Simultaneous attenuation and scatter correction of PET data in the image: quantitative and clinical assessment of image-to-image deep learning models.

Attenuation and scatter correction is crucial for quantitative positron emission tomography (PET) imaging. Direct attenuation correction (AC) in the image domain using deep learning approaches has been recently proposed for combined PET/MR and standalone PET modalities lacking transmission scanning devices or anatomical imaging. In this study, different input settings were considered in the model training to investigate deep learning-based AC in the image space. Three different deep learning methods were developed for direct AC in the image space: (i) use of non-attenuation-corrected PET images as input (NonAC-PET), (ii) use of attenuation-corrected PET images with a simple two-class AC map (composed of soft-tissue and background air) obtained from NonAC-PET images (PET segmentation-based AC [SegAC-PET]), and (iii) use of both NonAC-PET and SegAC-PET images in a Double-Channel fashion to predict ground truth attenuation corrected PET images with Computed Tomography images (CTAC-PET). Since a simple two-class AC map (generated from NonAC-PET images) can easily be generated, this work assessed the added value of incorporating SegAC-PET images into direct AC in the image space. A 4-fold cross-validation scheme was adopted to train and evaluate the different models based using 80 brain 18 F-Fluorodeoxyglucose PET/CT images. The voxel-wise and region-wise accuracy of the models were examined via measuring the standardized uptake value (SUV) quantification bias in different regions of the brain. The overall root mean square error (RMSE) for the Double-Channel setting was 0.157±0.08 SUV in the whole brain region, while RMSEs of 0.214±0.07 and 0.189±0.14 SUV were observed in NonAC-PET and SegAC-PET models, respectively. A mean SUV bias of 0.01±0.26% was achieved by the Double-Channel model regarding the activity concentration in cerebellum region, as opposed to 0.08±0.28% and 0.05±0.28% SUV biases for the network that uniquely used NonAC-PET or SegAC-PET as input, respectively. SegAC-PET images with an SUV bias of -1.15±0.54%, served as a benchmark for clinically accepted errors. In general, the Double-Channel network, relying on both SegAC-PET and NonAC-PET images, outperformed the other AC models. Since the generation of two-class AC maps from non-AC PET images is straightforward, the current study investigated the potential added value of incorporating SegAC-PET images into a deep learning-based direct AC approach. Altogether, compared with models that use only NonAC-PET and SegAC-PET images, the Double-Channel deep learning network exhibited superior attenuation correction accuracy.

The lack of physically measured attenuation maps (μ-maps) for attenuation and scatter correction is an important technical challenge in brain-dedicated stand-alone positron emission tomography (PET) scanners. The accuracy of the calculated attenuation correction is limited by the nonuniformity of tissue composition due to pathologic conditions and the complex structure of facial bones. The aim of this study is to develop an accurate transmission-less attenuation correction method for amyloid-β (Aβ) brain PET studies. We investigated the validity of a deep convolutional neural network trained to produce a CT-derived μ-map (μ-CT) from simultaneously reconstructed activity and attenuation maps using the MLAA (maximum likelihood reconstruction of activity and attenuation) algorithm for Aβ brain PET. The performance of three different structures of U-net models (2D, 2.5D, and 3D) were compared. The U-net models generated less noisy and more uniform μ-maps than MLAA μ-maps. Among the three different U-net models, the patch-based 3D U-net model reduced noise and cross-talk artifacts more effectively. The Dice similarity coefficients between the μ-map generated using 3D U-net and μ-CT in bone and air segments were 0.83 and 0.67. All three U-net models showed better voxel-wise correlation of the μ-maps compared to MLAA. The patch-based 3D U-net model was the best. While the uptake value of MLAA yielded a high percentage error of 20% or more, the uptake value of 3D U-nets yielded the lowest percentage error within 5%. The proposed deep learning approach that requires no transmission data, anatomic image, or atlas/template for PET attenuation correction remarkably enhanced the quantitative accuracy of the simultaneously estimated MLAA μ-maps from Aβ brain PET.

