Literature DB >> 32190569

Volumetric cine magnetic resonance imaging (VC-MRI) using motion modeling, free-form deformation and multi-slice undersampled 2D cine MRI reconstructed with spatio-temporal low-rank decomposition.

Wendy Harris1, Fang-Fang Yin1,2,3, Jing Cai1,2,4, Lei Ren1,2.   

Abstract

BACKGROUND: The purpose of this study is to improve on-board volumetric cine magnetic resonance imaging (VC-MRI) using multi-slice undersampled cine images reconstructed using spatio-temporal k-space data, patient prior 4D-MRI, motion modeling (MM) and free-form deformation (FD) for real-time 3D target verification of liver and lung radiotherapy.
METHODS: A previous method was developed to generate on-board VC-MRI by deforming prior MRI images based on a MM and a single-slice on-board 2D-cine image. The two major improvements over the previous method are: (I) FD was introduced to estimate VC-MRI to correct for inaccuracies in the MM; (II) multi-slice undersampled 2D-cine images reconstructed by a k-t SLR reconstruction method were used for FD-based estimation to maintain the temporal resolution while improving the accuracy of VC-MRI. The method was evaluated using XCAT lung simulation and four liver patients' data.
RESULTS: For XCAT, VC-MRI estimated using ten undersampled sagittal 2D-cine MRIs resulted in volume percent difference/volume dice coefficient/center-of-mass shift of 9.77%±3.71%/0.95±0.02/0.75±0.26 mm among all scenarios based on estimation with MM and FD. Adding FD optimization improved VC-MRI accuracy substantially for scenarios with anatomical changes. For patient data, the mean tumor tracking errors were 0.64±0.51, 0.62±0.47 and 0.24±0.24 mm along the superior-inferior (SI), anterior-posterior (AP) and lateral directions, respectively, across all liver patients.
CONCLUSIONS: It is feasible to improve VC-MRI accuracy while maintaining high temporal resolution using FD and multi-slice undersampled 2D cine images for real-time 3D target verification. 2020 Quantitative Imaging in Medicine and Surgery. All rights reserved.

Entities:  

Keywords:  Volumetric-cine magnetic resonance imaging (volumetric-cine MRI); free-form deformation; k-t SLR reconstruction; motion modeling; target verification

Year:  2020        PMID: 32190569      PMCID: PMC7063294          DOI: 10.21037/qims.2019.12.10

Source DB:  PubMed          Journal:  Quant Imaging Med Surg        ISSN: 2223-4306


  29 in total

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2.  Toward efficient biomechanical-based deformable image registration of lungs for image-guided radiotherapy.

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3.  Predicting real-time 3D deformation field maps (DFM) based on volumetric cine MRI (VC-MRI) and artificial neural networks for on-board 4D target tracking: a feasibility study.

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Journal:  Phys Med Biol       Date:  2019-08-21       Impact factor: 3.609

4.  MRI-guided tumor tracking in lung cancer radiotherapy.

Authors:  Laura I Cerviño; Jiang Du; Steve B Jiang
Journal:  Phys Med Biol       Date:  2011-05-31       Impact factor: 3.609

5.  Accelerated dynamic MRI exploiting sparsity and low-rank structure: k-t SLR.

Authors:  Sajan Goud Lingala; Yue Hu; Edward DiBella; Mathews Jacob
Journal:  IEEE Trans Med Imaging       Date:  2011-01-31       Impact factor: 10.048

6.  The management of respiratory motion in radiation oncology report of AAPM Task Group 76.

Authors:  Paul J Keall; Gig S Mageras; James M Balter; Richard S Emery; Kenneth M Forster; Steve B Jiang; Jeffrey M Kapatoes; Daniel A Low; Martin J Murphy; Brad R Murray; Chester R Ramsey; Marcel B Van Herk; S Sastry Vedam; John W Wong; Ellen Yorke
Journal:  Med Phys       Date:  2006-10       Impact factor: 4.071

7.  Validation of biomechanical deformable image registration in the abdomen, thorax, and pelvis in a commercial radiotherapy treatment planning system.

Authors:  Michael Velec; Joanne L Moseley; Stina Svensson; Björn Hårdemark; David A Jaffray; Kristy K Brock
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8.  A Technique for Generating Volumetric Cine-Magnetic Resonance Imaging.

Authors:  Wendy Harris; Lei Ren; Jing Cai; You Zhang; Zheng Chang; Fang-Fang Yin
Journal:  Int J Radiat Oncol Biol Phys       Date:  2016-02-06       Impact factor: 7.038

9.  4D-MRI analysis of lung tumor motion in patients with hemidiaphragmatic paralysis.

Authors:  Julien Dinkel; Christian Hintze; Ralf Tetzlaff; Peter E Huber; Klaus Herfarth; Juergen Debus; Hans U Kauczor; Christian Thieke
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10.  Investigation of sagittal image acquisition for 4D-MRI with body area as respiratory surrogate.

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Journal:  Med Phys       Date:  2022-02-25       Impact factor: 4.506

2.  Motion modeling from 4D MR images of liver simulating phantom.

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3.  Synthetic 4DCT(MRI) lung phantom generation for 4D radiotherapy and image guidance investigations.

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Journal:  Med Phys       Date:  2022-03-17       Impact factor: 4.506

  3 in total

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