Molecular Imaging and Biology

, Volume 18, Issue 1, pp 109–116 | Cite as

Automatic Cardiac Self-Gating of Small-Animal PET Data

  • Joaquin L. HerraizEmail author
  • Elena Herranz
  • Jacobo Cal-González
  • Juan J. Vaquero
  • Manuel Desco
  • Lorena Cussó
  • Jose M. Udias
Research Article



The cardiac gating signal (CGS) in positron emission tomography (PET) studies is usually obtained from an electrocardiography (ECG) monitor. In this work, we propose a method to obtain the CGS in small-animal PET using the acquired list-mode data without using any hardware or end-user input.


The CGS was obtained from the number of coincidences over time acquired in the lines-of-response connected with the cardiac region. This region is identified in the image as its value changes with frequencies in the range of 3 to 12 Hz. The procedure was tested in a study with 29 Wistar rats and 6 mice injected with 2-deoxy-2-[18F]fluoro-d-glucose, which underwent a 45-min single-bed list-mode PET scan of the heart syncronized with an ECG. The estimated signals and the reconstructed images using eight-gated frames were compared with the ones obtained using the ECG signal from the monitor.


The differences of the PET-based CGS with respect to the ECG relative to the duration of the heartbeats were 5.6 % in rats and 11.0 % in mice. The reconstructed gated images obtained from the proposed method do not differ qualitatively with respect to the ones obtained with the ECG. The quantitative analysis of both set of images were performed measuring the volume of the left ventricle (LV) of the rats in the end-of-systole and end-of-diastole phase. The differences found in these parameters between both methods were below 12.1 % in the ESV and 9.3 % in the EDV with a 95 % confidence interval, which are comparable to the accuracy (7 %) of the method used for segmenting the LV.


The proposed method is able to provide a valid and accurate CGS in small-animal PET list-mode data.

Key words

List-mode PET Small animal Cardiac gating Self-gating 



This work was supported in part by Consejería de Educación, Juventud y Deporte de la Comunidad de Madrid (Spain) through the Madrid-MIT M+Visión Consortium, Comunidad de Madrid (S2013/MIT-3024 TOPUS-CM), UCM (Grupos UCM, 910059), CPAN (Consolider-Ingenio 2010, CSPD-2007-00042), RIC-RETIC network, Spanish MINECO (RD12/0042/0057), Ministerio de Ciencia e Innovación, Spanish Government (ENTEPRASE grant, PSE-300000-2009-5 and TEC2007-64731/TCM), and European Regional funds.

Conflict of Interest

All authors declare that they have no competing interest.


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Copyright information

© World Molecular Imaging Society 2015

Authors and Affiliations

  • Joaquin L. Herraiz
    • 1
    • 2
    Email author
  • Elena Herranz
    • 3
    • 4
  • Jacobo Cal-González
    • 5
  • Juan J. Vaquero
    • 6
    • 7
  • Manuel Desco
    • 6
    • 7
    • 8
  • Lorena Cussó
    • 6
    • 7
    • 8
  • Jose M. Udias
    • 2
  1. 1.Madrid-MIT M+Vision ConsortiumMassachusetts Institute of TechnologyCambridgeUSA
  2. 2.Grupo de Física NuclearUniversidad Complutense de MadridMadridSpain
  3. 3.A.A.Martinos Center for Biomedical ImagingMassachusetts General HospitalCharlestownUSA
  4. 4.Harvard Medical SchoolBostonUSA
  5. 5.Center for Medical Physics and Biomedical EngineeringMedical University of ViennaViennaAustria
  6. 6.Departamento de Ingenieria Biomedica e Ingeniería AeroespacialUniversidad Carlos III de MadridLeganésSpain
  7. 7.Instituto de Investigación Sanitaria Gregorio MarañónMadridSpain
  8. 8.Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM)MadridSpain

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