Automatic estimation of detector radial position for contoured SPECT acquisition using CT images on a SPECT/CT system

An algorithm was developed to estimate noncircular orbit (NCO) single-photon emission computed tomography (SPECT) detector radius on a SPECT/CT imaging system using the CT images, for incorporation into collimator resolution modeling for iterative SPECT reconstruction. Simulated male abdominal (arms up), male head and neck (arms down) and female chest (arms down) anthropomorphic phantom, and ten patient, medium-energy SPECT/CT scans were acquired on a hybrid imaging system. The algorithm simulated inward SPECT detector radial motion and object contour detection at each projection angle, employing the calculated average CT image and a fixed Hounsfield unit (HU) threshold. Calculated radii were compared to the observed true radii, and optimal CT threshold values, corresponding to patient bed and clothing surfaces, were found to be between -970 and -950 HU. The algorithm was constrained by the 45 cm CT field-of-view (FOV), which limited the detected radii to < or = 22.5 cm and led to occasional radius underestimation in the case of object truncation by CT. Two methods incorporating the algorithm were implemented: physical model (PM) and best fit (BF). The PM method computed an offset that produced maximum overlap of calculated and true radii for the phantom scans, and applied that offset as a calculated-to-true radius transformation. For the BF method, the calculated-to-true radius transformation was based upon a linear regression between calculated and true radii. For the PM method, a fixed offset of +2.75 cm provided maximum calculated-to-true radius overlap for the phantom study, which accounted for the camera system's object contour detect sensor surface-to-detector face distance. For the BF method, a linear regression of true versus calculated radius from a reference patient scan was used as a calculated-to-true radius transform. Both methods were applied to ten patient scans. For -970 and -950 HU thresholds, the combined overall average root-mean-square (rms) error in radial position for eight patient scans without truncation were 3.37 cm (12.9%) for PM and 1.99 cm (8.6%) for BF, indicating BF is superior to PM in the absence of truncation. For two patient scans with truncation, the rms error was 3.24 cm (12.2%) for PM and 4.10 cm (18.2%) for BF. The slightly better performance of PM in the case of truncation is anomalous, due to FOV edge truncation artifacts in the CT reconstruction, and thus is suspect. The calculated NCO contour for a patient SPECT/CT scan was used with an iterative reconstruction algorithm that incorporated compensation for system resolution. The resulting image was qualitatively superior to the image obtained by reconstructing the data using the fixed radius stored by the scanner. The result was also superior to the image reconstructed using the iterative algorithm provided with the system, which does not incorporate resolution modeling. These results suggest that, under conditions of no or only mild lateral truncation of the CT scan, the algorithm is capable of providing radius estimates suitable for iterative SPECT reconstruction collimator geometric resolution modeling.     

Implementation of an iterative scatter correction, the influence of attenuation map quality and their effect on absolute quantitation in SPECT

We investigated the accuracy of qSPECT, a quantitative SPECT reconstruction algorithm we have developed which employs corrections for collimator blurring, photon attenuation and scatter, and provides images in units of absolute radiotracer concentrations (kBq cm(-3)). Using simulated and experimental phantom data with characteristics similar to clinical cardiac perfusion data, we studied the implementation of a scatter correction (SC) as part of an iterative reconstruction protocol. Additionally, with experimental phantom studies we examined the influence of CT-based attenuation maps, relative to those obtained from conventional SPECT transmission scans, on SCs and quantitation. Our results indicate that the qSPECT estimated scatter corrections did not change appreciably after the third iteration of the reconstruction. For the simulated data, qSPECT concentrations agreed with images reconstructed using ideal, scatter-free, simulated data to within 6%. For the experimental data, we observed small systematic differences in the scatter fractions for data using different combinations of SCs and attenuation maps. The SCs were found to be significantly influenced by errors in image coregistration. The reconstructed concentrations using CT-based corrections were more quantitatively accurate than those using attenuation maps from conventional SPECT transmission scans. However, segmenting the attenuation maps from SPECT transmission scans could provide sufficient accuracy for most applications.     

