Search

PET with (18)F-FDG has been increasingly applied, predominantly in the research setting, to study drug effects and pulmonary biology and to monitor disease progression and treatment outcomes in lung diseases that interfere with gas exchange through alterations of the pulmonary parenchyma, airways, or vasculature. To date, however, there are no widely accepted standard acquisition protocols or imaging data analysis methods for pulmonary (18)F-FDG PET/CT in these diseases, resulting in disparate approaches. Hence, comparison of data across the literature is challenging. To help harmonize the acquisition and analysis and promote reproducibility, we collated details of acquisition protocols and analysis methods from 7 PET centers. From this information and our discussions, we reached the consensus recommendations given here on patient preparation, choice of dynamic versus static imaging, image reconstruction, and image analysis reporting.

Blood-based kinetic analysis of PET data relies on an accurate estimate of the arterial plasma input function (PIF). An alternative to invasive measurements from arterial sampling is an image-derived input function (IDIF). However, an IDIF provides the whole blood radioactivity concentration, rather than the required free tracer radioactivity concentration in plasma. To estimate the tracer PIF, we corrected an IDIF from the carotid artery with estimates of plasma parent fraction (PF) and plasma-to-whole blood (PWB) ratio obtained from five venous samples. We compared the combined IDIF+venous approach to gold standard data from arterial sampling in 10 healthy volunteers undergoing [18F]GE-179 brain PET imaging of the NMDA receptor. Arterial and venous PF and PWB ratio estimates determined from 7 patients with traumatic brain injury (TBI) were also compared to assess the potential effect of medication. There was high agreement between areas under the curves of the estimates of PF (r = 0.99, p

In nuclear medicine all studies are dynamic. This may seem like a controversial statement as most studies performed in nuclear medicine departments consist of a single static scan. However, even in this case, the temporal dimension plays an important role in terms of the time point for the scan after administration of the tracer as well as its length.

Blood-based kinetic analysis of PET data relies on an accurate estimate of the arterial plasma input function (PIF). An alternative to invasive measurements from arterial sampling is an image-derived input function (IDIF). However, an IDIF provides the whole blood radioactivity concentration, rather than the required free tracer radioactivity concentration in plasma. To estimate the tracer PIF, we corrected an IDIF from the carotid artery with estimates of plasma parent fraction (PF) and plasma-to-whole blood (PWB) ratio obtained from five venous samples. We compared the combined IDIF+venous approach to gold standard data from arterial sampling in 10 healthy volunteers undergoing [

The estimation of the Depth-of-Interaction (DOI) of detected gamma photons is especially challenging for thick scintillators, yet relevant for moderately thin ones (8 mm CsI(Tl) in our case) employed in nuclear imaging. In SPECT, in particular using pinhole or slit-slat collimation, the parallax error produced by photons passing through the collimator holes, with trajectories non orthogonal to the crystal surface, can be reduced by including the DOI information into the tomographic reconstruction. We present an algorithm based on maximum likelihood that classifies into 4 layers the events absorbed in the scintillator. A novel initialization signal (a ring footprint surrounding the channel detecting the highest intensity) is proposed, only requiring a flood field irradiation as training. The algorithm is experimentally validated by means of a tilted collimated beam on a single camera. The DOI information will be applied in a stationary clinical MRI-compatible SPECT insert which is composed of 20 identical modules mounted in a partial ring.

In the context of the INSERT project, we have been developing a clinical single photon emission computed tomography (SPECT) insert for a magnetic resonance imaging (MRI) system, in order to perform simultaneous SPECT/MRI of the human brain. This system will consist of 20 CsI:Tl scintillation detectors, 5-cm wide and 10-cm long, with a 72-channel silicon photomultiplier (SiPM) readout per detector, and a multimini slit-slat (MSS) collimator set up in a stationary partial ring. Additionally the system has a custom-built transmit/receive MR coil to ensure compatibility with the SPECT system. Due to the novel design of the system/collimator, existing geometric calibration methods are not suitable. Therefore we propose a novel and practical calibration procedure that consists of a set of specific independent measurements to determine the geometric parameters of the collimator. This procedure was developed utilizing a prototype system that consists of a reduced-size single detector with a 36-channel SiPM-based readout and a single MSS collimator module. Validation was performed by reconstructing different imaging phantoms, using a rotating stage to simulate a tomographic acquisition. Regarding uniformity, the coefficient of variation (COV) for the cylinder phantom reconstructed with correct calibration parameters is 6.7%, whereas the COV using incorrect parameters is 9.4%. The quality of the phantom reconstructions provide evidence of the applicability of the proposed method to the calibration of the prototype system. This procedure can be easily adapted for the final INSERT system.