Introduction: Single-Photon Emission Computed Tomography (SPECT) is used to measure and quantify radiopharmaceutical distribution within the body. The accuracy of quantification depends on acquisition parameters and reconstruction algorithms. Until recently, most SPECT images were constructed using Filtered Back Projection techniques with no attenuation or scatter corrections. The introduction of 3-D Iterative Reconstruction algorithms with the availability of both computed tomography (CT)-based attenuation correction and scatter correction may provide for more accurate measurement of radiotracer bio-distribution. The effect of attenuation and scatter corrections on accuracy of SPECT measurements is well researched. It has been suggested that the combination of CT-based attenuation correction and scatter correction can allow for more accurate quantification of radiopharmaceutical distribution in SPECT studies (Bushberg et al., 2012). However, The effect of respiratory induced cardiac motion on SPECT images acquired using higher resolution algorithms such 3-D iterative reconstruction with attenuation and scatter corrections has not been investigated. Aims: To investigate the quantitative accuracy of 3D iterative reconstruction algorithms in comparison to filtered back projection (FBP) methods implemented on cardiac SPECT/CT imaging with and without CT-attenuation and scatter corrections. Also to investigate the effects of respiratory induced cardiac motion on myocardium perfusion quantification. Lastly, to present a comparison of spatial resolution for FBP and ordered subset expectation maximization (OSEM) Flash 3D together with and without respiratory induced motion, and with and without attenuation and scatter correction. Methods: This study was performed on a Siemens Symbia T16 SPECT/CT system using clinical acquisition protocols. Respiratory induced cardiac motion was simulated by imaging a cardiac phantom insert whilst moving it using a respiratory motion motor inducing cyclical elliptical motion of the apex of the cardiac insert. Results: Our analyses revealed that the use of the Flash 3-D reconstruction algorithm without scatter or attenuation correction has improved Spatial Resolution by 30% relative to FBP. Reduction in Spatial Resolution due to respiratory induced motion was 12% and 38% for FBP and Flash 3-D respectively. The implementation of scatter correction has resulted in a reduction in resolution by up to 6%. The application of CT-based attenuation correction has resulted in 13% and 26% reduction in spatial resolution for SPECT images reconstructed using FBP and Flash 3-D algorithms respectively. Conclusion: We conclude that iterative reconstruction (Flash-3D) provides significant improvement in image spatial resolution, however as a result the effects of respiratory induced motion have become more evident and correction of this is required before the full potential of these algorithms can be realised for myocardial perfusion imaging. Attenuation and scatter correction can improve image contrast, but may have significant detrimental effect on spatial resolution.

In human emission tomography, an additional transmission scan (x-ray CT or external gamma-source) is often required to obtain accurate attenuation maps for attenuation correction (AC) and scatter correction (SC). These transmission-based correction methods have been translated to small animal imaging although the impact of photon interactions on the mouse/rat-reconstructed images is substantially less than that in human imaging. Considering the additional complexity in design and cost of these systems, the necessity of these correction methods is questionable for small animal emission tomography. In this study, we evaluate the requirement of these corrections for small animal positron emission tomography (PET) through Monte Carlo simulations of the Inveon PET scanner using various sizes of MOBY voxelized phantoms. The 3D sinogram data obtained from simulations were reconstructed in 6 different conditions: Accurate AC+SC, simple (water) AC+SC, accurate AC only, simple AC only, SC only and no correction (NC). Mean error% for 8 different ROIs and 6 different MOBY sizes were obtained against the accurate scatter and attenuation corrections (first on the list). In addition to simulations, real mouse data obtained from an Inveon PET scanner were analyzed using similar methods. Results from both simulation and real mouse data showed that attenuation correction based on solely emission data should be sufficient for imaging animals smaller than 4 cm diameter. For larger sizes, a scatter correction employing an additional transmission scan can also be included depending on the objective of the study.

