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title: Analysis of [C-11]PBR28
author: Vesa Oikonen, Jouni Tuisku
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updated_at: 2021-04-27
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created_at: 2015-08-03
tags:
  - Inflammation
  - TSPO
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  - Glial cells
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---


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<h1>Quantification of [<sup>11</sup>C]PBR28 PET studies</h1>
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<p><a href="./pic/11C-PBR28.svg"><img src="./pic/11C-PBR28.svg" alt="11C-PBR28" 
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  style="padding:10px 0px 0px 10px; width:150px; float:right;" /></a>
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</p>

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<p>PBR28 is a selective second-generation ligand with high affinity for the 
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<a href="./target_tspo.html">translocator protein (TSPO)</a>, formerly known as peripheral 
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benzodiazepine receptor (PBR), a marker of <a href="./mitochondria.html#TSPO">mitochondria</a> and 
<a href="./target_inflammation.html">inflammation</a>.
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Increased distribution volume of [<sup>11</sup>C]PBR28 has been observed in 
<a href="./organ_brain.html">the brain</a> of baboons and humans after injection of <em>E. Coli</em> 
lipopolysaccharide 
(<a href="https://doi.org/10.1016/j.neuroimage.2012.06.055">Hannestad et al., 2012</a>; 
<a href="https://doi.org/10.1073/pnas.1511003112">Sandiego et al, 2015</a>; 
<a href="https://doi.org/10.1016/j.nucmedbio.2014.11.003">Yoder et al, 2015</a>). 
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The cerebral artery occlusion model of neuroinflammation and <a href="./dis_stroke.html">stroke</a> 
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in rats has shown a localized increase in [<sup>11</sup>C]PBR28 <a href="./model_suv.html">SUV</a> 
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(<a href="https://doi.org/10.1016/j.neulet.2006.09.093">Imaizumi et al, 2007</a>; 
<a href="https://doi.org/10.1007/s00429-014-0970-y">T&oacute;th et al, 2016</a>), 
and that increase could be reversed by injection of PK11195 
(<a href="https://doi.org/10.1016/j.neulet.2006.09.093">Imaizumi et al, 2007</a>).
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Also herpes simplex encephalitis model in rats resulted into increased [<sup>11</sup>C]PBR28 uptake 
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(<a href="https://doi.org/10.2967/jnumed.115.165019">Parente et al, 2016</a>). 
<a href="./dis_ad.html">Alzheimer's disease</a> model in mice has shown increased 
[<sup>11</sup>C]PBR28 uptake (<a href="https://doi.org/10.1002/glia.22978">Mirzaei et al, 2016</a>). 
<a href="https://doi.org/10.1016/j.nucmedbio.2013.06.008">Shao et al (2013)</a> demonstrated 
increased [<sup>11</sup>C]PBR28 SUV in rat models of acute inflammation (induced with carrageenan) 
and adjuvant arthritis model. 
[<sup>11</sup>C]PBR28 SUV is increased in the synovium of <a href="./dis_arthritis.html">rheumatoid
arthritis</a> patients
(<a href="https://doi.org/10.2967/jnumed.117.202200">Narayan et al., 2018</a>).
[<sup>11</sup>C]PBR28 SUV increased in the aged rats with increasing neuroinflammation 
(<a href="https://doi.org/10.1038/jcbfm.2015.54">Walker et al, 2015</a>).</p>
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<p>In humans, genetic polymorphism (<a href="./target_tspo.html#rs6971">rs6971</a>) affects 
the binding of [<sup>11</sup>C]PBR28 and other TSPO ligands, leading to three TSPO binding profiles: 
high-affinity binders (HAB), low-affinity binders (LAB) with 50-fold reduction in affinity, and 
mixed-affinity binders (MAB) which express both TSPO types in equal proportion 
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(Owen et al, <a href="https://doi.org/10.2967/jnumed.110.079459">2011</a> and 
<a href="https://doi.org/10.1038/jcbfm.2011.147">2012</a>; 
Kreisl et al., <a href="https://doi.org/10.1016/j.neuroimage.2009.11.056">2010</a> and 
<a href="https://doi.org/10.1038/jcbfm.2012.131">2013a</a>; 
<a href="https://doi.org/10.2967/jnumed.112.118885">Yoder et al, 2013</a>). 
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[<sup>11</sup>C]PBR28 uptake in LAB group is too low to be reliably quantified with PET; therefore 
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genotyping must be done prior to PET to omit the LAB subjects.
The rs6971 polymorphism affects cholesterol binding to TSPO, and in MAB group [<sup>11</sup>C]PBR28 
uptake has been shown to correlate negatively with plasma cholesterol level
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(<a href="https://doi.org/10.1038/s41386-018-0085-x">Kim et al., 2018</a>).</p>
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<p>Increased uptake of [<sup>11</sup>C]PBR28 has been seen in <a href="./dis_ms.html">MS patients</a>
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(<a href="https://doi.org/10.1007/s11481-010-9243-6">Oh et al, 2011</a>; 
<a href="https://doi.org/10.1007/s00259-015-3043-4">Park et al, 2015</a>), in ALS 
(<a href="https://doi.org/10.1016/j.nicl.2015.01.009">Z&uuml;rcher et al, 2015</a>), and in 
HIV-positive humans (<a href="https://doi.org/10.1212/WNL.0000000000002485">Vera et al, 2016</a>). 
[<sup>11</sup>C]PBR28 binding correlates with severity of <a href="./dis_ad.html">Alzheimer's 
disease</a> (<a href="https://doi.org/10.1093/brain/awt145">Kreisl et al, 2013b</a>).
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Myeloperoxidase inhibition in patients with <a href="./dis_pd.html">Parkinson's disease</a> 
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decreased the binding of [<sup>11</sup>C]PBR28 
(<a href="https://doi.org/10.1093/brain/awv184">Jucaite et al., 2015</a>).
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TSPO blocking study in rhesus monkeys suggests that non-displaceable uptake is very small, only 
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about 5% of the total distribution volume 
(<a href="https://doi.org/10.1016/j.neuroimage.2007.09.063">Imaizumi et al., 2008</a>). 
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In human TSPO blocking study V<sub>ND</sub> was estimated to be about 2, while V<sub>T</sub> was 
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about 3 and 4 for MAB and HAB groups, respectively, suggesting that BP<sub>ND</sub> in HAB is 
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twice that of MABs (<a href="https://doi.org/10.1038/jcbfm.2014.46">Owen et al, 2014</a>).</p>
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<p>The highest uptake of [<sup>11</sup>C]PBR28 is in <a href="./organ_kidney.html">kidneys</a>, 
<a href="./organ_spleen.html">spleen</a>, <a href="./organ_heart.html">heart</a>, 
and <a href="./organ_lung.html">lungs</a>, organs with high TSPO expression, except in LAB where 
uptake can only be seen in the <a href="./organ_liver.html">liver</a>, gallbladder, and 
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<a href="./organ_bladder.html">urinary bladder</a> 
(<a href="https://doi.org/10.2967/jnumed.107.044842">Brown et al, 2007</a>; 
<a href="https://doi.org/10.1016/j.neuroimage.2009.11.056">Kreisl et al, 2010</a>).</p> 