In this article, we describe recent developments in the design of both single-photon emission computed tomography (SPECT) and positron emission tomography (PET) instrumentation that have led to the current range of superior performance instruments. The adoption of solid-state technology for either complete detectors [e.g., cadmium zinc telluride (CZT)] or read-out systems that replace photomultiplier tubes [avalanche photodiodes (APD) or silicon photomultipliers (SiPM)] provide the advantage of compact technology, enabling flexible system design. In SPECT, CZT is well suited to multi-radionuclide and kinetic studies. For PET, SiPM technology provides MR compatibility and superior time-of-flight resolution, resulting in improved signal-to-noise ratio. Similar SiPM technology has also been used in the construction of the first SPECT insert for clinical brain SPECT/MRI.

We present a standalone, scalable and high-throughput software platform for PET image reconstruction and analysis. We focus on high fidelity modelling of the acquisition processes to provide high accuracy and precision quantitative imaging, especially for large axial field of view scanners. All the core routines are implemented using parallel computing available from within the Python package NiftyPET, enabling easy access, manipulation and visualisation of data at any processing stage. The pipeline of the platform starts from MR and raw PET input data and is divided into the following processing stages: (1) list-mode data processing; (2) accurate attenuation coefficient map generation; (3) detector normalisation; (4) exact forward and back projection between sinogram and image space; (5) estimation of reduced-variance random events; (6) high accuracy fully 3D estimation of scatter events; (7) voxel-based partial volume correction; (8) region- and voxellevel image analysis. We demonstrate the advantages of this platform using an amyloid brain scan where all the processing is executed from a single and uniform computational environment in Python. The high accuracy acquisition modelling is achieved through span-1 (no axial compression) ray tracing for true, random and scatter events. Furthermore, the platform offers uncertainty estimation of any image derived statistic to facilitate robust tracking of subtle physiological changes in longitudinal studies. The platform also supports the development of new reconstruction and analysis algorithms through restricting the axial field of view to any set of rings covering a region of interest and thus performing fully 3D reconstruction and corrections using real data significantly faster. All the software is available as open source with the accompanying wiki-page and test data.

Idiopathic pulmonary fibrosis (IPF) is a chronic fibrosing lung disease, with an incidence of ~1/10,000 per year, and a poor prognosis with limited treatments [1]. The role of hypoxia in disease progression is unclear. Footnotes This manuscript has recently been accepted for publication in the European Respiratory Journal . It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJ online. Please open or download the PDF to view this article. Conflict of interest: Dr. Porter has nothing to disclose. Conflict of interest: Dr. Win has nothing to disclose. Conflict of interest: Dr. Erlandsson has nothing to disclose. Conflict of interest: Dr. Fraioli has nothing to disclose. Conflict of interest: Dr. Rashidnasab has nothing to disclose. Conflict of interest: Dr. Holman has nothing to disclose. Conflict of interest: Dr. Ganeshan has nothing to disclose. Conflict of interest: Dr. Screaton has nothing to disclose. Conflict of interest: Dr. Maher has nothing to disclose. Conflict of interest: Mr. Endozo has nothing to disclose. Conflict of interest: Mr. Hoath has nothing to disclose. Conflict of interest: Mr. Shortman has nothing to disclose. Conflict of interest: Dr. Emond has nothing to disclose. Conflict of interest: Prof. Thielemans has nothing to disclose. Conflict of interest: Prof. Hutton has nothing to disclose. Conflict of interest: Dr. Lukey has nothing to disclose. Conflict of interest: Dr. Aigbirhio has nothing to disclose. Conflict of interest: Mr. Khan has nothing to disclose. Conflict of interest: Dr. Robriguez-Justo has nothing to disclose. Conflict of interest: Prof. Groves has nothing to disclose.

