Kathleen Vunckx

Evaluation of Three MRI-Based Anatomical Priors for Quantitative PET Brain Imaging

In emission tomography, image reconstruction and therefore also tracer development and diagnosis may benefit from the use of anatomical side information obtained with other imaging modalities in the same subject, as it helps to correct for the partial volume effect. One way to implement this, is to use the anatomical image for defining the a priori distribution in a maximum-a-posteriori (MAP) reconstruction algorithm. In this contribution, we use the PET-SORTEO Monte Carlo simulator to evaluate the quantitative accuracy reached by three different anatomical priors when reconstructing positron emission tomography (PET) brain images, using volumetric magnetic resonance imaging (MRI) to provide the anatomical information. The priors are: 1) a prior especially developed for FDG PET brain imaging, which relies on a segmentation of the MR-image (Baete , 2004); 2) the joint entropy-prior (Nuyts, 2007); 3) a prior that encourages smoothness within a position dependent neighborhood, computed from the MR-image. The latter prior was recently proposed by our group in (Vunckx and Nuyts, 2010), and was based on the prior presented by Bowsher (2004). The two latter priors do not rely on an explicit segmentation, which makes them more generally applicable than a segmentation-based prior. All three priors produced a compromise between noise and bias that was clearly better than that obtained with postsmoothed maximum likelihood expectation maximization (MLEM) or MAP with a relative difference prior. The performance of the joint entropy prior was slightly worse than that of the other two priors. The performance of the segmentation-based prior is quite sensitive to the accuracy of the segmentation. In contrast to the joint entropy-prior, the Bowsher-prior is easily tuned and does not suffer from convergence problems.

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.

Small animal imaging with multi-pinhole SPECT

With Single Photon Emission Computed Tomography (SPECT), images of minute concentrations of tracer molecules can be acquired, allowing in vivo molecular imaging. For human imaging, the SPECT system has a modest spatial resolution of 5-15 mm, a large field of view and a high sensitivity. Using multi-pinhole SPECT, one can trade in field of view for resolution with preserved sensitivity, which enables the implementation of a small animal SPECT system with an improved resolution, currently ranging from 0.3 to 2 mm, in a much smaller field of view. The unconventional collimation and the more stringent resolution requirements pose problems that are not present in clinical SPECT imaging. This paper discusses how these problems can be solved to implement micro-SPECT imaging on a rotating gamma camera.

Preliminary in vivo evaluation of a novel 99mTc-Labeled HYNIC-cys-annexin A5 as an apoptosis imaging agent

A novel cys-annexin A5 with a single cysteine-residue at its concave side has been developed by site-directed mutagenesis to allow conjugation through thiol-chemistry without affecting its apoptotic cell binding properties and was derivatized with HYNIC in a 1:1 stoichiometry. Similar to that of the 1st generation 99mTc-HYNIC-annexin A5, the novel 99mTc-HYNIC-cys-annexin A5 derivative shows in normal mice mainly renal and, to a lesser extent, hepatobiliary excretion. In murine models of hepatic apoptosis there was 257% increase in hepatic uptake of 99mTc-HYNIC-cys-annexin A5 as compared to normal mice. Using the novel tracer agent, acute reperfused myocardial infarction in rabbits was unequivocally delineated at 7h post-injection by muSPECT. The results indicate that the novel 99mTc-HYNIC-cys-annexin A5 shows similar apoptosis avidity as the 1st generation 99mTc-HYNIC-annexin A5.

Fisher Information-Based Evaluation of Image Quality for Time-of-Flight PET

The use of time-of-flight (TOF) information during reconstruction is generally considered to improve the image quality. In this work we quantified this improvement using two existing methods: (1) a very simple analytical expression only valid for a central point in a large uniform disk source, and (2) efficient analytical approximations for post-filtered maximum likelihood expectation maximization (MLEM) reconstruction with a fixed target resolution, predicting the image quality in a pixel or in a small region based on the Fisher information matrix. The image quality was investigated at different locations in various software phantoms. Simplified as well as realistic phantoms, measured both with TOF positron emission tomography (PET) systems and with a conventional PET system, were simulated. Since the time resolution of the system is not always accurately known, the effect on the image quality of using an inaccurate kernel during reconstruction was also examined with the Fisher information- based method. First, we confirmed with this method that the variance improvement in the center of a large uniform disk source is proportional to the disk diameter and inversely proportional to the time resolution. Next, image quality improvement was observed in all pixels, but in eccentric and high-count regions the contrast-to-noise ratio (CNR) increased slower than in central and low- or medium-count regions. Finally, the CNR was seen to decrease when the time resolution was inaccurately modeled (too narrow or too wide) during reconstruction. Although the optimum is rather flat, using an inaccurate TOF kernel might introduce artifacts in the reconstructed image.

Optimized multipinhole design for mouse imaging

To enhance high-sensitivity focused mouse imaging using multipinhole SPECT on a dual head camera, a fast analytical method was used to predict the contrast-to-noise ratio (CNR) in many points of a homogeneous cylinder for a large number of pinhole collimator designs with modest overlap. The design providing the best overall CNR, a configuration with 7 pinholes, was selected. Next, the pinhole pattern was made slightly irregular to reduce multiplexing artifacts. Two identical, but mirrored 7-pinhole plates were manufactured. In addition, the calibration procedure was refined to cope with small deviations of the camera from circular motion. First, the new plates were tested by reconstructing a simulated homogeneous cylinder measurement. Second, a Jaszczak phantom filled with 37 MBq 99mTc was imaged on a dual head gamma camera, equipped with the new pinhole collimators. The image quality before and after refined calibration was compared for both heads, reconstructed separately and together. Next, 20 short scans of the same phantom were performed with single and multipinhole collimation to investigate the noise improvement of the new design. Finally, two normal mice were scanned using the new multipinhole designs to illustrate the reachable image quality of abdomen and thyroid imaging. The simulation study indicated that the irregular patterns suppress most multiplexing artifacts. Using body support information strongly reduces the remaining multiplexing artifacts. Refined calibration improved the spatial resolution. Depending on the location in the phantom, the CNR increased with a factor of 1 to 2.5 using the new instead of a single pinhole design. The first proof of principle scans and reconstructions were successful, allowing the release of the new plates and software for preclinical studies in mice.

