Dirk Beque

Characterization of pinhole SPECT acquisition geometry

A method is presented to estimate the acquisition geometry of a pinhole single photon emission computed tomography (SPECT) camera with a circular detector orbit. This information is needed for the reconstruction of tomographic images. The calibration uses the point source projection locations of a tomographic acquisition of three point sources located at known distances from each other. It is shown that this simple phantom provides the necessary and sufficient information for the proposed calibration method. The knowledge of two of the distances between the point sources proves to be essential. The geometry is estimated by fitting analytically calculated projections to the measured ones, using a simple least squares Powell algorithm. Some mild a priori knowledge is used to constrain the solutions of the fit. Several of the geometrical parameters are however highly correlated. The effect of these correlations on the reconstructed images is evaluated in simulation studies and related to the estimation accuracy. The highly correlated detector tilt and electrical shift are shown to be the critical parameters for accurate image reconstruction. The performance of the algorithm is finally demonstrated by phantom measurements. The method is based on a single SPECT scan of a simple calibration phantom, executed immediately after the actual SPECT acquisition. The method is also applicable to cone-beam SPECT and X-ray CT.

Optimization of geometrical calibration in pinhole SPECT

Previously, we developed a method to determine the acquisition geometry of a pinhole camera. This information is needed for the correct reconstruction of pinhole single photon emission computed tomography images. The method uses a calibration phantom consisting of three point sources and their positions in the field of view (FOV) influence the accuracy of the geometry estimate. This work proposes two particular configurations of point sources with specific positions and orientations in the FOV for optimal image reconstruction accuracy. For the proposed calibration setups, inaccuracies of the geometry estimate due to noise in the calibration data, only cause subresolution inaccuracies in reconstructed images. The calibration method also uses a model of the point source configuration, which is only known with limited accuracy. The study demonstrates, however, that, with the proposed calibration setups, the error in reconstructed images is comparable to the error in the phantom model.

Comparison between MAP and postprocessed ML for image reconstruction in emission tomography when anatomical knowledge is available

Previously, the noise characteristics obtained with penalized-likelihood reconstruction [or maximum a posteriori (MAP)] have been compared to those obtained with postsmoothed maximum-likelihood (ML) reconstruction, for emission tomography applications requiring uniform resolution. It was found that penalized-likelihood reconstruction was not superior to postsmoothed ML. In this paper, a similar comparison is made, but now for applications where the noise suppression is tuned with anatomical information. It is assumed that limited but exact anatomical information is available. Two methods were compared. In the first method, the anatomical information is incorporated in the prior of a MAP-algorithm and is, therefore, imposed during MAP-reconstruction. The second method starts from an unconstrained ML-reconstruction, and imposes the anatomical information in a postprocessing step. The theoretical analysis was verified with simulations: small lesions were inserted in two different objects, and noisy PET data were produced and reconstructed with both methods. The resulting images were analyzed with bias-noise curves, and by computing the detection performance of the nonprewhitening observer and a channelized Hotelling observer. Our analysis and simulations indicate that the postprocessing method is inferior, unless the noise correlations between neighboring pixels are taken into account. This can be done by applying a so-called prewhitening filter. However, because the prewhitening filter is shift variant and object dependent, it seems that MAP reconstruction is the more efficient method.

Single and Multipinhole Collimator Design Evaluation Method for Small Animal SPECT

High-resolution functional imaging of small animals is often obtained by single pinhole SPECT with circular orbit acquisition. Multipinhole SPECT adds information due to its improved sampling, and can improve the trade-off between resolution and sensitivity. To evaluate different pinhole collimator designs an efficient method is needed that quantifies the reconstruction image quality. In this paper, we propose a fast, approximate method that examines the quality of individual voxels of a postsmoothed maximum likelihood expectation maximization (MLEM) reconstruction by studying their linearized local impulse response (LLIR) and (co)variance for a predefined target resolution. For validation, the contrast-to-noise ratios (CNRs) in some voxels of a homogeneous sphere and of a realistic rat brain software phantom were calculated for many single and multipinhole designs. A good agreement was observed between the CNRs obtained with the approximate method and those obtained with postsmoothed MLEM reconstructions of simulated noisy projections. This good agreement was quantified by a least squares fit through these results, which yielded a line with slope 1.02 (1.00 expected) and a y-intercept close to zero (0 expected). 95.4% of the validation points lie within three standard deviations from that line. Using the approximate method, the influence on the CNR of varying a parameter in realistic single and multipinhole designs was examined. The investigated parameters were the aperture diameter, the distance between the apertures and the axis-of-rotation, the focal distance, the acceptance angle, the position of the apertures, the focusing distance, and the number of pinholes. The results can generally be explained by the change in sensitivity, the amount of postsmoothing, and the amount of overlap in the projections. The method was applied to multipinhole designs with apertures focusing at a single point, but is also applicable to other designs.

