Introductory Nuclear Physics. David Halliday. New York: Wiley; London: Chapman & Hall, 1950. 558 pp. $6.50

development of the three Rs concept

1286 Objectives GA is an efficient method for estimating total tissue distribution volume (β1) from PET uptake data. The original GA produces a negative bias in β1. Estimates of β1 using other GA forms have less bias but less precision. Bias can also be removed from GA with an instrumental variable (IV).We propose to use the estimates from four GA methods including IV to obtain a best estimate of β1. Methods Forms of GA used are (1) ∫Rdt9/R(t)=β1∫Cpdt9/R(t)+β2 (2) ∫Cpdt9/R(t)=(1/β1)∫Rdt9/R(t)-β2/β1 and (3) R(t)=-(β1/β2)∫Cpdt9+∫Rdt9/β2 (Ichise, 2003)(Cp and R are plasma and tissue radioactivity at time t). The IV solution of (1) in vector form is β=[∑ΦΘT]-1[∑ΦY]. ΘT=[∫Cpdt9/R(t),1], Y=∫Rdt9/R(t) and Φ is the IV. Choose Φ to be uncorrelated with error. Let Φ=[∫Cpdt9/TAC(t),1] where TAC is noise-free (ie global or reference region). Simulations used a 2 compartment model with K1, k2, k4.35.086, and.0475min-1 and k3 .075, .25, .42, .7 min-1 (β1 10.5, 25.5, 40, and 64 mL/cm3) with added Gaussian noise, N=1000 for each β1. Results The error term at time t (V(t)) for (1), (2) and (3) are related as V(t), V(t)/β1, and V(t)/β2 so that if |β2| > β1 the bias is least for (3) and if β1 > 1 the bias for (2) is less than for (1). Bias from simulations given as avg over N of ( β1EST - β1TRUE) for β1=40 (64) are -6.8 (-18.5), -1.7 (-2.2), 1.6 (2.4) and 1.3 (1.2) for Eqs (1), (2), (3) and IV. (Eq(3) produces more outliers > 100 for β1 = 64). Conclusions Noise contributes to bias error differently for (1), (2) and (3) so they provide somewhat different estimates for β1, with (1) generally an underestimation and (3) with a number of outliers. The IV method of estimating β1, also provides an estimate with little bias. By using the median value of these four methods we can decrease the bias compared to (1) and increase the precision compared to (3) by eliminating the low and high values. However since the distribution of values is broader compared to (1), some method of noise removal may be needed such as the principal component method proposed by Joshi et al (2008)

The use of alternative forms of graphical analysis (GA) to balance bias and precision in PET images

Kinetic analysis in human brain of (11C)Befloxatone, a positron emission tomography ligand to image monoamine oxidase A