Attenuation correction (AC) and scatter correction (SC) are problematic issues for animal positron emission tomography (PET). In this study, the effects of AC and SC were assessed using PET on a phantom and actual rat brain. Transmission (TX) was performed using 57Co for 15 min. After a 15 min TX scan, emission (EM) PET was performed in list mode for 1 h. To assess the effects of AC and SC, the spillover ratio (SOR) was measured using a rat-sized NEMA NU4 image-quality phantom; statistical parametric mapping (SPM) was performed to assess the effects of AC and SC in the rat brain using 18F-FDG (FDG). In addition, the binding potential (BP) was compared for 18F-FP-CIT (FP-CIT) PET. SPM was used to compare PET images to which AC and SC were applied, and BP was used for FP-CIT PET. The SORs of air and water decreased after AC and SC. SPM for FDG PET after AC showed a significant increase in FDG-measured activity in the cerebellum and occipital cortex. After AC/SC, a significant decrease in FDG-measured activity was observed in the frontal and temporal cortices. For FP-CIT PET of the rat brain, the BP decreased by 26% after AC because the FP-CIT uptake increased more in the cerebellum than in the striatum owing to AC. After AC and SC, the mean BP increased by 61%. AC and AC/SC were found to be necessary components of the artifact correction process for both FDG PET and FP-CIT PET of rat brains.

Reliable attenuation correction represents an essential component of the long chain of modules required for the reconstruction of artifact-free, quantitative brain positron emission tomography (PET) images. In this work we demonstrate the proof of principle of segmented magnetic resonance imaging (MRI)-guided attenuation and scatter corrections in three-dimensional (3D) brain PET. We have developed a method for attenuation correction based on registered T1-weighted MRI, eliminating the need of an additional transmission (TX) scan. The MR images were realigned to preliminary reconstructions of PET data using an automatic algorithm and then segmented by means of a fuzzy clustering technique which identifies tissues of significantly different density and composition. The voxels belonging to different regions were classified into air, skull, brain tissue and nasal sinuses. These voxels were then assigned theoretical tissue-dependent attenuation coefficients as reported in the ICRU 44 report followed by Gaussian smoothing and addition of a good statistics bed image. The MRI-derived attenuation map was then forward projected to generate attenuation correction factors (ACFs) to be used for correcting the emission (EM) data. The method was evaluated and validated on 10 patient data where TX and MRI brain images were available. Qualitative and quantitative assessment of differences between TX-guided and segmented MRI-guided 3D reconstructions were performed by visual assessment and by estimating parameters of clinical interest. The results indicated a small but noticeable improvement in image quality as a consequence of the reduction of noise propagation from TX into EM data. Considering the difficulties associated with preinjection TX-based attenuation correction and the limitations of current calculated attenuation correction, MRI-based attenuation correction in 3D brain PET would likely be the method of choice for the foreseeable future as a second best approach in a busy nuclear medicine center and could be applied to other functional brain imaging modalities such as SPECT.

In order to obtain an accurate and quantitative positron emission tomography (PET) image, emission data need to be corrected for random coincidences, photon attenuation and Compton scattering of photons in the tissue, and detector efficiency response or normalization. The accuracy of these corrections strongly affects the quality of the PET image. There is evidence that time-of-flight (TOF) PET reconstruction is less sensitive than non-TOF reconstruction to inconsistencies between emission data and corrections. The purpose of this study is to analyze and discuss such experimental evidence. In this work, inconsistent correction data (inconsistent normalization, absence of scatter correction and mismatched attenuation correction) are introduced in experimental phantom data. Both TOF and non-TOF reconstructed images are analyzed to examine the effect of flawed data. The behavior of TOF reconstruction in respiratory artifacts, a very common example of inconsistency in the data, is studied in patient images. TOF reconstruction is less sensitive to mismatched attenuation correction, erroneous normalization and poorly estimated scatter correction. Such robustness depends strongly on the time resolution of the TOF PET scanner. In particular, the robustness of TOF in the presence of attenuation correction inconsistencies is discussed, using a simulation of a simple model of respiratory artifacts. We expect new generations of PET scanners, with improved time resolution, to be less and less sensitive to poor quality normalization, scatter and attenuation corrections. This not only reduces artifacts in the PET image, but also opens the way to less stringent requirements for the quality of the CT image (reducing either the equipment cost or the dose to the patient), and for the normalization protocols (simplifying or shortening the normalization procedures). Moreover, TOF reconstruction can be beneficial in multimodalities such as PET/MR, where a direct attenuation measurement is not available and attenuation correction can only be approximated.