Joint optimization of collimator and reconstruction parameters in SPECT imaging for lesion quantification

Obtaining the best possible task performance using reconstructed SPECT images requires optimization of both the collimator and reconstruction parameters. The goal of this study is to determine how to perform this optimization, namely whether the collimator parameters can be optimized solely from projection data, or whether reconstruction parameters should also be considered. In order to answer this question, and to determine the optimal collimation, a digital phantom representing a human torso with 16 mm diameter hot lesions (activity ratio 8:1) was generated and used to simulate clinical SPECT studies with parallel-hole collimation. Two approaches to optimizing the SPECT system were then compared in a lesion quantification task: sequential optimization, where collimation was optimized on projection data using the Cramer–Rao bound, and joint optimization, which simultaneously optimized collimator and reconstruction parameters. For every condition, quantification performance in reconstructed images was evaluated using the root-mean-squared-error of 400 estimates of lesion activity. Compared to the joint-optimization approach, the sequential-optimization approach favoured a poorer resolution collimator, which, under some conditions, resulted in sub-optimal estimation performance. This implies that inclusion of the reconstruction parameters in the optimization procedure is important in obtaining the best possible task performance; in this study, this was achieved with a collimator resolution similar to that of a general-purpose (LEGP) collimator. This collimator was found to outperform the more commonly used high-resolution (LEHR) collimator, in agreement with other task-based studies, using both quantification and detection tasks.     

The cardiofocal collimator: a variable-focus collimator for cardiac SPECT

Investigators in nuclear medicine have long been in search of a practical method to increase the number of detected events in cardiac SPECT. A clinically practical method requires a simple data acquisition protocol, clinically acceptable reconstruction times, artifact levels near or below visual threshold, and the use of currently available cameras and computers. Towards this end, we have developed the Cardiofocal collimator, a variable-focus collimator for cardiac SPECT that increases the number of detected events from the heart by more than a factor of two compared to that of a parallel-hole collimator with equivalent resolution. In both the transverse and axial dimensions, the focusing is strongest at the centre of the collimator, and gradually relaxes to nearly parallel-hole collimation at the edge of the collimator. The variable-focus concept provides an increase in the number of counts from organs imaged near the centre of the collimator, where the heart will spend most of the time during a cardiac SPECT study, while adequately sampling enough of the background activity distribution to prevent truncation artifacts in the reconstructed images. Images are reconstructed in clinically acceptable times using a filtered backprojection reconstruction algorithm. The algorithm supports both full-scan (360 degrees) and short-scan (180 degrees plus the fan angle) acquisitions. The results of simulations and phantom studies are included to demonstrate the performance of the Cardiofocal collimator.     

Noise and signal decoupling in maximum-likelihood reconstructions and Metz filters for PET brain images

Images reconstructed with the maximum-likelihood-by-expectation-maximization (ML) algorithm have lower noise in some regions, particularly low count areas, compared with images reconstructed with filtered backprojection (FBP). The use of statistically correct noise model coupled with the positivity constraint in the ML algorithm provides this noise improvement, but whether this model confers a general advantage for ML over FBP with no noise model and any reconstruction filter, is unclear. We have studied the quantitative impact of the correct noise model in the ML algorithm applied to simulated and real PET fluoro-deoxyglucose (FDG) brain images, given a simplified but accurate reconstruction model with spatially invariant resolution. For FBP reconstruction, several Metz filters were chosen and images with different resolution were obtained depending on the order (1-400) of the Metz filters. Comparisons were made based on the mean Fourier spectra of the projection amplitudes, the noise-power spectra, and the mean region-of-interest signal and noise behaviour in the images. For images with resolution recovery beyond the intrinsic detector resolution, the noise increased significantly for FBP compared with ML. This indicates that in the process of signal recovery using ML, the noise is decoupled from the signal. Such noise decoupling is not possible for FBP. However, for image resolution equivalent to or less than the intrinsic detector resolution, FBP with Metz filters of various orders can achieve a performance similar to ML. The significance of the noise decoupling advantage in ML is dependent on the reconstructed image resolution required for specific imaging tasks.     

Noise characteristics for cone beam collimators: a comparison with parallel hole collimator

In order to evaluate the properties of a cone beam (CB) collimator and three-dimensional filtered backprojection algorithm, the noise characteristics of this collimator configuration were determined and comparisons with a parallel hole (PH) collimator were made. Noise characteristics were evaluated using two approaches: the first consisted of assessing the magnitude of local random fluctuations in the reconstructed images, and the second consisted of assessing the noise texture in these images in the frequency domain by evaluating the noise power spectrum. Data used for these measurements were simulated using Monte Carlo models of SPECT systems equipped with cone beam and parallel hole collimators. Finally, to compare experimentally a specially designed high resolution CB collimator with a high resolution (HRES) PH collimator, measurements of a physical phantom were performed. Results of our studies show better noise magnitude for CB collimators; however, for CB collimators with short focal lengths (40-60 cm) the shape of %RMS noise distributions differs from slice to slice.     

