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It allows researchers to determine the quantity of injected particles successfully captured inside the magnetic field.

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Physics of pure and non-pure positron emitters for PET: a review and a discussion

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Particle Physics – Electron positron annihilation

E-mail newsletter. In this work, we focus on the aspects that could generate a viable PET signal. A few parameters can drive the use and success of a PET radioisotope:. Short or long half-life: the former is typically convenient for high-statistics PET scan of compounds that reach their target very quickly, like 15 O in brain studies or 18 F-FDG for oncology; the latter is used where the target is reached more slowly, as in 89 Zr-labeled or 64 Cu-labeled antibody imaging. Energy of the positron: the energy determines the range in the tissue.

Prompt gamma contamination: gammas emitted in decay cascades with the positron emission produce spurious coincidences, which blur the PET image and produce quantification errors, as in 76 Br, 86 Y, 82 Rb, and I. For the sake of simplicity, we will organize the radioisotopes in terms of pure positron emitter and prompt gamma positron emitters. A special class will be dedicated to 90 Y. A preliminary section is dedicated to a short review of the effect of positron range on spatial resolution and methods to correct for this effect. This implies a blurring of the source distribution and a consequent loss of spatial resolution [ 17 — 19 ].

The loss of spatial resolution, compared to short-range positron emitter such as 18 F, has been measured in high-resolution PET scanners for brain imaging and animal PET [ 20 , 21 ].

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Nevertheless, in the future, even whole-body PET, with improved spatial resolution, might require a mechanism to recover the loss of resolution associated with long positron range. An accurate characterization of the point spread function PSF allows for compensation of the loss in contrast recovery using calculated spill-over and partial volume corrections [ 23 ]. Methods to correct for positron range have been presented, as deblurring techniques [ 24 ] or incorporating positron range in the reconstruction itself [ 25 ].

Other researchers used the Monte Carlo simulation to estimate the distance between the source position and the detection line of response in the PET scanner and then incorporated this information in the reconstruction [ 19 , 26 ]. The increasing use of these long-positron-range radioisotopes will make methods for resolution recovery even more necessary. In addition, the long positron range of some of these radioisotopes can not only blur the primary radioisotope distribution but can also generate image artifacts. Properties of pure positron emission radioisotopes.

Range of positrons is in water [ 14 ]. The decay is The emitted positron has 0. The EC has a branching ratio of The rest 1. The isotopes 68 Ga, 76 Br, 82 Rb, 86 Y, and I have complex decay schemes with a variety of gammas in coincidences. Properties of prompt gamma positron emission radioisotopes. Only the positrons and prompt gammas with the two highest branching ratios are listed. This can constitute a small prompt gamma contamination in the PET data, if the 1.

The principal EC branches are to the ground level 8.

[] Positrons in Surface Physics

The rest of the EC 0. All gamma cascades can generate spurious coincidences: some prompt gammas have energy within the PET energy window. Some gammas have energy within the PET energy window. A fraction of the high-energy gammas could undergo Compton scatter in the tissue, and the scattered photons might enter the PET energy window.

PET data reconstruction is based on a two-step process: estimating the corrections to the data and image reconstruction itself. The data corrections are normalization individual detector sensitivity, sensitivity profile differences due to radial position of the source, and other factors relative to the scanner geometry , attenuation correction due to the interaction of emitted photons with the patient tissue , random correction accidental coincidence of uncorrelated photons at a high count rate , and scatter correction photons having a Compton interaction in the patient and therefore changing energy and direction.

Typically, all corrections assume that only two back-to-back keV photons from positron annihilation are involved: individual detector sensitivity is measured with keV photons, attenuation correction is measured with CT X-rays but is converted into a keV attenuation coefficient, and scatter is simulated or estimated based on single or multiple scatter simulations or models of interaction of keV photons. Randoms are usually estimated using a delayed window or from single models, measuring single count rates in detector.

Because of this, the random estimate does not include any assumption about the energy or the direction of the detected photons, and a random estimate method can work with any radioisotope. As we discussed in the previous section, also 11 C, 13 N, and 15 O are pure positron emitters. Because of the longer range of 13 N and 15 O, those radioisotopes might result in slightly blurred images or require positron range deblurring.