The AIM of this study was to evaluate the effect of scatter and attenuation correction in region of interest (ROI) analysis of brain perfusion single-photon emission tomography (SPECT), and to assess the influence of selecting the reference area on the calculation of lesion-to-reference count ratios. Data were collected from a brain phantom and ten patients with unilateral internal carotid artery stenosis. A simultaneous emission and transmission scan was performed after injecting 123I-iodoamphetamine. We reconstructed three SPECT images from common projection data: with scatter correction and nonuniform attenuation correction, with scatter correction and uniform attenuation correction, and with uniform attenuation correction applied to data without scatter correction. Regional count ratios were calculated by using four different reference areas (contralateral intact side, ipsilateral cerebellum, whole brain and hemisphere). Scatter correction improved the accuracy of measuring the count ratios in the phantom experiment. It also yielded marked difference in the count ratio in the clinical study when using the cerebellum, whole brain or hemisphere as the reference. Difference between nonuniform and uniform attenuation correction was not significant in the phantom and clinical studies except when the cerebellar reference was used. Calculation of the lesion-to-normal count ratios referring the same site in the contralateral hemisphere was not dependent on the use of scatter correction or transmission scan-based attenuation correction. Scatter correction was indispensable for accurate measurement in most of the ROI analyses. Nonuniform attenuation correction is not necessary when using the reference area other than the cerebellum.

Epidepride labelled with iodine-123 is a suitable probe for the in vivo imaging of striatal and extrastriatal dopamine D2 receptors using single-photon emission tomography (SPET). Recently, this molecule has also been labelled with carbon-11. The goal of this work was to develop a method allowing the in vivo quantification of radioactivity uptake in baboon brain using SPET and to validate it using positron emission tomography (PET). SPET studies were performed in Papio anubis baboons using 123I-epidepride. Emission and transmission measurements were acquired on a dual-headed system with variable head angulation and low-energy ultra-high resolution (LEUHR) collimation. The imaging protocol consisted of one transmission measurement (24 min, heads at 90 degrees), obtained with two sliding line sources of gadolinium-153 prior to injection of 0.21-0.46 GBq of 123I-epidepride, and 12 emission measurements starting 5 min post injection. For scatter correction (SC) we used a dual-window method adapted to 123I. Collimator blurring correction (CBC) was done by deconvolution in Fourier space and attenuation correction (AT) was applied on a preliminary (CBC) filtered back-projection reconstruction using 12 iterations of a preconditioned, regularized minimal residual algorithm. For each reconstruction, a calibration factor was derived from a uniform cylinder filled with a 123I solution of a known radioactivity concentration. Calibration and baboon images were systematically built with the same reconstruction parameters. Uncorrected (UNC) and (AT), (SC + AT) and (SC + CBC + AT) corrected images were compared. PET acquisitions using 0.11-0.44 GBq of 11C-epidepride were performed on the same baboons and used as a reference. The radioactive concentrations expressed in percent of the injected dose per 100 ml (% ID/100 ml) obtained after (SC + CBC + AT) in SPET are in good agreement with those obtained with PET and 11C-epidepride. A method for the in vivo absolute quantitation of 123I-epidepride uptake using SPET has been developed which can be directly applied to other 123I-labelled molecules used in the study of the dopamine system. Further work will consist in using PET to model the radioligand-receptor interactions and to derive a simplified model applicable in SPET.