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<h2><a name="brain">Brain</a></h2>

<h3>Scan protocol</h3>

<p>90-minute dynamic scan with arterial blood sampling is typically used 
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(<a href="https://doi.org/10.1093/brain/awt145">Kreisl et al, 2013b</a>; 
<a href="https://doi.org/10.1038/jcbfm.2014.46">Owen et al, 2014</a>; 
<a href="https://doi.org/10.1038/jcbfm.2014.55">Rizzo et al, 2014</a>; 
<a href="https://doi.org/10.1001/jamaneurol.2015.0941">Gershen et al, 2015</a>; 
<a href="https://doi.org/10.1176/appi.ajp.2015.14101358">Bloomfield et al, 2016</a>; 
<a href="https://doi.org/10.1007/s00259-015-3149-8">Collste et al., 2016</a>).

<a href="https://doi.org/10.2967/jnumed.111.091694">Hirvonen et al (2012)</a>, 
<a href="https://doi.org/10.1016/j.bbi.2013.06.010">Hannestad et al (2013)</a>, 
<a href="https://doi.org/10.1007/s00259-015-3043-4">Park et al (2015)</a>, and 
<a href="https://doi.org/10.1073/pnas.1511003112">Sandiego et al (2015)</a> scanned 
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subjects for 120 minutes.
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<a href="https://doi.org/10.1093/brain/awv184">Jucaite et al (2015)</a> performed the analysis using 
45-, 60-, and 90-min time intervals, and recommended using 60-min scans to minimize contribution of 
radioligand metabolites to the brain data.</p>
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<p>Scans should be performed at the same time of day, because afternoon scans tend to provide 
higher uptake values than morning scans because of changes in plasma concentrations 
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(<a href="https://doi.org/10.1007/s00259-015-3149-8">Collste et al., 2016</a>).</p> 

<p>Propofol anaesthesia may markedly decrease distribution volume of [<sup>11</sup>C]PBR28 in the 
human brain (<a href="https://doi.org/10.2967/jnumed.112.106872">Hines et al., 2013</a>).</p>

