Literature DB >> 23231288

The effect of breathing irregularities on quantitative accuracy of respiratory gated PET∕CT.

Boon-Keng Teo1, Babak Saboury, Reshma Munbodh, Joshua Scheuermann, Drew A Torigian, Habib Zaidi, Abass Alavi.   

Abstract

PURPOSE: 4D positron emission tomography and computed tomography (PET∕CT) can be used to reduce motion artifacts by correlating the raw PET data with the respiratory cycle. The accuracy of each PET phase is dependent on the reproducibility and consistency of the breathing cycle during acquisition. The objective of this study is to evaluate the impact of breathing amplitude and phase irregularities on the quantitative accuracy of 4D PET standardized uptake value (SUV) measurements. In addition, the magnitude of quantitative errors due to respiratory motion and partial volume error are compared.
METHODS: Phantom studies were performed using spheres filled with (18)F ranging from 9 to 47 mm in diameter with background activity. Motion was simulated using patient breathing data. The authors compared the accuracy of SUVs derived from gated PET (4 bins and 8 bins, phase-based) for ideal, average, and highly irregular breathing patterns.
RESULTS: Under ideal conditions, gated PET produced SUVs that were within (-5.4 ± 5.3)% of the static phantom measurements averaged across all sphere sizes. With breathing irregularities, the quantitative accuracy of gated PET decreased. Gated PET SUVs (best of 4 bins) were (-9.6 ± 13.0)% of the actual value for an average breather and decreased to (-17.1 ± 10.8)% for a highly irregular breather. Without gating, the differences in the SUV from actual value were (-28.5 ± 18.2)%, (-25.9 ± 14.4)%, and (-27.9 ± 18.2)% for the ideal, average, and highly irregular breather, respectively.
CONCLUSIONS: Breathing irregularities reduce the quantitative accuracy of gated PET∕CT. Current gated PET techniques may underestimate the actual lesion SUV due to phase assignment errors. Evaluation of respiratory trace is necessary to assess accuracy of data binning and its effect on 4D PET SUVs.

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Year:  2012        PMID: 23231288     DOI: 10.1118/1.4766876

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


  7 in total

1.  Correction for Partial Volume Effect Is a Must, Not a Luxury, to Fully Exploit the Potential of Quantitative PET Imaging in Clinical Oncology.

Authors:  Abass Alavi; Thomas J Werner; Poul Flemming Høilund-Carlsen; Habib Zaidi
Journal:  Mol Imaging Biol       Date:  2018-02       Impact factor: 3.488

2.  Utility of respiratory-gated small-animal PET/CT in the chronologic evaluation of an orthotopic lung cancer transplantation mouse model.

Authors:  Tamaki Otani; Hideki Otsuka; Kazuya Kondo; Hiromitsu Takizawa; Motoi Nagata; Mina Kishida; Hirokazu Miyoshi
Journal:  Radiol Phys Technol       Date:  2015-04-29

3.  Application of partial volume effect correction and 4D PET in the quantification of FDG avid lung lesions.

Authors:  Ali Salavati; Samuel Borofsky; Teo K Boon-Keng; Sina Houshmand; Benjapa Khiewvan; Babak Saboury; Ion Codreanu; Drew A Torigian; Habib Zaidi; Abass Alavi
Journal:  Mol Imaging Biol       Date:  2015-02       Impact factor: 3.488

Review 4.  Management of respiratory motion in PET/computed tomography: the state of the art.

Authors:  Audrey Pépin; Joël Daouk; Pascal Bailly; Sébastien Hapdey; Marc-Etienne Meyer
Journal:  Nucl Med Commun       Date:  2014-02       Impact factor: 1.690

5.  Variability of Image Features Computed from Conventional and Respiratory-Gated PET/CT Images of Lung Cancer.

Authors:  Jasmine A Oliver; Mikalai Budzevich; Geoffrey G Zhang; Thomas J Dilling; Kujtim Latifi; Eduardo G Moros
Journal:  Transl Oncol       Date:  2015-12       Impact factor: 4.243

6.  Visual and Quantitative Analysis Methods of Respiratory Patterns for Respiratory Gated PET/CT.

Authors:  Hye Joo Son; Young Jin Jeong; Hyun Jin Yoon; Jong-Hwan Park; Do-Young Kang
Journal:  Biomed Res Int       Date:  2016-10-31       Impact factor: 3.411

7.  A Computational Framework for Data Fusion in MEMS-Based Cardiac and Respiratory Gating.

Authors:  Mojtaba Jafari Tadi; Eero Lehtonen; Jarmo Teuho; Juho Koskinen; Jussi Schultz; Reetta Siekkinen; Tero Koivisto; Mikko Pänkäälä; Mika Teräs; Riku Klén
Journal:  Sensors (Basel)       Date:  2019-09-24       Impact factor: 3.576

  7 in total

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