<?xml version="1.0"?>
<Articles JournalTitle="Frontiers in Biomedical Technologies">
  <Article>
    <Journal>
      <PublisherName>Tehran University of Medical Sciences</PublisherName>
      <JournalTitle>Frontiers in Biomedical Technologies</JournalTitle>
      <Issn>2345-5837</Issn>
      <Volume>2</Volume>
      <Issue>3</Issue>
      <PubDate PubStatus="epublish">
        <Year>2015</Year>
        <Month>09</Month>
        <Day>30</Day>
      </PubDate>
    </Journal>
    <title locale="en_US">The Impact of Point Spread Function Modeling on Scan Duration in PET Imaging</title>
    <FirstPage>137</FirstPage>
    <LastPage>145</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName>Sahar</FirstName>
        <LastName>Ahangari</LastName>
        <affiliation locale="en_US">1- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran&#xD;
2- Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran.</affiliation>
      </Author>
      <Author>
        <FirstName>Pardis</FirstName>
        <LastName>Ghafarian</LastName>
        <affiliation locale="en_US">Chronic Respiratory Diseases Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD),Shahid Beheshti University of Medical Sciences, Tehran, Iran4- PET/CT and Cyclotron Center, Masih Daneshvari Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.</affiliation>
      </Author>
      <Author>
        <FirstName>Mahnaz</FirstName>
        <LastName>Shekari</LastName>
        <affiliation locale="en_US">1- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran&#xD;
2- Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran.</affiliation>
      </Author>
      <Author>
        <FirstName>Hossein</FirstName>
        <LastName>Ghadiri</LastName>
        <affiliation locale="en_US">Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran2- Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran.</affiliation>
      </Author>
      <Author>
        <FirstName>Mehrdad</FirstName>
        <LastName>Bakhshayeshkaram</LastName>
        <affiliation locale="en_US">Chronic Respiratory Diseases Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD),Shahid Beheshti University of Medical Sciences, Tehran, Iran4- PET/CT and Cyclotron Center, Masih Daneshvari Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.</affiliation>
      </Author>
      <Author>
        <FirstName>Mohammad Reza</FirstName>
        <LastName>Ay</LastName>
        <affiliation locale="en_US">Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran2- Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran.</affiliation>
      </Author>
    </AuthorList>
    <History>
      <PubDate PubStatus="received">
        <Year>2015</Year>
        <Month>12</Month>
        <Day>18</Day>
      </PubDate>
      <PubDate PubStatus="accepted">
        <Year>2015</Year>
        <Month>12</Month>
        <Day>18</Day>
      </PubDate>
    </History>
    <abstract locale="en_US">Purpose- In this study, we investigated the impact of PSF reconstruction&#xA0;
acquisition time would compromise the accuracy of quantitative measures&#xA0;using PSF algorithm.
Methods- Both phantom and patient images were evaluated. A complete set&#xA0;of experiments were performed using an image quality phantom containing 6&#xA0;inserts with 4:1 lesion to background ratio. Whole-body FDG PET/CT scan of&#xA0;17 patients with different primary cancers were used in this study. All hantom
images reconstructed with 3 iterations, 24 subsets for 180, 150, 120, 90, and 60 s&#xA0;acquisition time per bed position. Post-smoothing filters with FWHM of 5 and&#xA0;4 mm applied to HD and HD+PSF images respectively. Clinical PET images&#xA0;reconstructed with 3 iterations and 18 subsets. Quantitative analysis performed&#xA0;by CV%, SNR, RC, and SUVmax.
Results- By incorporating PSF algorithm, CV decreased 11.1% and 17.01% 0.92%&#xA0;for both phantom and clinical images. In addition, better edge detection achieved&#xA0;specially for smaller focal points. It was shown by reconstructing images with PSF&#xA0;algorithm, acquisition time can be reduced 33.3% with no significant changes of&#xA0;image quality and quantitative accuracy (P-value&lt;0.05).
Conclusion- It can be concluded that using PSF algorithm improves the image&#xA0;quality, lesion detection, and quantitative accuracy. Besides, by incorporating this&#xA0;algorithm, the acquisition time can be reduced with no loss of image quality and&#xA0;quantitative accuracy where it is possible to have higher patient throughout with&#xA0;the same image quality.</abstract>
    <web_url>https://fbt.tums.ac.ir/index.php/fbt/article/view/62</web_url>
    <pdf_url>https://fbt.tums.ac.ir/index.php/fbt/article/download/62/53</pdf_url>
  </Article>
</Articles>