The development of the first clinical simultaneous Single Photon Emission Computed Tomography (SPECT) and Magnetic Resonance Imaging (MRI) system was carried out within the INSERT project. The INSERT scanner was constructed under the initial project, but its performance was not fully evaluated; here we have reconstructed the first images on the SPECT system. Calibration and acquisition protocols were developed and used to establish the clinical feasibility of the system. The image reconstruction procedures were implemented on the first phantom images in order to assess the system's imaging capabilities. This study solved issues involving incomplete data sets and pixel failure in the prototype detector system. The final images determined a measure of trans-axial image resolution, giving average values of 9.14 mm and 6.75 mm in the radial and tangential directions respectively. The work carried out on the complete system produced several clinical phantom images which utilized the capabilities of both SPECT and MRI.

In addition to static tracer uptake values used routinely in clinical facilities, PET imaging can provide useful information on tracer kinetics via the use of dynamic acquisitions where a set of time frames are acquired starting from the injection/inhalation of the radiotracer. In lung studies, kinetic parameters, estimated from compartmental modelling, are however affected by respiratory motion. When only one attenuation image is available, most existing motion compensation strategies are not appropriate for the initial short time frames, especially as the activity distribution changes rapidly over the early part of the dynamic acquisition. This work presents a preliminary study to handle respiratory motion using a two-step process that uses gated dynamic data as input. We first use joint reconstruction of activity and motion on the entire gated PET data to estimate deformation fields. This allows the subsequent reconstruction of each time frame separately with motion compensation. We present results comparing on one hand the compartment model fit residuals with and without respiratory motion compensation and on the other hand the diaphragm position in non-attenuation corrected images and from this method.

A preclinical insert for small animal simultaneous SPECT and MR imaging, in particular for imaging mouse brains, is presented. It consists of ten static magnetic resonance imaging (MRI)-compatible gamma cameras based on tiles of silicon photomultipliers readout by a multichannel ASIC and coupled to 5 cm $\boldsymbol \times $ 5 cm CsI(Tl) scintillators and to an MRI-compatible multipinhole collimator. Calibration and image reconstruction algorithm are illustrated. Mutual compatibility is demonstrated along with imaging performance that is comparable with other non-MR micro-SPECT systems: 0.9 mm tomographic spatial resolution across a transverse field of view of 15.6 mm, 12% energy resolution (at 140 keV), and 1105 cps/MBq sensitivity. Experimental results with phantoms (glass capillaries of 290 $ \mu \text{m}$ diameter and a mini Derenzo) are presented.

The first SiPM-based clinical SPECT ring for brain simultaneous imaging in standard MR scanners has been put into operation. Reliable operation of the instrument has been achieved by means of its optimization, such as the introduction of a dual-cooling system (liquid-gas) of the DAQ electronics. The static gantry is composed of 20 MRI-compatible γ-detection modules mounting 5 cm × 10 cm CsI(Tl) scintillators for a total of 1440 pixels (targeting a transaxial FoV of 20 cm). Here we present the results of a preliminary characterization showing 220 kcps max. count rate, 365cps/MBq sensitivity with the multislit-slat collimator, ~17% energy resolution and an average extrinsic spatial resolution of ~8 mm in the trans-axial plane.

The initial characterization of the first single-photon emission computed tomography (SPECT) insert for simultaneous human brain imaging inside magnetic resonance imaging (MRI) is presented. The instrument features a novel multimini-slit-slat collimator and a static ring of 20 detectors. The scanner architecture is modular and represents the scale-up of a preclinical version whose MRI-compatibility has been already successfully demonstrated. The detectors are based on CsI(Tl) crystals (50 mm $\times $ 100 mm $\times $ 8 mm) coupled to arrays of silicon photomultipliers and ASIC readout for a total of 1440 channels. The transaxial field of view (FoV) is 20 cm by 9 cm in the axial direction. The experimental results show a sensitivity of 362 cps/MBq, an energy resolution of ~17% (at 140 keV), and a tomographic extrinsic resolution in the transaxial plane of ~8 mm across the whole FoV.