Gaussian prefiltering of 123I DAT SPECT images when using depth-independent resolution recovery

Previously we have investigated a depth-independent compensation for collimator detector response (CDR) included in the OSEM reconstruction, intended for SPECT images that have been corrected for scatter and septal penetration using convolution-based methods. In this work, the aim was to study how different filtering strategies affect contrast as a function of noise when using Gaussian smoothing filters in combination with the above-described CDR compensation. The evaluation was performed for (123)I dopamine transporter (DAT) SPECT images. Prefiltering with 2D Gaussian filter kernels, where the deterioration in resolution is included in the depth-independent CDR compensation, was compared to conventional postfiltering with 3D Gaussian filter kernels. Images reconstructed without filtering are also included in the comparison. It was found that there is little benefit in noise reduction when using CDR compensation. However, this variant of prefiltering gives consistently higher contrasts as a function of noise compared with the postfiltering alternative, and that could be of interest when using other types of filters with contrast improving properties.     

Assessment of the sources of error affecting the quantitative accuracy of SPECT imaging in small animals

Small animal SPECT imaging systems have multiple potential applications in biomedical research. Whereas SPECT data are commonly interpreted qualitatively in a clinical setting, the ability to accurately quantify measurements will increase the utility of the SPECT data for laboratory measurements involving small animals. In this work, we assess the effect of photon attenuation, scatter and partial volume errors on the quantitative accuracy of small animal SPECT measurements, first with Monte Carlo simulation and then confirmed with experimental measurements. The simulations modeled the imaging geometry of a commercially available small animal SPECT system. We simulated the imaging of a radioactive source within a cylinder of water, and reconstructed the projection data using iterative reconstruction algorithms. The size of the source and the size of the surrounding cylinder were varied to evaluate the effects of photon attenuation and scatter on quantitative accuracy. We found that photon attenuation can reduce the measured concentration of radioactivity in a volume of interest in the center of a rat-sized cylinder of water by up to 50% when imaging with iodine-125, and up to 25% when imaging with technetium-99m. When imaging with iodine-125, the scatter-to-primary ratio can reach up to approximately 30%, and can cause overestimation of the radioactivity concentration when reconstructing data with attenuation correction. We varied the size of the source to evaluate partial volume errors, which we found to be a strong function of the size of the volume of interest and the spatial resolution. These errors can result in large (>50%) changes in the measured amount of radioactivity. The simulation results were compared with and found to agree with experimental measurements. The inclusion of attenuation correction in the reconstruction algorithm improved quantitative accuracy. We also found that an improvement of the spatial resolution through the use of resolution recovery techniques (i.e. modeling the finite collimator spatial resolution in iterative reconstruction algorithms) can significantly reduce the partial volume errors.     

A performance study of 3D reconstruction algorithms for positron emission tomography

This paper investigates the statistical and systematic accuracy of five three-dimensional reconstruction algorithms for multi-ring PET scanners operated without septa: the reprojection method, the direct Fourier reconstruction, the FAVOR algorithm, and the single-slice and multi-slice rebinning algorithms. Simulated data of a uniform cylinder, of Gaussian sources, and of spherical sources are used to compare respectively the noise properties, the modulation transfer function, and the recovery coefficients of the algorithms. Brain scans reconstructed with the different algorithms are compared by calculating the linear regression of the mean values within regions of interest. The most significant observations are a slight loss of transaxial resolution with the reprojection algorithm in the external slices of the scanner, and increased noise in the images reconstructed using multi-slice rebinning.     

