Quantification of [11C]-R-PK11195 PET studies

PK11195 is a selective ligand for the translocator protein (TSPO), formerly known as peripheral benzodiazepine receptor (PBR).

Brain

Analysis methods used in literature

Schuitemaker et al. (2007a) published an extensive comparison of methods for producing parametric images of [11C]-R-PK11195 binding. They suggest that when plasma input is available the Logan graphical analysis should be used (30-60 min linear fit), and with reference region input RPM1 (original version by Gunn et al. 1997) should be used, provided that the range of basis functions is carefully optimized.

Image-derived input function can be obtained from carotid arteries in sufficient quality to detect glial activation in Parkinson’s disease (Kang et al., 2018).

2-tissue compartment model with plasma input

Kropholler et al. (2004) have validated the use of 2-tissue compartment model in estimating the total distribution volume (VT) and binding potential (k3/k4). VB was fitted, but K1/k2 was fixed to whole cortex value. With another tracer for peripheral benzodiazepine receptor ([11C]DAA1106) K1/k2 was found to differ among individuals (Ikoma et al., 2007), suggesting that k3/k4 should be preferred over VT.

Reference tissue input

Because glial cells are located everywhere in the brain, there is no true reference region for [11C]-R-PK11195 binding. Therefore, cluster analysis has been applied in extracting a reference tissue curve from the dynamic image, and it is used as input function for the simplified reference tissue model (Banati et al., 2000; Kropholler et al., 2006 and 2007).

However, the unsupervised tissue classification does not succeed in finding a reference tissue curve in all cases, and therefore a supervised clustering algorithm has been developed and validated (Turkheimer et al. 2007), and Matlab software Super-PK is available for this purpose. Reference region curve was then used to estimate binding potential (BPND) with simplified reference tissue model (SRTM) and rank-shaping regularized exponential spectral analysis (RS-ESA). Wavelet-based Logan plot, basis pursuit and SRTM give better ICC than ratio or traditional Logan method (Anderson et al., 2007).

For certain diseases it has been shown that cerebellum or certain cortical regions do not have increased microglial burden, and then these regions can be used as reference region for reference tissue model (Gerhard et al., 2002; 2005). Cerebellar grey matter can be used as reference tissue for quantifying TSPO expression in human glioma (Su et al., 2015).

Ratio method with white matter as reference tissue

Hammoud et al. (2005) validated by simulations the calculation of tissue-to-white matter ratio as a parameter related to binding potential. They calculated the ratio from 10 to 60 min p.i.. Unfortunately this method was not included in the comparison by Schuitemaker et al. (2007).

Suggested analysis method for Turku

[11C]-R-PK11195 has radioactive metabolites in the plasma and at least [11C]CH2O (formaldehyde) easily penetrates the blood-brain barrier (De Vos et al., 1999). The uptake of labeled metabolites in the brain precludes perfect quantification of peripheral benzodiazepine receptors, but an index related to the receptor concentration can still be achieved.

When plasma curves corrected for radioactive metabolites (Roivainen et al., 2009) are available, the method of Kropholler et al. (2004) is preferable choice for analysis method for regional data. To calculate parametric VT images the Logan graphical analysis is recommended (Schuitemaker et al., 2007), although a strictly linear phase can not be achieved.

When plasma curves are not available, the very simple method by Hammoud et al. (2005) seems like worth testing. Ratio image can be calculated e.g. using program imgratio. However, if precise quantitation is needed and extraction of valid reference tissue curves is possible (supervised cluster analysis is available in TPC; contact Jouni Tuisku), then RPM1 method is recommended (Schuitemaker et al., 2012), using PMOD or imgbfbp. Set the range of basis functions to the values determined for use with [11C]-R-PK11195 in TPC (contact Jouni Tuisku).