Partial volume effects are caused by the limited spatial resolution of the PET system. There is increasing evidence that partial volume correction (PVC) is necessary to guarantee quantitative accuracy in PET; however, there is reluctance to apply PVC routinely in clinical practice, partly because of uncertainty regarding the method of choice. To perform accurate PVC, it is necessary to introduce information from high-resolution anatomic images, such as MR imaging. All the methods rely on accurate coregistration between the anatomic image and the PET image. PET/MR imaging offers clear advantages for PVC and can help alleviate the image registration issues.

Motion correction has been added to a PET-MR reconstruction tool, SIRF, by incorporating a registration package, NiftyReg. New functionality has been demonstrated in the context of estimating kinetic parameters in the left temporal lobe, comparing direct and indirect reconstructions and evaluating the impact of using motion correction.Principal component analysis was used to detect motion and to determine time frames, while STIR’s parametric-OSEM was used to perform the motion-corrected direct parametric reconstruction.It was found that the variance in the left temporal lobe decreased when motion correction was performed, and the same was true of direct reconstructions compared to indirect.With SIRF, the entirety of the demonstrated functionality can be performed from a single Matlab or Python script.

Introduction Amyloid-specific PET tracers provide quantitative measurements for determining amyloid load in vivo. Many cutpoints have been proposed to define amyloid positivity; those based on post-mortem pathology are highly specific, but may not be sensitive to the initial signs of amyloid deposition. Cutpoints are also highly dependent on many analytical issues including: region of interest (ROI), reference region, partial volume correction, and the statistical criteria for choosing the cutpoint. In the absence of CT scanning, quantifying amyloid load with combined PET/MR scanners requires novel techniques for attenuation correction. We examined these aspects in a large UK sample of individuals born in the same week in 1946, all scanned on the same PET/MR scanner. Methods PET and MR data were acquired on 250 participants enrolled in Insight 1946, a sub-study of the MRC National Survey of Health and Development (NSHD). Scanning was performed on a Siemens Biograph PET-MR scanner using 18F-florbetapir. PET images were reconstructed from 50 to 60 minutes post-injection using two different attenuation correction techniques: an ultrashort echo time (UTE) and a pseudo CT (pCT) method. Volumetric T1 MR data were parcellated into ROIs and co-registered to PET to compute standard uptake value ratios (SUVR) against four commonly used reference regions, with and without partial volume correction. Cutpoints for amyloid positivity were created by fitting Gaussian mixture models (with 1 to 3 clusters) and using the 99th percentile of the Gaussian representing the amyloid negative population. Results 240 participants with suitable T1 and amyloid PET data were included in the analysis. The mixture modelling for cortical ROIs typically resulted in 2 clusters, confirming the expected bimodal distribution of amyloid deposition. Across the different reference regions, the rate of amyloid positive individuals was consistently 15 – 18% without PVC correction and 19-23% with PVC correction (Table). Precuneus and posterior cingulate SUVRs classified slightly more participants as amyloid positive, while those based on occipital lobe were much lower (Figure). Subcortical ROIs provided inconsistent evidence of bimodal distributions. Discussion Quantification of SUVR based measures of amyloid load using data acquired on PET/MR produces consistent rates of amyloid positivity across a variety of analysis options.

A clinical SPECT insert for a commercial MRI scanner has been developed within the INSERT project, allowing simultaneous SPECT/MRI studies of the human brain. Here we present preliminary experimental results. The reconstructed resolution was 6-11 mm and the sensitivity 280-440 s-1/MBq. The INSERT is the first clinical SPECT prototype for simultaneous SPECT/MRI.