Monte Carlo simulations of clinical PET and SPECT scans: impact of the input data on the simulated images

Monte Carlo simulations of emission tomography have proven useful to assist detector design and optimize acquisition and processing protocols. The more realistic the simulations, the more straightforward the extrapolation of conclusions to clinical situations. In emission tomography, accurate numerical models of tomographs have been described and well validated under specific operating conditions (collimator, radionuclide, acquisition parameters, count rates, etc). When using these models under these operating conditions, the realism of simulations mostly depends on the activity distribution used as an input for the simulations. It has been proposed to derive the input activity distribution directly from reconstructed clinical images, so as to properly model the heterogeneity of the activity distribution between and within organs. However, reconstructed patient images include noise and have limited spatial resolution. In this study, we analyse the properties of the simulated images as a function of the properties of the reconstructed images used to define the input activity distributions in (18)F-FDG PET and (131)I SPECT simulations. The propagation through the simulation/reconstruction process of the noise and spatial resolution in the input activity distribution was studied using simulations. We found that the noise properties of the images reconstructed from the simulated data were almost independent of the noise in the input activity distribution. The spatial resolution in the images reconstructed from the simulations was slightly poorer than that in the input activity distribution. However, using high-noise but high-resolution patient images as an input activity distribution yielded reconstructed images that could not be distinguished from clinical images. These findings were confirmed by simulated highly realistic (131)I SPECT and (18)F-FDG PET images from patient data. In conclusion, we demonstrated that (131)I SPECT and (18)F-FDG PET images indistinguishable from real scans can be simulated using activity maps with spatial resolution higher than that used in routine clinical applications.     

Study of noise propagation and the effects of insufficient numbers of projection angles and detector samplings for iterative reconstruction using planar-integral data

A rotating slat collimator can be used to acquire planar-integral data. It achieves higher geometric efficiency than a parallel-hole collimator by accepting more photons, but the planar-integral data contain less tomographic information that may result in larger noise amplification in the reconstruction. Lodge evaluated the rotating slat system and the parallel-hole system based on noise behavior for an FBP reconstruction. Here, we evaluate the noise propagation properties of the two collimation systems for iterative reconstruction. We extend Huesman's noise propagation analysis of the line-integral system to the planar-integral case, and show that approximately 2.0(D/dp) SPECT angles, 2.5(D/dp) self-spinning angles at each detector position, and a 0.5dp detector sampling interval are required in order for the planar-integral data to be efficiently utilized. Here, D is the diameter of the object and dp is the linear dimension of the voxels that subdivide the object. The noise propagation behaviors of the two systems are then compared based on a least-square reconstruction using the ratio of the SNR in the image reconstructed using a planar-integral system to that reconstructed using a line-integral system. The ratio is found to be proportional to the square root of F/D, where F is a geometric efficiency factor. This result has been verified by computer simulations. It confirms that for an iterative reconstruction, the noise tradeoff of the two systems is not only dependent on the increase of the geometric efficiency afforded by the planar projection method, but also dependent on the size of the object. The planar-integral system works better for small objects, while the line-integral system performs better for large ones. This result is consistent with Lodge's results based on the FBP method.     

Non-iterative methods incorporating a priori source distribution and data information for suppression of image noise and artefacts in 3D SPECT

Non-iterative methods have been developed for image reconstruction in 3D SPECT with uniform attenuation and distance-dependent spatial resolution. It was observed that these methods can, in general, be susceptible to data noise and other errors, yielding conspicuous image artefacts. In this work, we developed and evaluated a regularized inverse-filtering approach for effective suppression of noise and artefacts in 3D SPECT images without significantly compromising image resolution. The proposed approach allows the incorporation of a priori random image field and data information and can thus robustly control the degree of suppression of noise and artefacts in 3D SPECT images. Using computer simulations, we evaluated and compared quantitatively images reconstructed from data sets of various noise levels by the use of the proposed methods and the existing non-iterative methods. These numerical results clearly demonstrated that the proposed regularized inverse-filtering approach can effectively suppress image noise and artefacts that plague the existing non-iterative methods, thus yielding quantitatively more accurate 3D SPECT images. The proposed regularized inverse-filtering approach can also be generalized to other imaging modalities.     

Experimental results from a prototype slit-slat collimator with mixed multiplexed and non-multiplexed data

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.     

Simultaneous technetium-99m/thallium-201 SPECT imaging with model-based compensation for cross-contaminating effects.

