Literature DB >> 30710381

Patient body motion correction for dynamic cardiac PET-CT by attenuation-emission alignment according to projection consistency conditions.

Chad R R N Hunter1,2, Ran Klein1,3, Adam M Alessio4, Robert A deKemp1,2.   

Abstract

INTRODUCTION: Patient body motion is known to cause large deviations in the determination of myocardial blood flow (MBF) with errors exceeding 300%. Accurate correction for patient whole-body motion is still a largely unsolved problem in cardiac positron emission tomography (PET) imaging.
OBJECTIVE: This study evaluated the efficacy of using Natterer's formulation of the Helgason-Ludwig consistency conditions on the two-dimensional Radon transform to align computed tomography to PET projection data in multiple time frames of a dynamic sequence for the purpose of frame-by-frame correction of rigid whole-body motion.
METHODS: The correction algorithm was evaluated with digital NCAT phantoms using realistic noise added by the analytical simulator. Count rates used in the simulation were derived from clinical patient data. In addition, a proof of concept test using measured data with a cardiac torso phantom was conducted.
RESULTS: Motion correction resulted in significant improvement in the accuracy of MBF estimates, especially for high count-rate acquisitions. Maximum errors for 2 cm of motion dropped from 325% to 25% and from 250% to 25% using global and regional partial-volume correction, respectively. Median MBF errors dropped from 33% to 4.5% and 27% to 3.8%, respectively. Importantly, the correction algorithm performed equally well to compensate for body motion in both early and late time frames.
CONCLUSION: Cardiac PET-CT data used for attenuation correction (CTAC) alignment using projection consistency conditions was effective for reducing errors in MBF measurements due to simulated patient motion, and can be integrated into the image reconstruction workflow.
© 2019 American Association of Physicists in Medicine.

Entities:  

Keywords:  dynamic positron emission tomography; motion correction; patient body motion

Mesh:

Year:  2019        PMID: 30710381     DOI: 10.1002/mp.13419

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  2 in total

1.  Motion correction and its impact on quantification in dynamic total-body 18F-fluorodeoxyglucose PET.

Authors:  Tao Sun; Yaping Wu; Wei Wei; Fangfang Fu; Nan Meng; Hongzhao Chen; Xiaochen Li; Yan Bai; Zhenguo Wang; Jie Ding; Debin Hu; Chaojie Chen; Zhanli Hu; Dong Liang; Xin Liu; Hairong Zheng; Yongfeng Yang; Yun Zhou; Meiyun Wang
Journal:  EJNMMI Phys       Date:  2022-09-14

2.  Automatic Inter-Frame Patient Motion Correction for Dynamic Cardiac PET Using Deep Learning.

Authors:  Luyao Shi; Yihuan Lu; Nicha Dvornek; Christopher A Weyman; Edward J Miller; Albert J Sinusas; Chi Liu
Journal:  IEEE Trans Med Imaging       Date:  2021-11-30       Impact factor: 10.048

  2 in total

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