Simultaneous PET–MR acquisition reduces the possibility of registration mismatch between the two modalities. This facilitates the application of techniques, either during reconstruction or post-reconstruction, that aim to improve the PET resolution by utilising structural information provided by MR. However, in order to validate such methods for brain PET–MR studies it is desirable to evaluate the performance using data where the ground truth is known. In this work, we present a framework for the production of datasets where simulations of both the PET and MR, based on real data, are generated such that reconstruction and post-reconstruction approaches can be fairly compared.

Many partial volume correction approaches make use of anatomical information, readily available in PET/MRI systems but it is not clear what approach is best. Seven novel approaches to partial volume correction were evaluated, including several post-reconstruction methods and several reconstruction methods that incorporate anatomical information. These were compared with an MRI-independent approach (reblurred van Cittert ) and uncorrected data. Monte Carlo PET data were generated for activity distributions representing both 18F FDG and amyloid tracer uptake. Post-reconstruction methods provided the best recovery with ideal segmentation but were particularly sensitive to mis-registration. Alternative approaches performed better in maintaining lesion contrast (unseen in MRI) with good noise control. These were also relatively insensitive to mis-registration errors. The choice of method will depend on the specific application and reliability of segmentation and registration algorithms.

Spill over of data between different regions in a PET image is known as the “partial volume effect” (PVE) and leads to errors in the quantification of local tracer concentration. PVE can be a confounding factor in clinical studies if the effect changes over time or between subjects, and it is then important to correct for PVE. Such a correction procedure is known as “partial volume correction” (PVC). Since the PVE depends on the spatial resolution of the PET images, some degree of compensation can be obtained using resolution recovery or deconvolution algorithms. However, these algorithms should not be considered as PVC algorithms, as they simply provide alternative bias vs. noise trade-off solutions from the same measured data. More accurate correction methods can be implemented by utilising high-resolution anatomical information from co-registered MRI or CT images, which would typically first be segmented into a number of regions. Different PVC methods have been developed, which are based on different assumptions. The corrected values should therefore be regarded as approximations of the true values. Also, the results are sensitive to errors in co-registration and segmentation of the anatomical images, as well as in the estimation of the system point spread function. Despite these limitations, the importance of PVC has been demonstrated in a number of clinical neurology, oncology and cardiology studies.

Positron emission tomography (PET) images are degraded by a phenomenon known as the partial volume effect (PVE). Approaches have been developed to reduce PVEs, typically through the utilisation of structural information provided by other imaging modalities such as MRI or CT. These methods, known as partial volume correction (PVC) techniques, reduce PVEs by compensating for the effects of the scanner resolution, thereby improving the quantitative accuracy. The PETPVC toolbox described in this paper comprises a suite of methods, both classic and more recent approaches, for the purposes of applying PVC to PET data. Eight core PVC techniques are available. These core methods can be combined to create a total of 22 different PVC techniques. Simulated brain PET data are used to demonstrate the utility of toolbox in idealised conditions, the effects of applying PVC with mismatched point-spread function (PSF) estimates and the potential of novel hybrid PVC methods to improve the quantification of lesions. All anatomy-based PVC techniques achieve complete recovery of the PET signal in cortical grey matter (GM) when performed in idealised conditions. Applying deconvolution-based approaches results in incomplete recovery due to premature termination of the iterative process. PVC techniques are sensitive to PSF mismatch, causing a bias of up to 16.7% in GM recovery when over-estimating the PSF by 3 mm. The recovery of both GM and a simulated lesion was improved by combining two PVC techniques together. The PETPVC toolbox has been written in C++, supports Windows, Mac and Linux operating systems, is open-source and publicly available.

In compact systems, precise measurement in the projection space may be compromised due to minification. The objective of this work is to investigate the impact of the magnification factor in a model-based calibration procedure. This has direct relevance to the geometrical calibration of the clinical INSERT camera. Projection data from three point sources were simulated for a single pinhole collimator with magnification and single pinhole and slit-slat collimators with minification, for 100 noise realizations and 3 count levels. Model-based calibration was performed to estimate geometric parameters and data corresponding to a Derenzo phantom were simulated and reconstructed with true and worst-case estimates for each collimator. Experimental projection data were acquired with an INSERT prototype camera and four 99mTc line sources in different locations within the FoV. The collimator-CoR distance was varied in order to obtain different minifications and model-based calibration was performed. The results from the simulations suggest that calibration is less robust when minification is present, with higher biased calibration parameters, which result in activity underestimation. For experimental data, estimated parameters improved with a higher magnification factor, in line with the simulation results. However, some inconsistencies in the results suggest that there is still room for improvements. To conclude, geometric calibration of SPECT systems is more sensitive to minification than magnification, which will impact image quality.