This study assessed the impact of scatter and attenuation corrections on the estimated activity delivered to whole body and liver in five patients included in a radioimmunotherapy clinical trial. Before injection of the radiopharmaceutical, transmission images were acquired with the Transmission Attenuation Correction - Whole-body (SMVi-GEMS) prototype. Emission images were obtained in energy-indexed list mode at least four times after injection. 20% window and scatter-corrected images (Dual Energy Window-DEW and Triple Energy Window-TEW) were generated. Whole-body activity was calculated 1-h after injection (and compared with injected activity). Cumulated activities in whole body and liver were determined according to the geometric mean approach. The mean relative error made in estimations of whole-body activity at 1-h was 6.9+/-10.3% without corrections. Taking scatter into account led to underestimation, but reduced the influence of patient morphotype (-40.0+/-7.6% and -43.3+/-6.2% for DEW and TEW). Attenuation correction led to a large overestimation, whether used alone (155.2+/-39.0%) or associated with scatter correction (39.6+/-10.4% and 35.9+/-10.2% for DEW and TEW). Compared to the geometric mean alone, scatter correction led to a reduction of cumulated activities of around 45% for whole body and less than 30% for liver. Attenuation correction had a more marked impact, particularly for liver where estimated cumulated activity increased from 150 to 300%. Preliminary scatter correction limited the increase to 100% for DEW and 150% for TEW in liver and to 25% for both DEW and TEW in whole body. Although this would probably be different at the organ level, the calculation of whole-body activity without scatter and attenuation correction gave the lowest biases. But from a scientific point of view, this cannot be a satisfactory method. Attenuation correction has a greater impact than scatter correction. The association of both corrections is not sufficient to obtain accurate absolute quantification. Other factors limit planar quantification with iodine-131, notably auto-absorption of sources, septal penetration of high-energy photons through the collimator and superimposition of sources.

The aim of this study was to evaluate the effect of scatter and attenuation correction in region of interest (ROI) analysis in brain perfusion single-photon emission tomography (SPECT) and to assess the influence of selecting the reference area on semi-quantification. Ten normal subjects were enrolled and injected with 123I-iodoamphetamine to undergo simultaneous emission and transmission scanning for scatter and attenuation correction. We reconstructed three SPECT images from common projection data of each subject: with scatter correction and non-uniform attenuation correction, with scatter correction and uniform attenuation correction, and with uniform attenuation correction applied to data without scatter correction. A program for automated ROI drawing was used to set ROIs on various regions in brain images. Regional count ratios were compared in images with different correction procedures by using three different reference areas. The effect of the combination of scatter and attenuation correction was marked in the precentral, temporal, posterior, hippocampus and especially in the cerebellum. In contrast, it was not appreciable in the central and parietal areas. When using the cerebellar ROI as the reference, the count ratio varied widely depending on the correction procedures. On the other hand, the whole brain reference offered the least variation in the count ratio. The influence of photon scattering and attenuation was dependent on regions. Since the count in the cerebellar ROI is greatly affected by photon scattering and attenuation, nonuniform attenuation correction combined with scatter correction deserves consideration when using the cerebellar ROI as the reference.