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<h3>Analysis methods</h3>

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<p>TSPO is expressed not only on activated microglia but also in endothelial walls and 
immune cells of the blood. 
The marked endothelial binding of [<sup>11</sup>C]PBR28 and other second-generation TSPO ligands 
prevents the use of traditional <a href="./model_compartmental_ref.html">reference tissue models</a> 
or using supervised cluster analysis to extract the reference time-activity curve, since there is 
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no TSPO-free region 
(<a href="https://doi.org/10.1016/j.neuroimage.2007.09.063">Imaizumi et al., 2008</a>).</p>  
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<p>Quantification of [<sup>11</sup>C]PBR28 brain PET studies is usually performed using reversible 
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two-tissue compartmental model (2TCM)
(<a href="https://doi.org/10.1016/j.neuroimage.2007.11.011">Fujita et al., 2008</a>). 
Compartmental models with arterial plasma input provide us 
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the <a href="./model_distribution_volume.html">distribution volume</a> (V<sub>T</sub>).
V<sub>T</sub> estimated using multilinear analysis MA1 with fit start time of 30 min was found to 
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correlate well with V<sub>T</sub> from 2TCM by 
<a href="https://doi.org/10.1016/j.bbi.2013.06.010">Hannestad et al (2013)</a> and 
<a href="https://doi.org/10.1007/s00259-015-3043-4">Park et al (2015)</a>.
<a href="https://doi.org/10.1073/pnas.1511003112">Sandiego et al (2015)</a> used LEGA method 
(start time 30 min) to calculate parametric V<sub>T</sub> images.
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In contrast to several human studies, in rhesus monkeys the 1TCM was found to provide more accurate 
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V<sub>T</sub> than 2TCM 
(<a href="https://doi.org/10.1016/j.neuroimage.2007.09.063">Imaizumi et al., 2008</a>).</p>
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<p>TSPO tracer kinetics in the brain seem to consist of a slow irreversible (during PET scan) 
component localized in the brain main vasculature, venous sinuses, and arteries, as well as a faster 
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reversible component attributed to microglia 
(<a href="https://doi.org/10.1038/jcbfm.2014.55">Rizzo et al, 2014</a>).
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When the slow component for endothelial vascular TSPO binding has been included in the 
compartmental model (2TCM-1K), substantially better fits have been obtained. Resulting V<sub>T</sub> 
estimates are about one-third of the V<sub>T</sub>s from conventional 2TCM analysis, and correlation 
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is poor (<a href="https://doi.org/10.1038/jcbfm.2014.55">Rizzo et al., 2014</a>).
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Simulations suggest that 2TCM-1K would provide V<sub>T</sub> that is more sensitive to true 
variations in microglial TSPO binding. In addition to endothelial vascular binding, 2TCM-1K might 
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also correct for tissue uptake of label-carrying plasma metabolites of the radioligand.
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2TCM-1K model has since been used by 
<a href="https://doi.org/10.1176/appi.ajp.2015.14101358">Bloomfield et al (2016)</a>.</p>
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<p><a href="https://doi.org/10.1007/s11481-010-9243-6">Oh et al (2011)</a> used 
<a href="./model_mtga.html#logan">Logan plot</a> to calculate parametric V<sub>T</sub> images 
from 120-min PET scans; image noise leads to negative bias in Logan plot V<sub>T</sub>, 
and V<sub>T</sub> in image was indeed 9% smaller than V<sub>T</sub> from regional analysis. 
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Noise-induced bias in V<sub>T</sub> images can be reduced by using stationary wavelet aided 
parametric imaging (WAPI) approach
(<a href="https://doi.org/10.1093/brain/awv184">Jucaite et al., 2015</a>;
<a href="https://doi.org/10.1007/s00259-015-3149-8">Collste et al., 2016</a>;
<a href="https://doi.org/10.1002/ana.24909">Forsberg et al., 2017</a>).
<a href="https://doi.org/10.1016/j.bbi.2018.09.018">Albrecht et al (2019)</a> fitted Logan plot
using data range of 33-63 min.