Non-invasive imaging of neuropathology in a rat model of α-synuclein overexpression

Parkinsons disease is a neurodegenerative disorder affecting the dopaminergic neurons in the substantia nigra. Aggregation of alpha-synuclein appears to play a central role in the pathogenesis. Novel animal models for neurodegeneration have been generated by lentiviral vector-mediated locoregional overexpression of disease-associated genes in the adult brain. We have used lentiviral vectors to overexpress a clinical mutant of alpha-synuclein, A30P, in the rat substantia nigra. This overexpression induced time-dependent cytoplasmic and neuritic accumulation of alpha-synuclein and neurodegeneration. A subgroup of the rats developed asymmetric rotational behavior after administration of amphetamine. In addition, these animals displayed reduced dopamine transporter binding visualized by 123I-FP-CIT microSPECT imaging. The behavioral and microSPECT data were validated by histological analysis. There was a strong correlation between the reduction of dopaminergic neurons in the substantia nigra and the reduction of dopamine transporter binding in the striatum. MicroSPECT imaging enables non-invasive imaging of the neurodegeneration allowing longitudinal follow-up in this new animal model for Parkinsons disease and the evaluation of neuroprotective drugs.

Correction for imperfect camera motion and resolution recovery in pinhole SPECT

Pinhole SPECT is typically applied in small animal imaging, where high spatial resolution is required for imaging small structures in a limited field of view. Care must then be taken not to lose this high resolution information in the subsequent image reconstruction process. The calibration of a pinhole camera with a slightly oscillating detector tilt and its importance for the quality of reconstructed images is investigated. Also, the potential for resolution recovery, by modeling the finite dimensions of the pinhole aperture in the reconstruction, is investigated.

Geometrical calibration and aperture configuration design in multi-pinhole SPECT

A clinical gamma camera can be converted into a high resolution SPECT system for small animal imaging, by replacing the clinical collimator(s) with pinhole collimators. However, for optimal performance, an accurate geometrical calibration is required. If it is assumed that the detector orbit is a true circle, the calibration requires the determination of seven parameters. It has been shown that these can be uniquely determined from a SPECT scan of a phantom consisting of three point sources, if two of the distances between these point sources are known. For multi-pinhole SPECT, two point sources should be sufficient, knowledge of the distance between the point sources is not required. The calibration method has been extended for cases where the orbit deviates from the ideal circle. A second interesting problem in multi- pinhole SPECT is the optimisation of the collimator design. This requires a measure of image quality, enabling objective comparison between different designs. An efficient analytical method has been developed for that purpose. With this method, it has been shown that the aperture diameter should be slightly smaller than the desired system resolution. We have also found that increased multiplexing (which comes with an apparent increase in system sensitivity) does not lead to reduced variance for a particular target resolution. In practice, avoiding all overlap seems to yield better performance.

Optimization of pinhole SPECT calibration

Previously, we developed a method to determine the acquisition geometry of a pinhole camera. This information is needed for the correct reconstruction of pinhole SPECT images. The method uses a calibration phantom consisting of three point sources. Their positions in the field of view influence the accuracy of the geometry estimate. This study proposes a specific configuration of point sources with a specific position in the field of view for optimal image reconstruction accuracy. For the proposed calibration setup, inaccuracies of the geometry estimate due to noise in the calibration data, only cause subresolution inaccuracies in reconstructed images. Further, the calibration method uses a model of the point source configuration, which is only known with limited accuracy. The study demonstrates however, that, with the proposed calibration setup, the error in reconstructed images is comparable to the error in the phantom model.