Purpose: Small animal microSPECT is an important pre‐clinical imaging modality. However, the quantitative accuracy is limited by photon attenuation in the subject and scatter in the subject and the collimator. In this study we investigate correcting for both scatter and attenuation in the reconstruction of a small animal sized phantom. Methods: A phantom consisting of a cold centre surrounded by a hot shell, surrounded by an outer layer of either water or air, was scanned in a multiplexing multi‐pinhole (MMP) SPECT scanner. Scan parameters were as follows: 9 pinholes/detector, 2.5 mm diameter; 48 projections; helical scan; 3 minutes per projection. Projection data was recorded for two energy windows, one centered at the photopeak (140 keV) and a second window below the photopeak centered at 110 keV. The phantom was also scanned with the built‐in CT scanner (45 keV, cone beam) and reconstructed using filtered backprojection. The SPECT data were reconstructed using an iterative ordered subsets expectation maximization (OSEM) algorithm with no correction, attenuation correction (AC) only, and both scatter (SC) and AC. Attenuation was estimated from the CT and incorporated into the system matrix as part of the reconstruction. Scatter was estimated using the dual energy window method and subtracted from the projections prior to reconstruction. Absolute quantification was derived from a scan of a point source with known activity. Results: With attenuation and scatter correction, the measured activity concentrations in the hot region of the phantom were within 12% of the true value with the external chamber of the phantom both full and empty. Scatter correction in addition to AC improves the accuracy over AC alone in the cold regions. Conclusions: Attenuation correction significantly reduces the subject‐size dependence of the quantitative accuracy in small‐animal MMP SPECT. Scatter correction may provide some additional benefit.Heart and Stroke Foundation of Ontario (NA6374) National Science and Engineering Research Council of Canada (PGS D)

The purpose was to provide apractical and effective method for performing reliable 90Y dosimetry based on 99mTc-MAA and SPEC/CT. The impact of scatter correction (SC) and attenuation correction (AC) on the injected 90Y activity, lung shunt fraction (LSF) and the delivered dose to lung and liver compartments was investigated within the scope of the study. Eighteen eligible patients (F: 3, M: 15) were subjected to 90Y therapy. 99mTc-MAA (111-222 MBq) was injected into the targeted liver, followed by whole-body scan (WBS) with peak-window at 140 keV (15% width) and one down-scatter window. SPECT/CT scan was subsequently acquired encompassing lung and liver regions. The LSFs were fashioned from standard WBS LSFwb (St), scatter corrected WBS LSFwb (Sc), only scatter corrected SPECT LSFspect (NoAC-SC) and SPECT/CT with attenuation and scatter correction LSFspect (AC-SC). The absorbed doses that would be delivered to tumor and injected healthy liver were estimated using different calculation modes involving AC-SC (SPECT/CT), NoAC-SC (SPECT), NoAC-NoSC+LSFwb (SC), AC-SC + LSFwb (St), and NoAC-NoSC+LSFwb (St). The average deviations (range) in LSF values between standard LSFwb (St) and those from SPECT/CT (AC-SC), SPECT (NoAC-SC), and LSFwb (SC) were - 50% (- 29/- 71), - 32% (- 8/- 67), and - 45% (- 13/80), respectively. The suggested 90Y activity (GBq/Gy) was decreased within a range of 2-11%, 1-9%, and 2-7% by using LSFspect (AC-SC), LSFspect (NoAC-SC), and LSFwb (SC), respectively. Overall, two-sample t-test yielded no statistically significant difference (p < 0.05) in the absorbed doses to tumor and injected healthy liver between AC-SC (SPECT) and the rest of approaches with/and without AC and SC. However, a statistically significant difference (p < 0.05) was demonstrated in the lung shunt fractions and lung doses due to AC and SC. The LSFs from scatter corrected planar images LSFwb (SC) exhibited well agreement (R2 = 0.92) with SPECT/CT (AC-SC) and there was no statistically significant difference (Pvalue > 0.05) between both methods. It was deduced that SPECT/CT with attenuation and scatter correction plays a crucial role in the measurements of lung shunt fraction and dose as well as the total number of 90Y treatments. However, the absorbed dose to tumors and injected healthy liver was minimally affected by AC and SC. Besides, a good agreement was observed between LSF datasets from SPECT/CT versus scatter corrected WBS that can be alternatively and effectively used in 90Y dosimetry.