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In rats, both Logan plot and <a href="./model_compartmental.html#3cm">2TCM</a> are feasible 
(<a href="https://doi.org/10.1371/journal.pone.0125917">T&oacute;th et al, 2015</a>).</p>
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<p>V<sub>T</sub> shows high intersubject variability, also after taking TSPO genotype into account.
Age, BMI, and sex can be confounding factors in clinical studies
(<a href="https://doi.org/10.1007/s00259-019-04403-7">Tuisku et al., 2019</a>).
One possible cause may be the variable <a href="./plasma_protein_binding.html">plasma protein 
binding</a> of the tracer (<a href="https://doi.org/10.1038/jcbfm.2014.55">Rizzo et al, 2014</a>; 
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<a href="https://doi.org/10.1176/appi.ajp.2015.14101358">Bloomfield et al, 2016</a>).
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Therefore V<sub>T</sub> has been divided by the measured free fraction of tracer in the plasma 
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(<em>f<sub>p</sub></em>) 
(<a href="https://doi.org/10.1007/s11481-010-9243-6">Oh et al. 2011</a>; 
<a href="https://doi.org/10.1016/j.bbi.2013.06.010">Hannestad et al, 2013</a>; 
<a href="https://doi.org/10.1001/jamaneurol.2015.0941">Gershen et al, 2015</a>; 
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<a href="https://doi.org/10.2967/jnumed.114.146027">Lyoo et al, 2015</a>;
<a href="https://doi.org/10.1186/s13550-018-0401-9">Richards et al., 2018</a>). 
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However it has been estimated that the measurement error and noise from f<sub>p</sub> may even 
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increase the variability in "corrected" V<sub>T</sub> 
(<a href="https://doi.org/10.1007/s00259-015-3043-4">Park et al, 2015</a>; 
<a href="https://doi.org/10.1176/appi.ajp.2015.14101358">Bloomfield et al, 2016</a>), 
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and therefore it has been proposed that V<sub>T</sub> ratio should be used instead, obtained by 
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dividing regional V<sub>T</sub> by V<sub>T</sub> from the whole brain 
(<a href="https://doi.org/10.1176/appi.ajp.2015.14101358">Bloomfield et al, 2016</a>).
<a href="https://doi.org/10.2967/jnumed.114.146027">Lyoo et al (2015)</a> did not find any 
difference in COV% of V<sub>T</sub> and V<sub>T</sub>/f<sub>p</sub>.
<a href="https://doi.org/10.1016/j.bbi.2016.01.019">Kanegawa et al (2016)</a> have shown that 
[<sup>11</sup>C]PBR28 binding in blood cells correlates with V<sub>T</sub> in the brain, even when 
TSPO genotype is taken into account. Normalization of brain V<sub>T</sub> by V<sub>T</sub> of 
blood cells reduced intra-individual variability only when time between PET scans was short 
(<a href="https://doi.org/10.1016/j.bbi.2016.01.019">Kanegawa et al., 2016</a>).</p>
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<p>The mean absolute variability in V<sub>T</sub> (estimated using 2TCM where V<sub>B</sub> was 
fixed to 5%) in the brain gray matter in healthy human subjects, determined in test-retest setting, 
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was 18.3&plusmn;12.7 % and ICC 0.90-0.94 for 91-min scans 
(<a href="https://doi.org/10.1007/s00259-015-3149-8">Collste et al., 2016</a>);
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reducing analysis time to 63 min did not increase the variability.
Performing both of the scans at the same time of the day reduced variance to 15.9&plusmn;12.2 % for 
the 91-min analysis, since the afternoon scans resulted in higher V<sub>T</sub> estimates than 
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morning scans; this was caused by reduced plasma TAC in the afternoon scans 
(<a href="https://doi.org/10.1007/s00259-015-3149-8">Collste et al., 2016</a>).</p>
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<p>V<sub>T</sub> in HAB group is about 40% higher than in MAB group 
(<a href="https://doi.org/10.1038/jcbfm.2012.131">Kreisl et al, 2013a</a>).
Therefore <a href="https://doi.org/10.1001/jamaneurol.2015.0941">Gershen et al (2015)</a> multiplied 
the V<sub>T</sub> in MAB group by 1.4.</p> 
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<p>TSPO occupancy study was analyzed 2TCM, using <a href="./receptor_occupancy.html"#lassen_plot"
>Lassen plot</a> to estimate V<sub>ND</sub>
(<a href="https://doi.org/10.1002/syn.21970">Frankle et al., 2017</a>).</p>