Rheumatoid arthritis

11C-R-PK11195 PET imaging allows noninvasive in vivo imaging and quantification of macrophages in rheumatoid synovitis, and possibly even in subclinical synovitis (van der Laken et al., 2008; Kropholler et al., 2009). Noninvasive visualization of macrophages may be useful both for detecting early synovitis and for monitoring synovitis activity during treatment (van der Laken et al., 2008; Gent et al., 2012; Roivainen et al., 2013).

Analysis methods used in literature

van der Laken et al. (2008) reported that 1-tissue compartment model with arterial plasma input can be used to estimate regional volume of distribution (VT) of [11C]-R-PK11195 in synovial tissue, and that [11C]-R-PK11195 uptake in synovial tissue was due to binding to TSPO on macrophages.

van der Laken et al. (2008) also found a good correlation between VT and SUV40-60, as well as good correlation between SUV40-60 and macrophage infiltration in synovial tissue. Kropholler et al. (2009) recommended calculating SUV20-40 in clinical use. Therefore, the scanning procedure could be simplified and shortened to a 20-minute static scan of joints of interest. This would make it a method that could be applied in routine clinical practice (van der Laken et al., 2008; Kropholler et al., 2009), and in whole-body imaging.

A simple scoring based on visual analysis may be useful in following arthritis activity (Gent et al., 2012 and 2014).

Suggested analysis method for Turku PET Centre

When plasma curves corrected for radioactive metabolites are available the 1-tissue compartment model fitting of van der Laken et al. (2008) is preferable choice for analysis method for regional data. To calculate parametric VT images the Logan graphical analysis may be recommended (imgdv).

For clinical routine analysis, and when plasma curves are not available, the SUV images can be computed, preferably from 20 to 40 min after injection.

For research purposes the supervised clustering method can be applied to extract the reference tissue curve (Rissanen et al., 2014).

Processing of plasma data in TPC

A script called PK11195_input.bat is available for processing plasma input data. As input it needs four data files, and hematocrit for plasma-blood TAC conversion:

  1. Blood data file from online blood sampler (*.bld, *.alg, *.lis, *.txt)),
  2. Plasma TAC file from manual sampling (*ap.kbq),
  3. count-rate file (*.cr, *.r, *.hc, *.head or *.dft),
  4. fraction file of parent tracer in plasma (*.rat),
  5. Haematocrit (e.g. 0.40)

In addition, user has to give the names of output files:

  1. Parent tracer TAC in plasma (e.g. *apc.kbq),
  2. Metabolite TAC in plasma (e.g. *apm.kbq),
  3. Blood TAC (*ab.kbq).

Output TACs are calibrated and corrected for physical decay, and delay-time). In addition, the script will create SVG and/or PNG images where the user can verify how fit of an exponential function into the fraction data succeeded, how delay correction succeeded, and how the resulting curves look like.

Dispersion correction is not applied in this script because the effect of dispersion is minimal in case of an 11C labeled tracer with relatively slow kinetics.

Script can be used in Windows command-prompt window (CLI) directly, or a script can be written that processes all studies.


See also:



References:

Anderson AN, Pavese N, Edison P, Tai YF, Hammers A, Gerhard A, Brooks DJ, Turkheimer FE. A systematic comparison of kinetic modelling methods generating parametric maps for [11C]-(R)-PK11195. Neuroimage 2007; 36: 28-37.

Banati RB, Newcombe J, Gunn RN, Cagnin A, Turkheimer F, Heppner F, Price G, Wegner F, Giovannoni G, Miller DH, Perkin GD, Smith T, Hewson AK, Bydder G, Kreutzberg GW, Jones T, Cuzner ML, Myers R. The peripheral benzodiazepine binding site in the brain in multiple sclerosis. Quantitative in vivo imaging of microglia as a measure of disease activity. Brain 2000; 123:2321-2337.

Banati RB. Visualising microglial activation in vivo. Glia 2002; 40(2): 206-217.

