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    <title>Kyrre Eeg Emblem | Theragnostic Imaging</title>
    <link>https://www.theragnostics.no/en/author/kyrre-eeg-emblem/</link>
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      <title>Kyrre Eeg Emblem</title>
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      <title>Optimization of Q.Clear reconstruction for dynamic 18F PET imaging</title>
      <link>https://www.theragnostics.no/en/publications/lysvik-2023-optimization/</link>
      <pubDate>Fri, 20 Oct 2023 00:00:00 +0000</pubDate>
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      <description>&lt;hr&gt;
&lt;p&gt;Q.Clear, a Bayesian penalized likelihood reconstruction algorithm, has shown high potential in improving quantitation accuracy in PET systems. The Q.Clear algorithm controls noise during the iterative reconstruction through a β penalization factor. This study aimed to determine the optimal β-factor for accurate quantitation of dynamic PET scans. A Flangeless Esser PET Phantom with eight hollow spheres (4-25 mm) was scanned on a GE Discovery MI PET/CT system. Data were reconstructed into five sets of variable acquisition times using Q.Clear with 18 different β-factors ranging from 100 to 3500. The recovery coefficient (RC), coefficient of variation (CV&lt;sub&gt;RC&lt;/sub&gt;) and root-mean-square error (RMSE&lt;sub&gt;RC&lt;/sub&gt;) were evaluated for the phantom data. Two male patients with recurrent glioblastoma were scanned on the same scanner using &lt;sup&gt;18&lt;/sup&gt;F-PSMA-1007. Using an irreversible two-tissue compartment model, the area under curve (AUC) and the net influx rate K&lt;sub&gt;i&lt;/sub&gt; were calculated to assess the impact of different β-factors on the pharmacokinetic analysis of clinical PET brain data. In general, RC and CV&lt;sub&gt;RC&lt;/sub&gt; decreased with increasing β-factor in the phantom data. For small spheres (&amp;lt; 10 mm), and in particular for short acquisition times, low β-factors resulted in high variability and an overestimation of measured activity. Increasing the β-factor improves the variability, however at a cost of underestimating the measured activity. For the clinical data, AUC decreased and K&lt;sub&gt;i&lt;/sub&gt; increased with increased β-factor; a change in β-factor from 300 to 1000 resulted in a 25.5% increase in the K&lt;sub&gt;i&lt;/sub&gt;. In a complex dynamic dataset with variable acquisition times, the optimal β-factor provides a balance between accuracy and precision. Based on our results, we suggest a β-factor of 300-500 for quantitation of small structures with dynamic PET imaging, while large structures may benefit from higher β-factors. Clinicaltrials.gov, NCT03951142. Registered 5 October 2019, &lt;a href=&#34;https://clinicaltrials.gov/ct2/show/NCT03951142&#34; target=&#34;_blank&#34; rel=&#34;noopener&#34;&gt;https://clinicaltrials.gov/ct2/show/NCT03951142&lt;/a&gt; . EudraCT no 2018-003229-27. Registered 26 February 2019, &lt;a href=&#34;https://www.clinicaltrialsregister.eu/ctr-search/trial/2018-003229-27/NO&#34; target=&#34;_blank&#34; rel=&#34;noopener&#34;&gt;https://www.clinicaltrialsregister.eu/ctr-search/trial/2018-003229-27/NO&lt;/a&gt; .&lt;/p&gt;
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