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<p>Logan plot with reference tissue input has also been used to analyse [<sup>11</sup>C]PBR28 data.
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<a href="https://doi.org/10.2967/jnumed.116.187161">Datta et al (2017)</a> used caudate as the
reference region when studying brain white matter in healthy subjects and subjects with 
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<a href="./dis_ms.html">MS</a>.</p>
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<h4>SUV and SUVR</h4>

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<p><a href="./model_suv.html">Standardized uptake value</a> (SUV) is a semiquantitative method that 
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is often used to analyse also [<sup>11</sup>C]PBR28 data.
<a href="https://doi.org/10.1371/journal.pone.0125917">T&oacute;th et al (2015)</a> have shown that 
SUV and V<sub>T</sub> correlate well in healthy rats and mice, and test-retest variability is good.
However, in baboon studies correlation was poor 
(<a href="https://doi.org/10.1016/j.nucmedbio.2014.11.003">Yoder et al, 2015</a>).</p>

<p>In human studies, SUV calculation time was set to 40-90 min by 
<a href="https://doi.org/10.1007/978-3-319-02126-3_15">Kim et al (2013)</a> and 
<a href="https://doi.org/10.1001/jamaneurol.2015.0941">Gershen et al (2015)</a>, 
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60-90 min by <a href="https://doi.org/10.1016/j.nicl.2015.01.009">Z&uuml;rcher et al (2015)</a>, 
60-120 min by <a href="https://doi.org/10.2967/jnumed.111.091694">Hirvonen et al (2012)</a>, and
33-63 min by <a href="https://doi.org/10.1016/j.bbi.2018.09.018">Albrecht et al (2019)</a>.
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<a href="https://doi.org/10.2967/jnumed.114.146027">Lyoo et al (2015)</a> noticed that uptake in 
cerebellum did not differ between healthy subjects and patients with Alzheimer's disease (AD), and 
proposed using <a href="./model_ref_ratio.html">SUV ratio</a> (SUVR) from 60-90 min, with 
cerebellum as pseudo-reference region. 
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<a href="https://doi.org/10.1186/s13550-016-0226-3">Nair et al (2016)</a> reported that the best 
test-retest variability in AD study was obtained when using whole brain as the pseudo-reference.
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Whole brain (not including the ventricles) has been used as reference to calculate SUVR maps from 
data range 60-90 min in several brain studies
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(<a href="https://doi.org/10.1093/brain/awu377">Loggia et al., 2015</a>;
<a href="https://doi.org/10.1016/j.nicl.2015.01.009">Zürcher et al., 2015</a>;
<a href="https://doi.org/10.1038/s41380-019-0433-1">Albrecht et al., 2021</a>).

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<a href="https://doi.org/10.2967/jnumed.116.178335">Albrecht et al (2018)</a> proposed using 
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occipital cortex as pseudo-reference region in patients with chronic low back pain or ALS,
and used it also in PET studies of fibromyalgia patients
(<a href="https://doi.org/10.1016/j.bbi.2018.09.018">Albrecht et al., 2019</a>).</p>
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<p>If inflammation is localized on one side of the brain only, for example in 
<a href="./dis_stroke.html">stroke</a> or epilepsy, <a href="./model_ai.html">Asymmetry index</a> 
(AI) can be calculated from SUV 
(<a href="https://doi.org/10.1001/jamaneurol.2015.0941">Gershen et al., 2015</a>).
In studies of lumbar radiculopathy, the two sides of neurofamina (containing dorsal root ganglion 
and nerve roots) can be compared, and for the <a href="./organ_spinal_cord.html">spinal cord</a>, 
healthy spinal cord segments can be used as reference
(<a href="https://doi.org/10.1097/j.pain.0000000000001171">Albrecht et al., 2018</a>).</p>


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<p>In a mice study SUV between 30 and 60 min was calculated, and normalized by dividing it with 
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the SUV of heart (<a href="https://doi.org/10.1002/glia.22978">Mirzaei et al., 2016</a>).</p>
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<h2><a name="BAT">Brown adipose tissue</a></h2>

<p>Because of the abundance of mitochondria in <a href="./organ_bat.html">brown adipose tissue</a> 
(BAT), TSPO tracers have the potential to be used for in vivo detection of BAT.
<a href="https://doi.org/10.1007/s11307-017-1129-z">Ran et al. (2018)</a> have successfully used
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[<sup>11</sup>C]PBR28 PET late scan (60-90 min p.i.) in BAT imaging in humans.</p>
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<h2>Arterial plasma input</h2>

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<p>The binding group affects the arterial plasma input curves (examples in 
<a href="#fig_pbr28_ptacs">Fig 1</a>). 
Reliable <a href="./input_idif.html">image-derived arterial input function</a> is difficult to 
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obtain (<a href="https://doi.org/10.1371/journal.pone.0017056">Zanotti-Fregonara et al., 2011</a>),
and thus <a href="./input_sampling.html">arterial sampling</a> is recommended.</p> 

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<a name="fig_pbr28_ptacs"></a>
<figure style="border: 1px solid #000;">
  <a href="./pic/PBR28_PTACs.png">
  <img style="width:600px; height:200px; margin: 0.5em;" src="./pic/PBR28_PTACs.png"
       alt="PBR28 plasma curves"></a>
  <figcaption style="margin: 0.5em;"><strong>Figure 1.</strong> 
  Examples of total radioactivity concentration curves in plasma after bolus [<sup>11</sup>C]PBR28 
  administration. The initial part of the plasma data, collected using 
  <a href="./input_abss.html">ABSS</a>, is excluded from the plots.<br>
  </figcaption>
</figure>

<p>The plasma curves are on highest levels in LAB subjects (<a href="#fig_pbr28_ptacs">Fig 1</a>)
because the specific binding to <a href="./target_tspo.html">TSPO</a> in all organs is low and 
therefore [<sup>11</sup>C]PBR28 stays longer in the circulation.
In the subjects of the HAB group the clearance of [<sup>11</sup>C]PBR28 is so fast that the
total plasma radioactivity concentration is soon dominated by label-carrying metabolites, which
have relatively low clearance, causing the total plasma curve to increase after &sim;20 min.
This can be seen even in some subjects of the MAB group.</p>


