han

Chao Ma

Sally J W Kim

Nathaniel M Alpert

Georges El Fakhri

Jinsong Ouyang

Affiliations

Soon will be listed here.

Abstract

Purpose: Patient body motion during a cardiac positron emission tomography (PET) scan can severely degrade image quality. We propose and evaluate a novel method to detect, estimate, and correct body motion in cardiac PET.

Methods: Our method consists of three key components: motion detection, motion estimation, and motion-compensated image reconstruction. For motion detection, we first divide PET list-mode data into 1-s bins and compute the center of mass (COM) of the coincidences' distribution in each bin. We then compute the covariance matrix within a 25-s sliding window over the COM signals inside the window. The sum of the eigenvalues of the covariance matrix is used to separate the list-mode data into "static" (i.e., body motion free) and "moving" (i.e. contaminated by body motion) frames. Each moving frame is further divided into a number of evenly spaced sub-frames (referred to as "sub-moving" frames), in which motion is assumed to be negligible. For motion estimation, we first reconstruct the data in each static and sub-moving frame using a rapid back-projection technique. We then select the longest static frame as the reference frame and estimate elastic motion transformations to the reference frame from all other static and sub-moving frames using nonrigid registration. For motion-compensated image reconstruction, we reconstruct all the list-mode data into a single image volume in the reference frame by incorporating the estimated motion transformations in the PET system matrix. We evaluated the performance of our approach in both phantom and human studies.

Results: Visually, the motion-corrected (MC) PET images obtained using the proposed method have better quality and fewer motion artifacts than the images reconstructed without motion correction (NMC). Quantitative analysis indicates that MC yields higher myocardium to blood pool concentration ratios. MC also yields sharper myocardium than NMC.

Conclusions: The proposed body motion correction method improves image quality of cardiac PET.

Citing Articles

Effects of List-Mode-Based Intraframe Motion Correction in Dynamic Brain PET Imaging.

Tiss A, Chemli Y, Guehl N, Marin T, Johnson K, El Fakhri G IEEE Trans Radiat Plasma Med Sci. 2024; 8(8):950-958.

PMID: 39507127 PMC: 11540417. DOI: 10.1109/trpms.2024.3432322.

The value of net influx constant based on FDG PET/CT dynamic imaging in the differential diagnosis of metastatic from non-metastatic lymph nodes in lung cancer.

Wumener X, Zhang Y, Zang Z, Ye X, Zhao J, Zhao J Ann Nucl Med. 2024; 38(11):904-912.

PMID: 39078558 PMC: 11489159. DOI: 10.1007/s12149-024-01964-y.

The value of dynamic FDG PET/CT in the differential diagnosis of lung cancer and predicting EGFR mutations.

Wumener X, Zhang Y, Zang Z, Du F, Ye X, Zhang M BMC Pulm Med. 2024; 24(1):227.

PMID: 38730287 PMC: 11088023. DOI: 10.1186/s12890-024-02997-9.

Improvement of motion artifacts using dynamic whole-body F-FDG PET/CT imaging.

Kaji T, Osanai K, Takahashi A, Kinoshita A, Satoh D, Nakata T Jpn J Radiol. 2023; 42(4):374-381.

PMID: 38093138 PMC: 10980605. DOI: 10.1007/s11604-023-01513-z.

Supplemental Transmission Aided Attenuation Correction for Quantitative Cardiac PET.

Park M, Zaha V, Badawi R, Bowen S IEEE Trans Med Imaging. 2023; 43(3):1125-1137.

PMID: 37948143 PMC: 10986771. DOI: 10.1109/TMI.2023.3330668.

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