Motion robust 4D-MRI sorting based on anatomic feature matching: A digital phantom simulation study

Purpose: Motion artifacts induced by breathing variations are common in 4D-MRI images. This study aims to reduce the motion artifacts by developing a novel, robust 4D-MRI sorting method based on anatomic feature matching and applicable in both cine and sequential acquisition. Method: The proposed me...

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Main Authors: Zi Yang, Lei Ren, Fang-Fang Yin, Xiao Liang, Jing Cai
Format: Article
Language:English
Published: Elsevier 2020-03-01
Series:Radiation Medicine and Protection
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2666555720300034
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author Zi Yang
Lei Ren
Fang-Fang Yin
Xiao Liang
Jing Cai
author_facet Zi Yang
Lei Ren
Fang-Fang Yin
Xiao Liang
Jing Cai
author_sort Zi Yang
collection DOAJ
description Purpose: Motion artifacts induced by breathing variations are common in 4D-MRI images. This study aims to reduce the motion artifacts by developing a novel, robust 4D-MRI sorting method based on anatomic feature matching and applicable in both cine and sequential acquisition. Method: The proposed method uses the diaphragm as the anatomic feature to guide the sorting of 4D-MRI images. Initially, both abdominal 2D sagittal cine MRI images and axial MRI images were acquired. The sagittal cine MRI images were divided into 10 phases as ground truth. Next, the phase of each axial MRI image is determined by matching its diaphragm position in the intersection plane to the ground truth cine MRI. Then, those matched phases axial images were sorted into 10-phase bins which were identical to the ground truth cine images. Finally, 10-phase 4D-MRI were reconstructed from these sorted axial images. The accuracy of reconstructed 4D-MRI data was evaluated by comparing with the ground truth using the 4D eXtended Cardiac Torso (XCAT) digital phantom. The effects of breathing signal, including both regular (cosine function) and irregular (patient data) in both axial cine and sequential scanning modes, on reconstruction accuracy were investigated by calculating total relative error (TRE) of the 4D volumes, Volume-Percent-Difference (VPD) and Center-of-Mass-Shift (COMS) of the estimated tumor volume, compared with the ground truth XCAT images. Results: In both scanning modes, reconstructed 4D-MRI images matched well with ground truth with minimal motion artifacts. The averaged TRE of the 4D volume, VPD and COMS of the EOE phase in both scanning modes are 0.32%/1.20%/±0.05 ​mm for regular breathing, and 1.13%/4.26%/±0.21 ​mm for patient irregular breathing. Conclusion: The preliminary evaluation results illustrated the feasibility of the robust 4D-MRI sorting method based on anatomic feature matching. This method provides improved image quality with reduced motion artifacts for both cine and sequential scanning modes.
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spelling doaj.art-6584f194b7bc4e919cba82c826f9539e2023-08-02T00:54:22ZengElsevierRadiation Medicine and Protection2666-55572020-03-01114147Motion robust 4D-MRI sorting based on anatomic feature matching: A digital phantom simulation studyZi Yang0Lei Ren1Fang-Fang Yin2Xiao Liang3Jing Cai4Medical Physics Graduate Program, Duke University, Durham, NC, USAMedical Physics Graduate Program, Duke University, Durham, NC, USA; Department of Radiation Oncology, Duke University Medical Center, Durham, NC, USA; Corresponding authors. Department of Radiation Oncology, Duke University Medical Center, Durham, NC, USA.Medical Physics Graduate Program, Duke University, Durham, NC, USA; Department of Radiation Oncology, Duke University Medical Center, Durham, NC, USAMedical Physics Graduate Program, Duke University, Durham, NC, USADepartment of Radiation Oncology, Duke University Medical Center, Durham, NC, USA; Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China; Corresponding authors. Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.Purpose: Motion artifacts induced by breathing variations are common in 4D-MRI images. This study aims to reduce the motion artifacts by developing a novel, robust 4D-MRI sorting method based on anatomic feature matching and applicable in both cine and sequential acquisition. Method: The proposed method uses the diaphragm as the anatomic feature to guide the sorting of 4D-MRI images. Initially, both abdominal 2D sagittal cine MRI images and axial MRI images were acquired. The sagittal cine MRI images were divided into 10 phases as ground truth. Next, the phase of each axial MRI image is determined by matching its diaphragm position in the intersection plane to the ground truth cine MRI. Then, those matched phases axial images were sorted into 10-phase bins which were identical to the ground truth cine images. Finally, 10-phase 4D-MRI were reconstructed from these sorted axial images. The accuracy of reconstructed 4D-MRI data was evaluated by comparing with the ground truth using the 4D eXtended Cardiac Torso (XCAT) digital phantom. The effects of breathing signal, including both regular (cosine function) and irregular (patient data) in both axial cine and sequential scanning modes, on reconstruction accuracy were investigated by calculating total relative error (TRE) of the 4D volumes, Volume-Percent-Difference (VPD) and Center-of-Mass-Shift (COMS) of the estimated tumor volume, compared with the ground truth XCAT images. Results: In both scanning modes, reconstructed 4D-MRI images matched well with ground truth with minimal motion artifacts. The averaged TRE of the 4D volume, VPD and COMS of the EOE phase in both scanning modes are 0.32%/1.20%/±0.05 ​mm for regular breathing, and 1.13%/4.26%/±0.21 ​mm for patient irregular breathing. Conclusion: The preliminary evaluation results illustrated the feasibility of the robust 4D-MRI sorting method based on anatomic feature matching. This method provides improved image quality with reduced motion artifacts for both cine and sequential scanning modes.http://www.sciencedirect.com/science/article/pii/S2666555720300034Motion artifacts4D-MRIXCATLiver cancerSimulation
spellingShingle Zi Yang
Lei Ren
Fang-Fang Yin
Xiao Liang
Jing Cai
Motion robust 4D-MRI sorting based on anatomic feature matching: A digital phantom simulation study
Radiation Medicine and Protection
Motion artifacts
4D-MRI
XCAT
Liver cancer
Simulation
title Motion robust 4D-MRI sorting based on anatomic feature matching: A digital phantom simulation study
title_full Motion robust 4D-MRI sorting based on anatomic feature matching: A digital phantom simulation study
title_fullStr Motion robust 4D-MRI sorting based on anatomic feature matching: A digital phantom simulation study
title_full_unstemmed Motion robust 4D-MRI sorting based on anatomic feature matching: A digital phantom simulation study
title_short Motion robust 4D-MRI sorting based on anatomic feature matching: A digital phantom simulation study
title_sort motion robust 4d mri sorting based on anatomic feature matching a digital phantom simulation study
topic Motion artifacts
4D-MRI
XCAT
Liver cancer
Simulation
url http://www.sciencedirect.com/science/article/pii/S2666555720300034
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AT xiaoliang motionrobust4dmrisortingbasedonanatomicfeaturematchingadigitalphantomsimulationstudy
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