De Vos F, Dumont F, Santens P, Slegers G, Dierckx R, De Reuck J. High-performance liquid chromatographic determination of [11C]1-(2-chlorophenyl)-N-methyl-N-(1-methylpropyl)-3-isoquinoline carboxamide in mouse plasma and tissue and in human plasma. J. Chromatogr. B 1999; 736: 61-66.

Gent YYJ, Voskuyl AE, Kloet RW, van Schaardenburg D, Hoekstra OS, Dijkmans BAC, Lammertsma AA, van der Laken CJ. Macrophage positron emission tomography imaging as biomarker for preclinical rheumatoid arthritis: findings of a prospective pilot study. Arthritis Rheum. 2012; 64(1): 62-66.

Gent YY, Ahmadi N, Voskuyl AE, Hoetjes N, van Kuijk C, Britsemmer K, Turkstra F, Boers M, Hoekstra OS, van der Laken CJ. Detection of subclinical synovitis with macrophage targeting and positron emission tomography in patients with rheumatoid arthritis without clinical arthritis. J Rheumatol. 2014; 41(11): 2145-2152.

Gerhard A, Schwarz J, Myers R, Wise R, Banati RB. Evolution of microglial activation in patients after ischemic stroke: a [11C](R)-PK11195 PET study. Neuroimage 2005; 24: 591-595.

Gerhard A, Watts J, Trender-Gerhard I, Turkheimer F, Banati RB, Bhatia K, Brooks DJ. In vivo imaging of microglial activation with [11C](R)-PK11195 PET in corticobasal degeneration. Mov Disord. 2004; 19(10): 1221-1226.

Hammoud DA, Endres CJ, Chander AR, Guilarte TR, Wong DF, Sacktor NC, McArthur JC, Pomper MG. Imaging glial cell activation with [11C]-R-PK11195 in patients with AIDS. J Neurovirol. 2005; 11(4): 346-355.

Hinz R, Boellaard R. Challenges of quantification of TSPO in the human brain. Clin Transl Imaging 2015; 3: 403-416.

Ikoma Y, Yasuno F, Ito H, Suhara T, Ota M, Toyama H, Fujimura Y, Takano A, Maeda J, Zhang M-R, Nakao R, Suzuki K. Quantitative analysis for estimating binding potential of the peripheral benzodiazepine receptor with [11C]DAA1106. J Cereb Blood Flow Metab. 2007; 27: 173-184.

Jucaite A, Cselenyi Z, Arvidsson A, Åhlberg G, Julin P, Varnäs K, Stenkrona P, Andersson J, Halldin C, Farde L. Kinetic analysis and test-retest variability of the radioligand [11C](R)-PK11195 binding to TSPO in the human brain - a PET study in control subjects. EJNMMI Res. 2012; 2: 15.

Kropholler MA, Boellaard R, Schuitemaker A, van Berckel BNM, Luurtsema G, Windhorst AD, Lammertsma AA. Development of a tracer kinetic plasma input model for (R)-[11C]PK11195 brain studies. J Cereb Blood Flow Metab. 2005; 25(7): 842-851.

Kropholler MA, Boellaard R, Schuitemaker A, Folkersma H, van Berckel BNM, Lammertsma AA. Evaluation of reference tissue models for the analysis of [11C](R)-PK11195 studies. J Cereb Blood Flow Metab. 2006; 26(11): 1431-1441.

Kropholler MA, Boellaard R, van Berckel BN, Schuitemaker A, Kloet RW, Lubberink MJ, Jonker C, Scheltens P, Lammertsma AA. Evaluation of reference regions for (R)-[11C]PK11195 studies in Alzheimer’s disease and mild cognitive impairment. J Cereb Blood Flow Metab. 2007; 27(12): 1965-1974.