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<h3>Blood-to-plasma conversion</h3>

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<p><a href="./input_blood-to-plasma.html">Correction of arterial blood TAC to plasma</a> requires 
that plasma-to-blood ratio is known. This ratio for [<sup>11</sup>C]PBR28 is changing during 
the scan, and it is different in the binding groups.
Blood-to-plasma ratios can be <a href="./input_blood-to-plasma_fitting.html">fitted</a> using 
program <a href="./tpcclib/doc/fit_bpr.html">fit_bpr</a>,
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with option <code>-model=ihillb</code> for HAB and MAB groups, and option <code>-model=hillb</code> 
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for LAB group.</p>

<p>Population ratio curves for each binding group are implemented in programs <a href=
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"./tpcclib/doc/b2plasma.html">b2plasma</a> and <a href="./tpcclib/doc/p2blood.html">p2blood</a>.</p> 

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<h3>Plasma metabolite correction</h3>

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<p>Arterial plasma TAC needs to be <a href="./input_metabolite_correction.html">corrected for 
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metabolites</a>. 
<a href="https://doi.org/10.1021/ac401742v">Nakao et al (2013)</a> have published method for
assessing plasma protein binding and metabolites simultaneously in a [<sup>11</sup>C]PBR28 study.</p>

<p><a href="https://doi.org/10.1007/s00259-015-3149-8">Collste et al (2016)</a> fitted 
plasma parent fractions with three-exponential function,
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and <a href="https://doi.org/10.2967/jnumed.116.178335">Albrecht et al (2018)</a> with 
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biexponential function. <a href="https://doi.org/10.2967/jnumed.115.165019">Parente et al (2016)</a> 
used <a href="./input_parent_fitting.html#monoexp">one-phase exponential function</a> in rat studies.
<a href="https://doi.org/10.1523/JNEUROSCI.0928-14.2014">Narendran et al (2014)</a> applied 
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the Hill model fitting:</p>

<div class="eqs">
<script type="math/tex; mode=display">
  f_{parent}(t)=1 - \frac{p_1 \times t^{p_2}}{t^{p_2} + p_3}
</script>
</div>

<p>This <a href="./input_parent_fitting_hill.html">Hill function</a> has also been used in Turku.</p>

<p><a href="https://doi.org/10.1176/appi.ajp.2015.14101358">Bloomfield et al (2016)</a> used 
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extended Hill (sigmoidal) function for fitting [<sup>11</sup>C]PBR28 plasma parent fractions:</p>
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<div class="eqs">
<script type="math/tex; mode=display">
  f_{parent}(t)=1 - \frac{p_1 + p_2 \times t}{(\frac{p_3}{t})^{p_4} + 1}
</script>
</div>

<p>, where p<sub>1</sub> &gt; 0.</p>

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<p><a href="https://doi.org/10.1038/jcbfm.2014.46">Owen et al (2014)</a> fitted parent fractions 
using sigmoid function:</p>
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<div class="eqs">
<script type="math/tex; mode=display">
  f_{parent}(t)=\frac{(1 - \frac{t^3}{t^3 + 10^a})^b + c}{1+c}
</script>
</div>

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<p><a href="https://doi.org/10.1007/s00259-015-3043-4">Park et al (2015)</a> fitted plasma parent 
fractions with an inverted gamma function.</p> 
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<p>Metabolite corrected plasma TAC can be further 
<a href="./input_fitting_exp.html">fitted to sum of three exponentials</a> from the time of peak 
(<a href="https://doi.org/10.1523/JNEUROSCI.0928-14.2014">Narendran et al., 2014</a>).</p>


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<br>
<h2>See also:</h2>

<ul>
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  <li><a href="./target_tspo.html">PET imaging of the translocator protein (TSPO)</a></li>
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  <li><a href="./target_inflammation.html">Inflammation and infection</a></li>
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  <li><a href="./analysis_11c-pk11195.html">[<sup>11</sup>C]-<em>R</em>-PK11195</a></li>
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  <li><a href="./analysis_18f-dpa714.html">[<sup>18</sup>F]DPA-714</a></li>
  <li><a href="./input_process.html">Processing input data</a></li>
</ul>