マウスの断面解剖アトラス = A color atlas of sectional anatomy of the mouse

Within the framework of the “Sel-tag imaging project”, a novel method was used to rapidly label protein tracers and the in vivo targeting abilities of these tracers were studied in animal models of cancer using a preclinical positron emission tomography (PET) camera. To first evaluate and optimize preclinically the use of PET tracers can facilitate their translation to and implementation in human patient studies. The ultimate goal of the different projects within the Sel-tag imaging project was to find imaging biomarkers that could potentially be used for individualizing cancer treatment and thereby improve the therapeutic results. This thesis focuses on methods employed to describe the distribution of these protein-based tracers in human xenografts. Many of the techniques used had been developed for other imaging circumstances. Therefore verification for these imaging applications was an important aspect of these papers. Paper I examined the distribution in a tumour of a medium-sized AnnexinA5-based tracer that targeted phosphatidylserine externalised during cell death in tumours in two cases; first, with no pre-treatment (baseline) and, second, after pre-treatment with a chemotherapeutic agent. Small differences between tracer uptakes in the two cases required a macro parameter analysis method for quantifications. Evaluations of the influence of the enhanced permeability and retention effect by using a size-matched control were introduced. The AnnexinA5 results were compared to those of the metabolic tracer [F]FDG and complemented with circulating serum markers to increase sensitivity. Paper II extended the analysis in paper I to incorporate more verifications that were also more thorough. The choice of input (blood or reference tissue) and the statistical significance of intergroup comparisons when using conventional uptake measurements and the more involved macro parameter analyses like in paper I were compared. We also proposed that distribution volume ratio was a more appropriate quantification parameter concept for these protein-based tracers with relatively large non-specific uptake. Paper III assessed the smaller AffibodyTM tracer ZHER2:342 as an imaging biomarker for human epidermal growth factor 2 (HER2), whose overexpressions are associated with a poor prognosis for breast cancer patients. In order to demonstrate specific binding to HER2, pre-treatment of the tumour with unlabelled protein and uptake in xenografts with low HER2 expression was evaluated. Ex vivo immunohistochemistry of expression levels supported the imaging results. Paper IV examined a radiopharmaceutical that targeted the epidermal growth factor receptor (EGFR), whose overexposure in tumours is associated with a negative prognosis. Again an AffibodyTM molecule, (ZEGFR:2377), was used and, as in in paper I, a size-matched control was also used to estimate the non-specific uptake. Uptakes, quantified by conventional uptake methods, varied in tumours with different EGFR expression levels. Ex vivo analyses of expression levels were also performed. Paper V addressed the non-uniform (heterogeneous) uptake of different tracers in a tumour tissue. An algorithm was written that aimed at incorporating all relevant aspects that will influence non-uniformity. Histograms were generated that visualized how the frequency and spread of deviations contributed to the heterogeneity. These aspects could not always be attended in a direct manner, but instead had to be handled in an indirect way. The effect of varying imaging parameters was examined as part of the validation procedure. The method developed is a robust, user-friendly tool for comparing heterogeneity in similar volume preclinical tumor tissues. LIST OF PUBLICATIONS I. Cheng Q. Lu L. Grafström J. Olofsson MH. Thorell JO. Samén E. Johansson K. Ahlzén HS. Stone-Elander S. Linder S. Arnér ESJ; Sel-tag Imaging Project. 2012. Combining [C]-AnxA5 PET imaging with serum biomarkers for improved detection in live mice of modest cell death in human solid tumor xenografts. PLoS One; 7:e42151 II. Grafström J. Stone-Elander S. 2014. Comparison of methods for evaluating radiolabelled Annexin A5 uptake in pre-clinical PET oncological studies. Nucl Med Biol; 41:793-800 III. Wållberg H. Grafström J. Cheng Q. Lu L. Martinsson Ahlzén HS. Samén E. Thorell JO. Johansson K. Dunås F. Olofsson MH. Stone-Elander S. Arnér ESJ. Ståhl S. 2012. HER2-Positive tumors imaged within 1 hour using a sitespecifically C-labeled Sel-tagged Affibody molecule. J Nucl Med; 53:14461453 IV. Cheng Q*. Wållberg H*. Grafström J*. Lu L. Thorell JO. Hägg-Olofsson M. Linder S. Johansson K. Tegnebratt T. Arnér ES. Stone-Elander S. MartinssonAhlzén HS. Ståhl S, Sel-tag imaging project. Manuscript. Preclinical PET imaging of EGFR levels: pairing a targeting with a nontargeting Sel-tagged Affibody-based tracer to estimate the specific uptake V. Grafström J. Martinsson-Ahlzén HS. Stone-Elander S. 2015. A method for comparing intra-tumoural radioactivity uptake heterogeneity in preclinical positron emission tomography studies. EJNMMI Physics; 2:19 Publications that are not part of the thesis: i. Cheng Q. Lu L. Grafström J. Olofsson MH. Thorell JO. Samén E. Johansson K. Ahlzén HS. Linder S. Arnér ES. Stone-Elander S. 2013. Sitespecifically C-labeled Sel-tagged annexin A5 and a size-matched control for dynamic in vivo PET imaging of protein distribution in tissues prior to and after induced cell death. Biochim Biophys Acta; 1830:2562-2573. ii. Arnberg F*. Samén E*. Lundberg J. Lu L. Grafström J. Söderman M. Stone-Elander S. Holmin S. 2014. Selective intra-arterial administration of F-FDG to the rat brain effects on hemispheric uptake. Neuroradiology; 56:375-380 iii. Arnberg F. Grafström J. Lundberg J. Nikkhou-Aski S. Little P. Damberg P. Mitsios N. Mulder J. Lu L. Söderman M. Stone-Elander S. Holmin S. 2015. Imaging of a clinically relevant stroke model: glucose hypermetabolism revisited. Stroke; 46:835-842 * These authors contributed equally to this work † Cheng Q. Wållberg H. Johansson K. Ahlzén-Martinsson HS. Arnér ESJ. Lindberg H. Fleetwood F. Löfblom J. Ståhl S. Lu L. Grafström J. Thorell JO. Samén E. Stone-Elander S. Hägg M. Linder S. Nilsson S.

Kinetics of protein-based in vivo Imaging tracers for positron emission tomography

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Kinetics of protein-based in vivo Imaging tracers for positron emission tomography