Simultaneous acquisition of dual-isotope SPECT data offers a number of advantages over separately acquired data; however, simultaneous acquisition can result in cross-contamination between isotopes. In this work we propose and evaluate two frameworks for iterative model-based compensation of cross-contamination in dual-isotope SPECT. The methods were applied to cardiac imaging with technetium-99m-sestamibi and thallium-201, and they were compared with a subtraction-based compensation method using a cross-talk estimate obtained from an auxiliary energy window. Monte Carlo simulations were performed to carefully study aspects of bias and noise for the methods, and a torso phantom with cardiac insert was used to evaluate the performance of the methods for experimentally acquired data. The cross-talk compensation methods substantially improved lesion contrast and significantly reduced quantitative errors for simultaneously acquired data. Thallium image normalized mean square error (NMSE) was reduced from 0.522 without cross-talk compensation to as low as 0.052 with model-based cross-talk compensation. This is compared with a NMSE of 0.091 for the subtraction-based compensation method. The application of a preliminary model for cross-talk arising from lead fluorescence x-rays and collimator scatter gave promising results, and the future development of a more accurate model for collimator interactions would probably benefit simultaneous Tc/Tl imaging. Model-based compensation methods provide feasible cross-talk compensation in clinically acceptable times, and they may ultimately make simultaneous dual-isotope protocols an effective alternative for many imaging procedures.     

An analytical reconstruction algorithm for multifocal converging-beam SPECT

Multifocal converging-beam collimation has been suggested for cardiac SPECT imaging to increase sensitivity over the heart without truncation of the activity distribution in the chest. In this study, an analytical reconstruction algorithm is derived for multifocal fan-beam and multifocal cone-beam tomography. In the algorithm, the projection data are differently weighted and filtered, depending on the distance from the detector. For a given image point, the set of filtered data corresponding to the distance between this point and detector is backprojected to determine the pixel value of the point. Thus, the backprojection is done only once at each projection view. To evaluate the algorithm, simulation studies are performed using a 3D Defrise slab phantom without considering photon attenuation and scatter, detector response, and statistical noise. Reconstructed images demonstrate that reasonable quality can be achieved with a modest focal-length variation rate and with a small radius of rotation. A collimator with a focal length increasing quickly near its centre provides better quality in the image region distant from the central plane of the cone geometry, but produces more severe artifacts at the centre of the reconstructed image, compared to a collimator with an initially slowly varying focal length.     

Direct reconstruction of single-photon emission computed tomography images using retained matrix elements

In clinical applications, two methods of single-photon emission computed tomography (SPECT) reconstruction are widely used. These are filtered backprojection and iterative reconstruction. Filtered backprojection is fast and produces acceptable images. Iterative reconstruction is slow, but produces images of greater accuracy than backprojection. The authors sought to develop a method of SPECT reconstruction that would have the advantages of both established methods: close in speed to backprojection and with the accuracy of iterative reconstruction. This was accomplished by computing a direct solution to the set of linear equations governing SPECT reconstruction. We tested this method of SPECT reconstruction using a set of projections from a cold rod and sphere phantom. Direct reconstruction produced images having equivalent resolution to backprojected images, but with double the contrast ratio. The direct method required 10 seconds of computation per slice on a Macintosh Quadra 950 (Apple Computer; Cupertin, CA), significantly faster than most iterative methods.     

Noise properties of the EM algorithm: II. Monte Carlo simulations

In an earlier paper we derived a theoretical formulation for estimating the statistical properties of images reconstructed using the iterative ML-EM algorithm. To gain insight into this complex problem, two levels of approximation were considered in the theory. These techniques revealed the dependence of the variance and covariance of the reconstructed image noise on the source distribution, imaging system transfer function, and iteration number. In this paper a Monte Carlo approach was taken to study the noise properties of the ML-EM algorithm and to test the predictions of the theory. The study also served to evaluate the approximations used in the theory. Simulated data from phantoms were used in the Monte Carlo experiments. The ML-EM statistical properties were calculated from sample averages of a large number of images with different noise realizations. The agreement between the more exact form of the theoretical formulation and the Monte Carlo formulation was better than 10% in most cases examined, and for many situations the agreement was within the expected error of the Monte Carlo experiments. Results from the studies provide valuable information about the noise characteristics of ML-EM reconstructed images. Furthermore, the studies demonstrate the power of the theoretical and Monte Carlo approaches for investigating noise properties of statistical reconstruction algorithms.     