<br><hr>
<h2>References:</h2>

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<p>Bloomfield PS, Selvaraj S, Veronese M, Rizzo G, Bertoldo A, Owen DR, Bloomfield MA, Bonoldi I, 
Kalk N, Turkheimer F, McGuire P, de Paola V, Howes OD. Microglial activity in people at ultra high 
risk of psychosis and in schizophrenia: An [<sup>11</sup>C]PBR28 PET brain imaging study. 
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<em>Am J Psychiatry</em> 2016; 173(1): 44-52.
doi: <a href="https://doi.org/10.1176/appi.ajp.2015.14101358">10.1176/appi.ajp.2015.14101358</a>.</p>
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<p>Collste K, Forsberg A, Varrone A, Amini N, Aeinehband S, Yakushev I, Halldin C, Farde L, 
Cervenka S. Test-retest reproducibility of [<sup>11</sup>C]PBR28 binding to TSPO in healthy 
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control subjects. <em>Eur J Nucl Med Mol Imaging</em> 2016; 43(1): 173-183.
doi: <a href="https://doi.org/10.1007/s00259-015-3149-8">10.1007/s00259-015-3149-8</a>.</p>
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<p>Fujita M, Imaizumi M, Zoghbi SS, Fujimura Y, Farris AG, Suhara T, Hong J, Pike VW, Innis RB. 
Kinetic analysis in healthy humans of a novel positron emission tomography radioligand to image 
the peripheral benzodiazepine receptor, a potential biomarker for inflammation. 
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<em>Neuroimage</em> 2008; 40(1): 43-52. doi: 
<a href="https://doi.org/10.1016/j.neuroimage.2007.11.011">10.1016/j.neuroimage.2007.11.011</a>.</p>
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<p>Gershen LD, Zanotti-Fregonara P, Dustin IH, Liow JS, Hirvonen J, Kreisl WC, Jenko KJ, Inati SK, 
Fujita M, Morse CL, Brouwer C, Hong JS, Pike VW, Zoghbi SS, Innis RB, Theodore WH. 
Neuroinflammation in temporal lobe epilepsy measured using positron emission tomographic imaging of 
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translocator protein. <em>JAMA Neurol.</em> 2015; 72(8): 882-888.
doi: <a href="https://doi.org/10.1001/jamaneurol.2015.0941">10.1001/jamaneurol.2015.0941</a>.</p>
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<p>Hines CS, Fujita M, Zoghbi SS, Kim JS, Quezado Z, Herscovitch P, Miao N, Ferraris Araneta MD, 
Morse C, Pike VW, Labovsky J, Innis RB. Propofol decreases in vivo binding of <sup>11</sup>C-PBR28 
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to translocator protein (18 kDa) in the human brain. <em>J Nucl Med.</em> 2013; 54(1): 64-69.
doi: <a href="https://doi.org/10.2967/jnumed.112.106872">10.2967/jnumed.112.106872</a>.</p>
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<p>Imaizumi M, Briard E, Zoghbi SS, Gourley JP, Hong J, Fujimura Y, Pike VW, Innis RB, Fujita M. 
Brain and whole-body imaging in nonhuman primates of [<sup>11</sup>C]PBR28, a promising PET 
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radioligand for peripheral benzodiazepine receptors. <em>Neuroimage</em> 2008; 39(3): 1289-1298. doi: 
<a href="https://doi.org/10.1016/j.neuroimage.2007.09.063">10.1016/j.neuroimage.2007.09.063</a>.</p>
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<p>Kreisl WC, Fujita M, Fujimura Y, Kimura N, Jenko KJ, Kannan P, Hong J, Morse CL, Zoghbi SS, 
Gladding RL, Jacobson S, Oh U, Pike VW, Innis RB. 
Comparison of [<sup>11</sup>C]-(<em>R</em>)-PK 11195 and [<sup>11</sup>C]PBR28, two radioligands for 
translocator protein (18 kDa) in human and monkey: Implications for positron emission tomographic 
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imaging of this inflammation biomarker. <em>Neuroimage</em> 2010; 49(4): 2924-2932. doi: 
<a href="https://doi.org/10.1016/j.neuroimage.2009.11.056">10.1016/j.neuroimage.2009.11.056</a></p>
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<p>Kreisl WC, Jenko KJ, Hines CS, Lyoo CH, Corona W, Morse CL, Zoghbi SS, Hyde T, Kleinman JE, 
Pike VW, McMahon FJ, Innis RB. A genetic polymorphism for translocator protein 18 kDa affects both 
<em>in vitro</em> and <em>in vivo</em> radioligand binding in human brain to this putative biomarker 
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of neuroinflammation. <em>J Cereb Blood Flow Metab.</em> 2013a; 33(1): 53-58.
doi: <a href="https://doi.org/10.1038/jcbfm.2012.131">10.1038/jcbfm.2012.131</a>.</p>
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<p>Kreisl WC, Lyoo CH, McGwier M, Snow J, Jenko KJ, Kimura N, Corona W, Morse CL, Zoghbi SS, 
Pike VW, McMahon FJ, Turner RS, Innis RB. <em>In vivo</em> radioligand binding to translocator 
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protein correlates with severity of Alzheimer's disease. <em>Brain</em> 2013b; 136(Pt 7): 2228-2238.