In the context of the development of a simultaneous SPECT/MRI system, we have previously proposed a multi-mini-slit-slat (MSS) collimator, with multiple sections of short slits in order to improve the angular sampling. The data can be reconstructed using a 3D reconstruction algorithm that models the collimator geometry. One drawback, however, is that the projection data obtained with this collimator are difficult to interpret visually. Also, calibration can be problematic, as each mini-slit only covers part of the object FoV. We have therefore developed an algorithm for transforming the MSS projection data into the traditional sinogram format. These sinograms consist of multiple thin tilted lines with gaps in between due to the lack of detector rotation in this system. The data can be reconstructed using standard parallel-beam algorithms, taking into account the fact that there are data missing. We have shown with simulations and measurements that the algorithm can transform complex data, consisting of multiple rough broken line segments, into simple sine-curves. This algorithm can be useful for interpreting the acquired MSS data, reconstructing images, and calibrating the system.

Investigations on the effect of normal healthy ageing on the muscarinic system have shown conflicting results. Also, in vivo determination of muscarinic receptor binding has been hampered by a lack of subtype selective ligands and differences in methods used for quantification of receptor densities. Recent in vitro and in vivo work with the muscarinic antagonist ( R , R )-I-QNB indicates this ligand has selectivity for m 1 and m 4 muscarinic receptor subtypes. Therefore, we used ( R , R )[ 123 I]-I-QNB and single photon emission tomography to study brain m 1 and m 4 muscarinic receptors in 25 healthy female subjects (11 younger subjects, age range 26–32 years and 14 older subjects, age range 57–82 years). Our aims were to ascertain the viability of tracer administration and imaging within the same day, and to evaluate whether normalization to whole brain, compared to normalization to cerebellum, could alter the clinical interpretation of results. Images were analyzed using the simplified reference tissue model and by two ratio methods: normalization to whole brain and normalization to cerebellum. Significant correlations were observed between kinetic analysis and normalization to cerebellum, but not to whole brain. Both the kinetic analysis and normalization to cerebellum showed age-related reductions in muscarinic binding in frontal, orbitofrontal, and parietal regions. Normalization to whole brain, however, failed to detect age-related changes in any region. Here we show that, for this radiotracer, normalizing to a region of negligible specific binding (cerebellum) significantly improves sensitivity when compared to global normalization.

Kinetic analysis of 18F-fluorodeoxyglucose positron emission tomography data requires an accurate knowledge the arterial input function. The gold standard method to measure the arterial input function requires collection of arterial blood samples and is an invasive method. Measuring an image derived input function is a non-invasive alternative but is challenging due to partial volume effects caused by the limited spatial resolution of the positron emission tomography scanners. In this work, a practical image derived input function extraction method is presented, which only requires segmentation of the carotid arteries from MR images. The simulation study results showed that at least 92% of the true intensity could be recovered after the partial volume correction. Results from 19 subjects showed that the mean cerebral metabolic rate of glucose calculated using arterial samples and partial volume corrected image derived input function were 26.9 and 25.4 mg/min/100 g, respectively, for the grey matter and 7.2 and 6.7 mg/min/100 g for the white matter. No significant difference in the estimated cerebral metabolic rate of glucose values was observed between arterial samples and corrected image derived input function (p > 0.12 for grey matter and white matter). Hence, the presented image derived input function extraction method can be a practical alternative to noninvasively analyze dynamic 18F-fluorodeoxyglucose data without the need for blood sampling.