Spurious coincidences can be produced by prompt photons or high-energy photons generated during the decay of the injected radioisotope Fig. A prompt gamma can be detected because it has energy within or close to the PET energy window Fig. In this case, their energy must be over the threshold of 1. Also, in some decay modes, high-energy levels are populated via EC, and they decay to the ground level in cascade of two or more gammas. These cascades add to the background of spurious coincidences.

Finally, radioisotopes with a prompt gamma can generate not only coincidences between two photons but also triple coincidences, between two annihilation gammas and a prompt gamma. The different ratios of double and triple coincidences in pure beta emitter and non-pure beta emitter have been exploited as a method to differentiate radioisotopes in multiple-tracer imaging [ 12 , 13 ].

The contribution of the prompt gamma coincidences has a different spatial distribution when compared to the pure annihilation coincidences. This can be observed by looking at the radial profiles of sinograms obtained using the same phantom but with different radioisotopes.

The data, reprocessed for this article, were acquired during an experiment aimed to characterize PET scanner performance, and details are given in [ 22 ]. In Fig. Also, the tails of the sinograms quickly decrease. As expected, I has a large fraction of the coincidences that appear to have originated outside the phantom, a substantial contribution from prompt gamma coincidences. Radial net true sinogram profiles all angles added of a NEMA image quality phantom, filled with water solutions of several radioisotopes used for PET imaging: 68 Ga thick black line , 90 Y thin red line , I thick red line , and 11 C, 18 F, 64 Cu, and 89 Zr all in black dotted lines.

The profile is shown after normalization to maximum, a in linear scale and b log scale. In fact, 68 Ga has only 1. Nevertheless, it has been observed that if the 68 Ga activity is concentrated in a specific organ, and the scatter is evaluated away from the concentrated activity, this small background of the prompt gamma can create artifacts and generate scatter overestimate. In these occurrences, it has been recommended to use some prompt gamma correction even for 68 Ga [ 31 ]. The detection probability of the prompt gamma is reduced by the fact that only a small fraction of the 0.

In any case, a prompt gamma correction is absolutely necessary for 82 Rb. For both 82 Rb and 68 Ga, a uniform radial offset or a first-order polynomial well describe the prompt gamma, probably because the scattered detected gammas have quite a flat spatial distribution. The contribution of the prompt gamma becomes prevalent in I, where Moreover, some of the remaining In fact, we could roughly estimate the ratio of the prompt gamma over total coincidences in a sinogram.

This results in a ratio of the prompt gamma over total of about 0. A second-order polynomial seems a better fit for I, due to the concavity of the background. One possible explanation for this shape is the fact that the keV photons are directly detected into the energy window and the spatial distribution is dictated by the simple attenuation of the photons in the tissue [ 32 ].

Radial net true sinogram profiles all angles added of a NEMA image quality phantom, filled with water solutions of I. A second-order polynomial is used to fit the background: the I profile black line , the second-order polynomial fit red line , and the tail region used for the fit thick red dotted line are shown.

Finally, 76 Br and 86 Y are dominated by decay schemes with prompt gammas. Prompt gamma correction is absolutely necessary, since spurious coincidences are the majority of the coincidences for these radioisotopes. Standard scatter correction and random correction alone are not sufficient to obtain quantitative images in the presence of abundant spurious coincidences from prompt gammas. In the absence of proper correction, this results in high artifact background levels and consequent loss of contrast, or overestimation of the conventional scatter, with over subtraction in the central part of the body.

In order to mitigate the effect of the prompt gamma, it has been shown that a narrower energy window can effectively reduce the prompt gamma contamination in the data [ 33 ]. Moreover, it does reduce the sensitivity of the PET scanner to true coincidences. A new correction is needed, the prompt gamma correction PGC. In the past years, several methods have been proposed to estimate and subtract the prompt gamma component.

The first group of methods consists of estimating the prompt gamma background fitting the radial tails of the sinogram with a constant offset and first- or second-order polynomials. The offset due to prompt gammas can be evaluated and subtracted. Subtracting a simple uniform background has been shown to be effective even with 86 Y and I, which have abundant prompt gamma fraction [ 34 — 36 ].

