Annihilation density distribution calculations for medically important positron emitters

Palmer, Matthew R.; Brownell, G.L.

doi:10.1109/42.158941

Cited by 60 publications

(61 citation statements)

References 9 publications

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“…They achieved this in reference to the seminal work of Palmer and Brownell 91 wherein an analytic model of positron range was developed and shown to closely agree with experimental 92 as well as simulated 93 results. Specifically, for a given emitted positron energy E, the annihilation density D(r,E) was modeled as a 3D symmetric Gaussian with its standard deviation being a function of the density d, effective atomic weight A eff and atomic number Z eff of the medium.…”

Section: Iiib Positron Range Modelingmentioning

confidence: 99%

Resolution modeling in PET imaging: Theory, practice, benefits, and pitfalls

2013

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In this paper, the authors review the field of resolution modeling in positron emission tomography (PET) image reconstruction, also referred to as point-spread-function modeling. The review includes theoretical analysis of the resolution modeling framework as well as an overview of various approaches in the literature. It also discusses potential advantages gained via this approach, as discussed with reference to various metrics and tasks, including lesion detection observer studies. Furthermore, attention is paid to issues arising from this approach including the pervasive problem of edge artifacts, as well as explanation and potential remedies for this phenomenon. Furthermore, the authors emphasize limitations encountered in the context of quantitative PET imaging, wherein increased intervoxel correlations due to resolution modeling can lead to significant loss of precision (reproducibility) for small regions of interest, which can be a considerable pitfall depending on the task of interest.

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Section: Iiib Positron Range Modelingmentioning

confidence: 99%

Resolution modeling in PET imaging: Theory, practice, benefits, and pitfalls

2013

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“…A model for aPSF was proposed by Palmer and Brownell (1992) and by Palmer et al (2005). In those works, the aPSF for mono-energetic positrons (with energy E 0 < 4 MeV) in isotropic media was represented by a three-dimensional Gaussian.…”

Section: Positron Range Distributionsmentioning

confidence: 99%

“…There are several potential difficulties inherent to this approach (Levin and Hoffman 1999), such as the need to extrapolate range results from polyurethane to water or the possible loss of information due to the deconvolution. Palmer and Brownell (1992) evaluated annihilation density distributions for certain positron emitters through calculations based on beta-decay energy spectra combined with an empirical range formula, assuming that positrons behave diffusively. More recently, several authors have studied the reduction of positron range in presence of a magnetic field (Wirrwar et al 1997, Herzog et al 2010.…”

Section: Introductionmentioning

confidence: 99%

Positron range estimations with PeneloPET

Cal-González

Herraiz²,

España

et al. 2013

Phys. Med. Biol.

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Technical advances towards high resolution PET imaging try to overcome the inherent physical limitations to spatial resolution. Positrons travel in tissue until they annihilate into the two gamma photons detected. This range is the main detector-independent contribution to PET imaging blurring. To a large extent, it can be remedied during image reconstruction if accurate estimates of positron range are available. However, the existing estimates differ, and the comparison with the scarce experimental data available is not conclusive. In this work we present positron annihilation distributions obtained from Monte Carlo simulations with the PeneloPET simulation toolkit, for several common PET isotopes ( 18 F, 11 C, 13 N, 15 O, 68 Ga and 82 Rb) in different biological media (cortical bone, soft bone, skin, muscle striated, brain, water, adipose tissue and lung). We compare PeneloPET simulations against experimental data and other simulation results available in the literature. To this end the different positron range representations employed in the literature are related to each other by means of a new parameterization for positron range profiles. Our results are generally consistent with experiments and with most simulations previously reported with differences of less than 20% in the mean and maximum range values. From these results, we conclude that better experimental measurements are needed, especially to disentangle the effect of positronium formation in positron range. Finally, with the aid of PeneloPET, we confirm that scaling approaches can be used to obtain universal, material and isotope independent, positron range profiles, which would considerably simplify range correction.

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“…We used a modification of the SimSET simulation package to model the positron range of Na22 and F18 based on the Palmer and Brownell parameterized model [8]. Rather than following the positron trajectory until is reaches thermal energy [9], this model assumes that the equilibrium particle density resulting from a point source of monoenergetic positrons can be represented by a three-dimensional Gaussian distribution centered at the origin.…”

Section: Collimated Vs Non-collimatedmentioning

confidence: 99%

Measured Spatially Variant System Response for PET Image Reconstruction

Alessio

Kinahan

Harrison

et al.

IEEE Nuclear Science Symposium Conference Record, 2005

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Abstract-Quantitative accuracy in PET imaging is essential for longitudinal studies and monitoring tumor response to treatment. The goal of this work is to improve the quantitative accuracy of whole-body PET imaging through the use of an accurate, measured system model. Past empirically measured system response functions used line sources positioned at various locations in the imaging field of view. Here, we present a practical method for measuring the detector blurring component of a whole-body PET system with a non-collimated point source. We employ Monte Carlo simulations to show that a non-collimated point source is acceptable for modeling the radial blurring present in a PET tomograph. And, we justify the use of a Na22 point source for collecting these measurements. We measure the system response, simplify it to a two-dimensional function, and incorporate a parameterized version of this response into a modified OSEM algorithm. Reconstructions of measured data from an image quality and line source phantom reveal improved quantitative accuracy and resolution with the modified system model.

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Annihilation density distribution calculations for medically important positron emitters

Cited by 60 publications

References 9 publications

Resolution modeling in PET imaging: Theory, practice, benefits, and pitfalls

Resolution modeling in PET imaging: Theory, practice, benefits, and pitfalls

Positron range estimations with PeneloPET

Measured Spatially Variant System Response for PET Image Reconstruction

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