In this paper we propose a segmented magnetic resonance imaging (MRI) prior-based maximum penalized likelihood deconvolution technique for positron emission tomography (PET) images. The model assumes the existence of activity classes that behave like a hidden Markov random field (MRF) driven by the segmented MRI. We utilize a mean field approximation to compute the likelihood of the MRF. We tested our method on both simulated and clinical data (brain PET) and compared our results with PET images corrected with the re-blurred Van Cittert (VC) algorithm, the simplified Guven (SG) algorithm and the region-based voxel-wise (RBV) technique. We demonstrated our algorithm outperforms the VC algorithm and outperforms SG and RBV corrections when the segmented MRI is inconsistent (e.g. mis-segmentation, lesions, etc) with the PET image.

Sprague Dawley rats (10/sex/group) were given a single intravenous (iv) dose of CUMI-101 to determine acute toxicity of CUMI-101 and radiation dosimetry estimations were conducted in baboons with [11C]CUMI-101. Intravenous administration of CUMI-101 did not produce overt biologically or toxicologically significant adverse effects except transient hypoactivity immediately after dose in the mid- and high-dose groups, which is not considered to be a dose-limiting toxic effect. No adverse effects were observed in the low-dose group. The no observed adverse effect level (NOAEL) is considered to be 44.05 µg/kg for a single iv dose administration in rats. The maximum tolerated dose (MTD) was estimated to be 881 µg/kg for a single iv dose administration. The Medical Internal Radiation Dose (MIRDOSE) estimates indicate the maximum permissible single-study dosage of [11C]CUMI-101 in humans is 52 mCi with testes and urinary bladder as the critical organ for males and females, respectively.

SPECT images suffer from poor spatial resolution, which leads to partial volume effects due to cross-talk between different anatomical regions. By utilising high-resolution structural images (CT or MRI) it is possible to compensate for these effects. Traditional partial volume correction (PVC) methods suffer from various limitations, such as correcting a single region only, returning only regional mean values, or assuming a stationary point spread function (PSF). We recently presented a novel method in which PVC was combined with the reconstruction process in order to take into account the distance dependent PSF in SPECT, which was based on filtered backprojection (FBP) reconstruction. We now present a new method based on the iterative OSEM algorithm, which has advantageous noise properties compared to FBP. We have applied this method to a series of 10 brain SPECT studies performed on healthy volunteers using the DATSCAN tracer. T1-weighted MRI images were co-registered to the SPECT data and segmented into 33 anatomical regions. The SPECT data were reconstructed using OSEM, and PVC was applied in the projection domain at each iteration. The correction factors were calculated by forward projection of a piece-wise constant image, generated from the segmented MRI. Images were also reconstructed using FBP and standard OSEM with and without resolution recovery (RR) for comparison. The images were evaluated in terms of striatal contrast and regional variability (CoV). The mean striatal contrast obtained with OSEM, OSEM-RR and OSEM-PVC relative to FBP were 1.04, 1.42 and 1.53, respectively, and the mean striatal CoV values are 1.05, 1.53, 1.07. Both OSEM-RR and OSEM-PVC results in images with significantly higher contrast as compared to FBP or OSEM, but OSEM-PVC avoids the increased regional variability of OSEM-RR due to improved structural definition.

We have previously shown with simulations that a gain in signal-to-noise ratio (SNR) can be obtained by using mixed multiplexed (MX) and non-MX data in a slit-slat SPECT system as compared to using non-MX data only. We have now developed a prototype slit-slat collimator for a conventional gamma camera in order to validate these simulation results. The prototype collimator consists of seven slits and multiple parallel slats. Image reconstruction is performed using a modified OSEM algorithm, which takes into account geometric sensitivity variations and attenuation, but not scatter or resolution effects. Here, we first describe the calibration of the system and then we present the experimental validation with phantom experiments. SPECT acquisitions using different geometric and anthropomorphic phantoms were performed with and without multiplexing. The results show that reconstruction of the MX projections with the non-MX-projections eliminates artefacts caused by multiplexing. SNR gains obtained using the mixed MX and non-MX configurations were in the range of 26% to 51% for different phantoms. The results were in agreement with our previously published simulation work, proving that combining MX and non-MX data can result in artefact-free reconstructed images with improved SNR.