MSCT轴向分辨力和图像噪声影响因素分析

目的:探讨多排螺旋CT（MSCT）轴向分辨力或断层灵敏度曲线（SSP）和图像噪声的影响因素。方法:使用临床常 用的腹部扫描模式,采用不同直径的模板,重建层厚、螺距、电压（kV）、重建算法等扫面参数,进行MSCT扫描,对不同参数 对断层图像SSP和图像噪声的影响进行统计学分析。结果:当螺距和准直器宽度保持不变,不同层厚和重建算法得到的 SSP的半高宽FWHM值基本保持不变（P>0.05）;当重建算法和准直器宽度保持不变,不同螺距和层厚得到的SSP的半高 宽FWHM值基本保持不变（P>0.05）;不同准直器宽度,同螺距和层厚得到的SSP 的半高宽FWHM值基本保持不变（P> 0.05）;随着层厚、mAs增加,图像噪声减小（P<0.05）;随着kV增加,图像噪声随之减小,不同重建算法下图像噪声存在明显 差异（P<0.05）。结论:卷积重建算法、螺距和准直器宽度对SSP的影响很小,螺距对图像噪声影响很小,而层厚、重建算 法、mAs、kV对图像噪声影响大。层厚、mAs、kV增大,图像噪声减小;重建算法分辨率越高,图像噪声越大。     

Comparing planar image quality of rotating slat and parallel hole collimation: influence of system modeling

The main remaining challenge for a gamma camera is to overcome the existing trade-off between collimator spatial resolution and system sensitivity. This problem, strongly limiting the performance of parallel hole collimated gamma cameras, can be overcome by applying new collimator designs such as rotating slat (RS) collimators which have a much higher photon collection efficiency. The drawback of a RS collimated gamma camera is that, even for obtaining planar images, image reconstruction is needed, resulting in noise accumulation. However, nowadays iterative reconstruction techniques with accurate system modeling can provide better image quality. Because the impact of this modeling on image quality differs from one system to another, an objective assessment of the image quality obtained with a RS collimator is needed in comparison to classical projection images obtained using a parallel hole (PH) collimator. In this paper, a comparative study of image quality, achieved with system modeling, is presented. RS data are reconstructed to planar images using maximum likelihood expectation maximization (MLEM) with an accurate Monte Carlo derived system matrix while PH projections are deconvolved using a Monte Carlo derived point-spread function. Contrast-to-noise characteristics are used to show image quality for cold and hot spots of varying size. Influence of the object size and contrast is investigated using the optimal contrast-to-noise ratio (CNR(o)). For a typical phantom setup, results show that cold spot imaging is slightly better for a PH collimator. For hot spot imaging, the CNR(o) of the RS images is found to increase with increasing lesion diameter and lesion contrast while it decreases when background dimensions become larger. Only for very large background dimensions in combination with low contrast lesions, the use of a PH collimator could be beneficial for hot spot imaging. In all other cases, the RS collimator scores better. Finally, the simulation of a planar bone scan on a RS collimator revealed a hot spot contrast improvement up to 54% compared to a classical PH bone scan.     

Design and performance of a multi-pinhole collimation device for small animal imaging with clinical SPECT and SPECT-CT scanners

A multi-pinhole collimation device is developed that uses the gamma camera detectors of a clinical SPECT or SPECT-CT scanner to produce high-resolution SPECT images. The device consists of a rotating cylindrical collimator having 22 tungsten pinholes with 0.9 mm diameter apertures and an animal bed inside the collimator that moves linearly to provide helical or ordered-subsets axial sampling. CT images also may be acquired on a SPECT-CT scanner for purposes of image co-registration and SPECT attenuation correction. The device is placed on the patient table of the scanner without attaching to the detectors or scanner gantry. The system geometry is calibrated in-place from point source data and is then used during image reconstruction. The SPECT imaging performance of the device is evaluated with test phantom scans. Spatial resolution from reconstructed point source images is measured to be 0.6 mm full width at half maximum or better. Micro-Derenzo phantom images demonstrate the ability to resolve 0.7 mm diameter rod patterns. The axial slabs of a Micro-Defrise phantom are visualized well. Collimator efficiency exceeds 0.05% at the center of the field of view, and images of a uniform phantom show acceptable uniformity and minimal artifact. The overall simplicity and relatively good imaging performance of the device make it an interesting low-cost alternative to dedicated small animal scanners.