Kropholler MA, Boellaard R, Elzinga EH, van der Laken CJ, Maruyama K, Kloet RW, Voskuyl AE, Dijkmans BA, Lammertsma AA. Quantification of (R)-[11C]PK11195 binding in rheumatoid arthritis. Eur J Nucl Med Mol Imaging. 2009; 36(4): 624-631.

van der Laken CJ, Elzinga EH, Kropholler MA, Molthoff CF, van der Heijden JW, Maruyama K, Boellaard R, Dijkmans BA, Lammertsma AA, Voskuyl AE. Noninvasive imaging of macrophages in rheumatoid synovitis using 11C-(R)-PK11195 and positron emission tomography. Arthritis Rheum. 2008; 58(11): 3350-3355.

Rissanen E, Tuisku J, Rokka J, Paavilainen T, Parkkola R, Rinne JO, Airas L. In vivo detection of diffuse inflammation in secondary progressive multiple sclerosis using PET imaging and the radioligand 11C-PK11195. J Nucl Med. 2014; 55(6): 939-944.

Roivainen A, Hautaniemi S, Möttönen T, Nuutila P, Oikonen V, Parkkola R, Pricop L, Ress R, Seneca N, Seppänen M, Yli-Kerttula T. Correlation of 18F-FDG PET/CT assessments with disease activity and markers of inflammation in patients with early rheumatoid arthritis following the initiation of combination therapy with triple oral antirheumatic drugs. Eur J Nucl Med Mol Imaging 2013; 40(3): 403-410.

Roivainen A, Någren K, Hirvonen J, Oikonen V, Virsu P, Tolvanen T, Rinne J. Whole-body distribution and metabolism of [N-methyl-11C](R)-1-(2-chlorophenyl)-N-(1-methylpropyl)-3-isoquinoline carboxamide in man; an imaging agent for in vivo assessment of peripheral benzodiazepine receptor activity with positron emission tomography. Eur J Nucl Med Mol Imaging 2009; 36(4): 671-682.

Schuitemaker A, van Berckel BNM, Kropholler MA, Kloet RW, Jonker C, Scheltens P, Lammertsma AA, Boellaard R. Evaluation of methods for generating parametric (R)-[11C]PK11195 binding images. J Cereb Blood Flow Metab. 2007a; 1603-1615.

Schuitemaker A, van Berckel BN, Kropholler MA, Veltman DJ, Scheltens P, Jonker C, Lammertsma AA, Boellaard R. SPM analysis of parametric (R)-[11C]PK11195 binding images: plasma input versus reference tissue parametric methods. Neuroimage 2007b; 35(4): 1473-1479.

Schuitemaker A, Kropholler MA, Boellaard R, van der Flier WM, Kloet RW, van der Doef TF, Knol DL, Windhorst AD, Luurtsema G, Barkhof F, Jonker C, Lammertsma AA, Scheltens P, van Berckel BNM. Microglial activation in Alzheimer’s disease: an (R)-[11C]PK11195 positron emission tomography study. Neurobiol Aging 2013; 34(1): 128-136.

Su Z, Roncaroli F, Durrenberger PF, Coope DJ, Karabatsou K, Hinz R, Thompson G, Turkheimer FE, Janczar K, Du Plessis D, Brodbelt A, Jackson A, Gerhard A, Herholz K. The 18-kDa mitochondrial translocator protein in human gliomas: an 11C(R)PK11195 PET imaging and neuropathology study. J Nucl Med. 2015; 56: 512-517.

Tomasi G, Edison P, Bertoldo A, Roncaroli F, Singh P, Gerhard A, Cobelli C, Brooks DJ, Turkheimer FE. Novel reference region model reveals increased microglial and reduced vascular binding of 11C-(R)-PK11195 in patients with Alzheimer’s Disease. J Nucl Med. 2008; 49: 1249-1256.

Turkheimer FE, Edison P, Pavese N, Roncaroli F, Anderson AN, Hammers A, Gerhard A, Hinz R, Tai YF, Brooks DJ. Reference and target region modeling of [11C](R)-PK11195 brain studies. J Nucl Med. 2007; 48(1): 158-167.



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Created at: 2007-01-29
Updated at: 2018-05-14
Written by: Vesa Oikonen