doi: <a href="https://doi.org/10.1093/brain/awt145">10.1093/brain/awt145</a>.</p>
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<p>Lyoo CH, Ikawa M, Liow JS, Zoghbi SS, Morse CL, Pike VW, Fujita M, Innis RB, Kreisl WC. 
Cerebellum can serve as a pseudo-reference region in Alzheimer disease to detect neuroinflammation 
measured with PET radioligand binding to translocator protein. 
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<em>J Nucl Med.</em> 2015; 56(5): 701-706.
doi: <a href="https://doi.org/10.2967/jnumed.114.146027">10.2967/jnumed.114.146027</a>.</p>
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<p>Owen DR, Gunn RN, Rabiner EA, Bennacef I, Fujita M, Kreisl WC, Innis RB, Pike VW, Reynolds R, 
Matthews PM, Parker CA. Mixed-affinity binding in humans with 18-kDa translocator protein ligands. 
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<em>J Nucl Med.</em> 2011; 52(1): 24-32.
doi: <a href="https://doi.org/10.2967/jnumed.110.079459">10.2967/jnumed.110.079459</a>.</p>
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<p>Owen DR, Yeo AJ, Gunn RN, Song K, Wadsworth G, Lewis A, Rhodes C, Pulford DJ, Bennacef I, 
Parker CA, StJean PL, Cardon LR, Mooser VE, Matthews PM, Rabiner EA, Rubio JP. 
An 18-kDa translocator protein (TSPO) polymorphism explains differences in binding affinity of 
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the PET radioligand PBR28. <em>J Cereb Blood Flow Metab.</em> 2012; 32(1): 1-5.
doi: <a href="https://doi.org/10.1038/jcbfm.2011.147">10.1038/jcbfm.2011.147</a>.</p>
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<p>Owen DR, Guo Q, Kalk NJ, Colasanti A, Kalogiannopoulou D, Dimber R, Lewis YL, Libri V, 
Barletta J, Ramada-Magalhaes J, Kamalakaran A, Nutt DJ, Passchier J, Matthews PM, Gunn RN, 
Rabiner EA. Determination of [<sup>11</sup>C]PBR28 binding potential in vivo: a first human TSPO 
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blocking study. <em>J Cereb Blood Flow Metab.</em> 2014; 34(6): 989-994.
doi: <a href="https://doi.org/10.1038/jcbfm.2014.46">10.1038/jcbfm.2014.46</a>.</p>
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<p>Park E, Gallezot JD, Delgadillo A, Liu S, Planeta B, Lin SF, O'Connor KC, Lim K, Lee JY, 
Chastre A, Chen MK, Seneca N, Leppert D, Huang Y, Carson RE, Pelletier D. <sup>11</sup>C-PBR28 
imaging in multiple sclerosis patients and healthy controls: test-retest reproducibility and focal 
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visualization of active white matter areas. <em>Eur J Nucl Med Mol Imaging</em> 2015; 42(7): 
1081-1092. doi: <a href="https://doi.org/10.1007/s00259-015-3043-4">10.1007/s00259-015-3043-4</a>.</p>
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<p>Rizzo G, Veronese M, Tonietto M, Zanotti-Fregonara P, Turkheimer FE, Bertoldo A. 
Kinetic modeling without accounting for the vascular component impairs the quantification of 
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[<sup>11</sup>C]PBR28 brain PET data. <em>J Cereb Blood Flow Metab.</em> 2014; 34(6): 1060-1069.
doi: <a href="https://doi.org/10.1038/jcbfm.2014.55">10.1038/jcbfm.2014.55</a>.</p>
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<p>T&oacute;th M, Doorduin J, Häggkvist J, Varrone A, Amini N, Halldin C, Gulyás B.
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Positron emission tomography studies with [<sup>11</sup>C]PBR28 in the healthy rodent brain: 
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Validating SUV as an outcome measure of neuroinflammation. <em>PLoS One</em> 2015; 10(5):e0125917.
doi: <a href="https://doi.org/10.1371/journal.pone.0125917">10.1371/journal.pone.0125917</a>.</p>
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<p>Yoder KK, Nho K, Risacher SL, Kim S, Shen L, Saykin AJ. 
Influence of TSPO genotype on <sup>11</sup>C-PBR28 standardized uptake values. 
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<em>J Nucl Med.</em> 2013; 54(8): 1320-1322.
doi: <a href="https://doi.org/10.2967/jnumed.112.118885">10.2967/jnumed.112.118885</a>.</p>
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<p>Yoder KK, Territo PR, Hutchins GD, Hannestad J, Morris ED, Gallezot JD, Normandin MD, Cosgrove KP. 
Comparison of standardized uptake values with volume of distribution for quantitation of 
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[<sup>11</sup>C]PBR28 brain uptake. <em>Nucl Med Biol.</em> 2015; 42(3): 305-308. doi: 
<a href="https://doi.org/10.1016/j.nucmedbio.2014.11.003">10.1016/j.nucmedbio.2014.11.003</a>.</p>
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