Effect of Overlapping Projections on Reconstruction Image Quality in Multipinhole SPECT

Multipinhole imaging has a lot of advantages over single pinhole, such as an increased sensitivity and an improved sampling. However, the quest for a good design is tedious, due to the large number of design parameters. One of these, the amount of overlap in the projection images, and its effect on the reconstruction image quality, is examined in this paper. The evaluation of the quality is based on efficient approximations for the linearized local impulse response and the covariance in a voxel. Two (theoretical) methods for overlap removal and two measures to quantify the overlap are proposed. First, the approximate method is validated with standard iterative reconstructions. Second, designs with different amounts of overlap are evaluated before and after overlap removal to verify the effect of multiplexing. Third, the results are interpreted with the overlap quantification measures. We can conclude that overlap removal improves image quality: the loss of information due to multiplexing is not compensated by the increase in sensitivity.

Construction and Evaluation of Quantitative Small-Animal PET Probabilistic Atlases for [18F]FDG and [18F]FECT Functional Mapping of the Mouse Brain

Automated voxel-based or pre-defined volume-of-interest (VOI) analysis of small-animal PET data in mice is necessary for optimal information usage as the number of available resolution elements is limited. We have mapped metabolic ([18F]FDG) and dopamine transporter ([18F]FECT) small-animal PET data onto a 3D Magnetic Resonance Microscopy (MRM) mouse brain template and aligned them in space to the Paxinos co-ordinate system. In this way, ligand-specific templates for sensitive analysis and accurate anatomical localization were created. Next, using a pre-defined VOI approach, test-retest and intersubject variability of various quantification methods were evaluated. Also, the feasibility of mouse brain statistical parametric mapping (SPM) was explored for [18F]FDG and [18F]FECT imaging of 6-hydroxydopamine-lesioned (6-OHDA) mice. Methods Twenty-three adult C57BL6 mice were scanned with [18F]FDG and [18F]FECT. Registrations and affine spatial normalizations were performed using SPM8. [18F]FDG data were quantified using (1) an image-derived-input function obtained from the liver (cMRglc), using (2) standardized uptake values (SUVglc) corrected for blood glucose levels and by (3) normalizing counts to the whole-brain uptake. Parametric [18F]FECT binding images were constructed by reference to the cerebellum. Registration accuracy was determined using random simulated misalignments and vectorial mismatch determination. Results Registration accuracy was between 0.21–1.11 mm. Regional intersubject variabilities of cMRglc ranged from 15.4% to 19.2%, while test-retest values were between 5.0% and 13.0%. For [18F]FECT uptake in the caudate-putamen, these values were 13.0% and 10.3%, respectively. Regional values of cMRglc positively correlated to SUVglc measured within the 45–60 min time frame (spearman r = 0.71). Next, SPM analysis of 6-OHDA-lesioned mice showed hypometabolism in the bilateral caudate-putamen and cerebellum, and an unilateral striatal decrease in DAT availability. Conclusion MRM-based small-animal PET templates facilitate accurate assessment and spatial localization of mouse brain function using VOI or voxel-based analysis. Regional intersubject- and test-retest variations indicate that for these targets accuracy comparable to humans can be achieved.

Heuristic modification of an anatomical Markov prior improves its performance

Including anatomical information during emission tomography reconstruction with resolution modeling can enhance the image quality. Often accurate segmentation of the anatomical image is required, being a major challenge for most applications. Recently, we studied a segmentation-free MAP algorithm proposed by Bowsher et al, that encourages similar activity in a selection of neighboring voxels that look most alike in the anatomical image. In an evaluation with Monte Carlo simulations, it was found to be very promising for both bias and noise reduction in 3D PET/MRI brain imaging, compared to MLEM and MAP algorithms with regular or anatomical priors. Here we study a small modification of the Bowsher algorithm to further improve its reconstruction capacities. Comparison between the two methods using the same brain phantom scan simulations indicated a further decrease in bias at the same noise level.

Evaluation of different MRI-based anatomical priors for PET brain imaging

Image reconstruction in emission tomography may benefit from the use of anatomical side information obtained with other imaging modalities in the same subject. One way to implement this, is to use the anatomical image for defining the a-priori distribution in a maximum-a-posteriori reconstruction algorithm. In this contribution, we use the PET-SORTEO Monte Carlo simulator to evaluate three different anatomical priors for PET brain imaging, using MRI for the anatomical image. The priors are: 1) a prior based on a segmentation of the MRI image; 2) the joint entropy prior; 3) a prior (proposed by Bowsher et al. [1]) that encourages smoothness within a position dependent neighborhood, computed from the MRI image. The two latter priors do not rely on an explicit segmentation, which makes them more generally applicable than a segmentation-based prior. The three priors produced a compromise between noise and bias that was significantly better than that obtained with post-smoothed MLEM. The performance of the joint entropy prior was slightly worse than that of the other two priors. In contrast to the joint entropy prior, the Bowsher prior is easily tuned and does not pose convergence problems due to local maxima.