Dear Sir, We read with great interest the paper “Data acquisition and analysis: the strength of methodology in nuclear medicine and molecular imaging” by G. Lucignani [1]. The author nicely demonstrates the need for image quantification of positron emission tomography (PET) studies. Typically a PET acquisition consists of an emission scan and a transmission scan. Iterative reconstruction methods yield a better result compared with the filtered back projection method, especially in terms of noise. However, iterative reconstruction methods have a tendency to give rise to noise artefacts when a large number of iterations are performed. Image quality also depends greatly on how correction methods, such as attenuation and scatter correction, are applied, because these methods may introduce additional statistical noise into the reconstructed data sets. The complexity of different reconstruction methods, i.e. different correction methods, and the variation in scanner characteristics make it very difficult to compare the results between institutions. The effect of reconstruction on NEMA contrast values was demonstrated recently [2], and an interlaboratory comparison study of image quality using the NEMA NU 2-2001 procedure for assessment of image quality showed significant differences between different PET scanners [3]. The systematic difference in contrast entails two practical problems: visual image interpretation of scans may become more and more difficult and a systematic difference in measured SUVs may affect the diagnostic accuracy to be compared inter-institutionally. Using a common whole-body PET study and differing OSEM reconstruction parameters (number of iterations and subsets) of the emission data sets, we found no significant differences in the maximum SUV, but there were differences of up to 30% in the homogeneity of the liver. Of course, the SUV has an important clinical significance, but the homogeneity of a study is important for the clinician as well. Changing the reconstruction parameters of transmission data sets did not have any significant impact, because we used a segmented attenuation correction method. This has also been found to reduce the metal artefacts in PET-CT studies [4]. If the mathematical algorithm fails to perform an accurate attenuation correction, the image quality is degraded. Applying a phantom study by varying the transmission acquisition times (600, 300, 200, 100 or 20 s) and using Ge rods for attenuation correction, we observed sudden changes of up to 23% in homogeneity, but very minor differences in maximum SUV. Our preliminary findings show that in order to achieve comparable results of clinical studies from different institutions, the specification of both emission and transmission acquisition parameters has to be as detailed as possible. Eur J Nucl Med Mol Imaging (2007) 34:961–962 DOI 10.1007/s00259-007-0399-0

BackgroundNoninvasive multimodality imaging is essential for preclinical evaluation of the biodistribution and pharmacokinetics of radionuclide therapy and for monitoring tumor response. Imaging with nonstandard positron-emission tomography [PET] isotopes such as 124I is promising in that context but requires accurate activity quantification. The decay scheme of 124I implies an optimization of both acquisition settings and correction processing. The PET scanner investigated in this study was the Inveon PET/CT system dedicated to small animal imaging.MethodsThe noise equivalent count rate [NECR], the scatter fraction [SF], and the gamma-prompt fraction [GF] were used to determine the best acquisition parameters for mouse- and rat-sized phantoms filled with 124I. An image-quality phantom as specified by the National Electrical Manufacturers Association NU 4-2008 protocol was acquired and reconstructed with two-dimensional filtered back projection, 2D ordered-subset expectation maximization [2DOSEM], and 3DOSEM with maximum a posteriori [3DOSEM/MAP] algorithms, with and without attenuation correction, scatter correction, and gamma-prompt correction (weighted uniform distribution subtraction).ResultsOptimal energy windows were established for the rat phantom (390 to 550 keV) and the mouse phantom (400 to 590 keV) by combining the NECR, SF, and GF results. The coincidence time window had no significant impact regarding the NECR curve variation. Activity concentration of 124I measured in the uniform region of an image-quality phantom was underestimated by 9.9% for the 3DOSEM/MAP algorithm with attenuation and scatter corrections, and by 23% with the gamma-prompt correction. Attenuation, scatter, and gamma-prompt corrections decreased the residual signal in the cold insert.ConclusionsThe optimal energy windows were chosen with the NECR, SF, and GF evaluation. Nevertheless, an image quality and an activity quantification assessment were required to establish the most suitable reconstruction algorithm and corrections for 124I small animal imaging.