Literature DB >> 25841276

Motion correction options in PET/MRI.

Ciprian Catana1.   

Abstract

Subject motion is unavoidable in clinical and research imaging studies. Breathing is the most important source of motion in whole-body PET and MRI studies, affecting not only thoracic organs but also those in the upper and even lower abdomen. The motion related to the pumping action of the heart is obviously relevant in high-resolution cardiac studies. These two sources of motion are periodic and predictable, at least to a first approximation, which means certain techniques can be used to control the motion (eg, by acquiring the data when the organ of interest is relatively at rest). Additionally, nonperiodic and unpredictable motion can also occur during the scan. One obvious limitation of methods relying on external devices (eg, respiratory bellows or the electrocardiogram signal to monitor the respiratory or cardiac cycle, respectively) to trigger or gate the data acquisition is that the complex motion of internal organs cannot be fully characterized. However, detailed information can be obtained using either the PET or MRI data (or both) allowing the more complete characterization of the motion field so that a motion model can be built. Such a model and the information derived from simple external devices can be used to minimize the effects of motion on the collected data. In the ideal case, all the events recorded during the PET scan would be used to generate a motion-free or corrected PET image. The detailed motion field can be used for this purpose by applying it to the PET data before, during, or after the image reconstruction. Integrating all these methods for motion control, characterization, and correction into a workflow that can be used for routine clinical studies is challenging but could potentially be extremely valuable given the improvement in image quality and reduction of motion-related image artifacts.
Copyright © 2015 Elsevier Inc. All rights reserved.

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Year:  2015        PMID: 25841276      PMCID: PMC4487884          DOI: 10.1053/j.semnuclmed.2015.01.001

Source DB:  PubMed          Journal:  Semin Nucl Med        ISSN: 0001-2998            Impact factor:   4.446


  89 in total

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2.  Motion estimation for cardiac emission tomography by optical flow methods.

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Journal:  Phys Med Biol       Date:  2008-05-12       Impact factor: 3.609

3.  Cranio-caudal movements of the liver, pancreas and kidneys in respiration.

Authors:  I Suramo; M Päivänsalo; V Myllylä
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4.  Liver stiffness assessment with tagged MRI of cardiac-induced liver motion in cirrhosis patients.

Authors:  Sohae Chung; Kyoung-Eun Kim; Mi-Suk Park; Sharath Bhagavatula; James Babb; Leon Axel
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5.  Four-dimensional measurement of intrafractional respiratory motion of pancreatic tumors using a 256 multi-slice CT scanner.

Authors:  Shinichiro Mori; Ryusuke Hara; Takeshi Yanagi; Gregory C Sharp; Motoki Kumagai; Hiroshi Asakura; Riwa Kishimoto; Shigeru Yamada; Susumu Kandatsu; Tadashi Kamada
Journal:  Radiother Oncol       Date:  2009-02-09       Impact factor: 6.280

6.  Characterization of pancreatic tumor motion using cine MRI: surrogates for tumor position should be used with caution.

Authors:  Mary Feng; James M Balter; Daniel Normolle; Saroja Adusumilli; Yue Cao; Thomas L Chenevert; Edgar Ben-Josef
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7.  Individually wide range of renal motion evaluated by four-dimensional computed tomography.

Authors:  Hideomi Yamashita; Mami Yamashita; Masahiko Futaguchi; Ryousuke Takenaka; Shino Shibata; Kentaro Yamamoto; Akihiro Nomoto; Akira Sakumi; Satoshi Kida; Yoshihiro Kaneko; Shigeharu Takenaka; Takashi Shiraki; Keiichi Nakagawa
Journal:  Springerplus       Date:  2014-03-07

8.  An analysis of respiratory induced kidney motion on four-dimensional computed tomography and its implications for stereotactic kidney radiotherapy.

Authors:  Shankar Siva; Daniel Pham; Suki Gill; Mathias Bressel; Kim Dang; Thomas Devereux; Tomas Kron; Farshad Foroudi
Journal:  Radiat Oncol       Date:  2013-10-26       Impact factor: 3.481

9.  Motion of the esophagus due to cardiac motion.

Authors:  Jacob Palmer; Jinzhong Yang; Tinsu Pan; Laurence E Court
Journal:  PLoS One       Date:  2014-02-28       Impact factor: 3.240

10.  On transcending the impasse of respiratory motion correction applications in routine clinical imaging - a consideration of a fully automated data driven motion control framework.

Authors:  Adam L Kesner; Paul J Schleyer; Florian Büther; Martin A Walter; Klaus P Schäfers; Phillip J Koo
Journal:  EJNMMI Phys       Date:  2014-06-17
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  28 in total

1.  Novel adversarial semantic structure deep learning for MRI-guided attenuation correction in brain PET/MRI.

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Review 2.  Quantitative Rodent Brain Receptor Imaging.

Authors:  Kristina Herfert; Julia G Mannheim; Laura Kuebler; Sabina Marciano; Mario Amend; Christoph Parl; Hanna Napieczynska; Florian M Maier; Salvador Castaneda Vega; Bernd J Pichler
Journal:  Mol Imaging Biol       Date:  2020-04       Impact factor: 3.488

Review 3.  Cardiac Applications of PET-MR.

Authors:  Peter J Bergquist; Michael S Chung; Anja Jones; Mark A Ahlman; Charles S White; Jean Jeudy
Journal:  Curr Cardiol Rep       Date:  2017-05       Impact factor: 2.931

4.  Cardiac and Respiratory Motion Correction for Simultaneous Cardiac PET/MR.

Authors:  Christoph Kolbitsch; Mark A Ahlman; Cynthia Davies-Venn; Robert Evers; Michael Hansen; Devis Peressutti; Paul Marsden; Peter Kellman; David A Bluemke; Tobias Schaeffter
Journal:  J Nucl Med       Date:  2017-02-09       Impact factor: 10.057

5.  Comparison of the clinical performance of upper abdominal PET/DCE-MRI with and without concurrent respiratory motion correction (MoCo).

Authors:  Onofrio A Catalano; Lale Umutlu; Niccolo Fuin; Matthew Louis Hibert; Michele Scipioni; Stefano Pedemonte; Mark Vangel; Andreea Maria Catana; Ken Herrmann; Felix Nensa; David Groshar; Umar Mahmood; Bruce R Rosen; Ciprian Catana
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-07-11       Impact factor: 9.236

Review 6.  Dynamic whole-body PET imaging: principles, potentials and applications.

Authors:  Arman Rahmim; Martin A Lodge; Nicolas A Karakatsanis; Vladimir Y Panin; Yun Zhou; Alan McMillan; Steve Cho; Habib Zaidi; Michael E Casey; Richard L Wahl
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-09-29       Impact factor: 9.236

Review 7.  From simultaneous to synergistic MR-PET brain imaging: A review of hybrid MR-PET imaging methodologies.

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Review 8.  Advances in PET/MR instrumentation and image reconstruction.

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Review 9.  The Use of Anatomical Information for Molecular Image Reconstruction Algorithms: Attenuation/Scatter Correction, Motion Compensation, and Noise Reduction.

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Journal:  Nucl Med Mol Imaging       Date:  2016-02-11

Review 10.  MR Imaging-Guided Attenuation Correction of PET Data in PET/MR Imaging.

Authors:  David Izquierdo-Garcia; Ciprian Catana
Journal:  PET Clin       Date:  2016-01-26
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