A linear approximation of the background has been used successfully for 76 Br and proposed in general for all prompt gamma radioisotopes [ 37 — 39 ]. In order to better match the slightly concave shape of the background observed in 86 Y and I [ 34 ], a second-order polynomial fit to the tails has been proposed and tested on 86 Y [ 40 ]. A second approach is based on the observation that, for 82 Rb, the prompt gamma background has a similar radial distribution as the randoms [ 41 ]. The authors proposed a method that uses the scaled random estimate, added to the single scatter conventional estimate, to match the tails of the prompt sinogram.

The random scaling factor, obtained by fitting the tails, includes the prompt gamma contribution. This approach to prompt gamma correction was also used on I data, where the I image quality after PGC was comparable to that shown in a similar experiment with 18 F [ 42 ]. A third approach is based on a convolution of the estimate of the original activity with some kernel based on models that include prompt gamma generation. One option uses a spatially variant, attenuation-dependent kernel that has been analytically determined and is based upon a simplified model of the cascade-coincidence attenuation and detection process [ 43 ].

The model is based on the measured attenuation map of the patient. In this method, the emission sinogram is preliminarily corrected with the standard corrections, then convolved with the kernel, and the tails of the convolved sinogram and the measured sinogram are fitted to obtain a scaling factor for the convolution kernel. Then, the scaled kernel can be used for the final estimate of the prompt gamma correction.

This method has been tested with 76 Br and 86 Y data. Another group proposed a correction method for 86 Y, based on the convolution of the estimate of the original activity with a 86 Y point spread function kernel [ 44 ]. The resulting prompt gamma estimate is then normalized to counts outside the patient body, in order to obtain a more accurate correction. The method can be iterated. The 86 Y point spread function kernel was measured once with an elliptical phantom that simulates the abdomen.

Even with its limitation the point spread function is based on a phantom , the results are encouraging. A fourth approach is based on a simple attenuation model SAM for prompt gammas [ 32 ], analog to the single scatter model for single scatter simulation SSS [ 45 ]. This method assumes that the principal effect driving the spatial distribution of the prompt gamma coincidences in I is the simple attenuation of the 0. The attenuation probability, for each source position and each detector, is computed geometrically, based on the expected travel path in the patient.

As for the SSS, the original emission sinogram and the measured attenuation map of the patient are used to estimate a first approximation of the activity distribution. At each iteration, the attenuation of the prompt gammas is estimated via the new SAM method and the scatter of the annihilation photons via the conventional SSS. This method has shown excellent matching of the radial shape for I [ 32 ]. Finally, a possible but time-consuming solution is a full Monte Carlo simulation of the emission and interaction of all radiation in the prompt gamma radioisotopes.

GATE Monte Carlo simulation was successful for a complete simulation of non-pure radioisotopes, and it was used as a support for estimating suitable functions modeling the tails of the sinograms. In particular, a two-component correction was proposed with the aid of GATE simulations, a uniform background and a Gaussian function [ 47 , 48 ]. In this section, we will briefly discuss these effects. High-energy positrons, associated with ranges larger than a few millimeters, can escape the patient skin.

The positrons can travel in air and reach the PET scanner internal tunnel, where they annihilate and produce two keV gammas in coincidence, completely uncorrelated with the distribution of the radioisotope in the patient Fig. One can observe the presence of the copper shield, stopping the positrons that otherwise would travel in air and reach the internal tunnel of the PET scanner.

In the absence of the shielding, the spatial distribution of coincidence events is affected by the high-range positrons. In fact, similar effects have been observed in patient and phantom data, if I and 68 Ga are used [ 27 , 28 ]. The positrons escaping the phantom annihilate in the copper, which becomes a source of gamma pairs, and are visible in the image as a shell surrounding the phantom. The 68 Ge source was held in place in the center of the field of view by a polymer foam holder covering the bottom part of the tunnel.

The foam is unable to stop keV photons but can reduce the flux of positrons reaching the lower part of the tunnel Fig. At angle zero top view , the radial distribution is fully symmetrical. In fact, while this effect can be observed in phantoms, in patients, it might be very negligible. If the tracer is less specific and abundantly reaches the patient skin, this effect can appear.

In addition, sources of radioactivity completely independent of the patient can generate a background radiation: for example, in LSO- or LYSO-based PET scanners, a small background of Lu radiation can be seen when the PET signal in the patient is extremely low, as in 90 Y imaging. LSO contains 2. This is a small but not negligible background for some applications at a very low count rate, such as with 90 Y imaging.