A new approach in patient motion correction for cardiac SPECT: A simulation study

Respiratory motion induces artifacts in reconstructed cardiac perfusion SPECT images. Correction for respiratory motion often relies on a respiratory signal describing the heart displacements during breathing. However, using external tracking devices to estimate respiratory signals can add cost and operational complications in a clinical setting. We aim to develop a deep learning (DL) approach that uses only SPECT projection data for respiratory signal estimation. A modified U-Net was implemented that takes temporally finely sampled SPECT sub-projection data (100ms) as input. These sub-projections are obtained by reframing the 20-s list-mode data, resulting in 200 sub-projections, at each projection angle for each SPECT camera head. The network outputs a 200-time-point motion signal for each projection angle, which was later aggregated over all angles to give a full respiratory signal. The target signal for DL model training was from an external stereo-camera visual tracking system (VTS). In addition to comparing DL and VTS, we also included a data-driven approach based on the center-of-mass (CoM) strategy. This CoM method estimates respiratory signals by monitoring the axial changes of CoM for counts in the heart region of the sub-projections. We utilized 900 subjects with stress cardiac perfusion SPECT studies, with 302 subjects for testing and the remaining 598 subjects for training and validation. The Pearson's correlation coefficient between the DL respiratory signal and the reference VTS signal was 0.90, compared to 0.70 between the CoM signal and the reference. For respiratory motion correction on SPECT images, all VTS, DL, and CoM approaches partially de-blured the heart wall, resulting in a thinner wall thickness and increased recovered maximal image intensity within the wall, with VTS reducing blurring the most followed by the DL approach. Uptake quantification for the combined anterior and inferior segments of polar maps showed a mean absolute difference from the reference VTS of 1.7% for the DL method for patients with motion >12mm, compared to 2.6% for the CoM method and 8.5% for no correction. We demonstrate the capability of a DL approach to estimate respiratory signal from SPECT projection data for cardiac perfusion imaging. Our results show that the DL based respiratory motion correction reduces artefacts and achieves similar regional quantification to that obtained using the stereo-camera VTS signals. This may enable fully automatic data-driven respiratory motion correction without relying on external motion tracking devices.

Motion correction in Arterial Spin Labeling (ASL) is essential to accurately assess brain perfusion. Motion correction techniques are usually based on intensity-related information, which might be unreliable in ASL due to local intensity differences between control and labeled acquisitions and to non-uniform volume magnetization caused by background-suppressed acquisition protocols. Accordingly, a novel motion correction technique based only on brain contour points is presented and tested against a widely used intensity-based technique (MCFLIRT). The proposed Contour-Based Motion Correction (CBCM) technique relies on image segmentation (to extract brain contour point clouds) and on Iterative Closest Point algorithm (to estimate the roto-translation required to align them). At variance with other approaches based on point clouds alignment, the local 3D curvature is also computed for each contour point and used as an additional coordinate to increase the accuracy of the alignment. The technique has been tested along with MCFLIRT on a database of randomly roto-translated brain volumes. Several error metrics have been computed and compared between the two techniques. The results show that the proposed technique is able to achieve a higher accuracy than MCFLIRT without any intensity-dependent information.

Cardiac motion is a challenging cause of image artefacts in myocardial perfusion SPECT. A wide range of motion correction methods have been developed over the years, and so far automatic algorithms based on the reconstruction--reprojection principle have proved to be the most effective. However, these methods have not been fully optimised in terms of their free parameters and implementational details. Two slightly different implementations of reconstruction--reprojection-based motion correction techniques were optimised for effective, good-quality motion correction and then compared with each other. The first of these methods (Method 1) was the traditional reconstruction-reprojection motion correction algorithm, where the motion correction is done in projection space, whereas the second algorithm (Method 2) performed motion correction in reconstruction space. The parameters that were optimised include the type of cost function (squared difference, normalised cross-correlation and mutual information) that was used to compare measured and reprojected projections, and the number of iterations needed. The methods were tested with motion-corrupt projection datasets, which were generated by adding three different types of motion (lateral shift, vertical shift and vertical creep) to motion-free cardiac perfusion SPECT studies. Method 2 performed slightly better overall than Method 1, but the difference between the two implementations was small. The execution time for Method 2 was much longer than for Method 1, which limits its clinical usefulness. The mutual information cost function gave clearly the best results for all three motion sets for both correction methods. Three iterations were sufficient for a good quality correction using Method 1. The traditional reconstruction--reprojection-based method with three update iterations and mutual information cost function is a good option for motion correction in clinical myocardial perfusion SPECT.

BackgroundRespiratory motion in PET/CT leads to well-known image degrading effects commonly compensated using elastic motion correction approaches. Gate-to-gate motion correction techniques are promising tools for improving clinical PET data but suffer from relatively long reconstruction times. In this study, the performance of a fast elastic motion compensation approach based on motion deblurring (DEB-MC) was evaluated on patient and phantom data and compared to an EM-based fully 3D gate-to-gate motion correction method (G2G-MC) which was considered the gold standard.MethodsTwenty-eight patients were included in this study with suspected or confirmed malignancies in the thorax or abdomen. All patients underwent whole-body [18F]FDG PET/CT examinations applying hardware-based respiratory gating. In addition, a dynamic anthropomorphic thorax phantom was studied with PET/CT simulating tumour motion under controlled but realistic conditions. PET signal recovery values were calculated from phantom scans by comparing lesion activities after motion correction to static ground truth data. Differences in standardized uptake values (SUV) and metabolic volume (MV) between both reconstruction methods as well as between motion-corrected (MC) and non motion-corrected (NOMC) results were statistically analyzed using a Wilcoxon signed-rank test.ResultsPhantom data analysis showed high lesion recovery values of 91% (2 cm motion) and 98% (1 cm) for G2G-MC and 83% (2 cm) and 90% (1 cm) for DEB-MC. The statistical analysis of patient data found significant differences between NOMC and MC reconstructions for SUV max, SUV mean, MV, and contrast-to-noise ratio (CNR) for both reconstruction algorithms. Furthermore, both methods showed similar increases of 11–12% in SUV max and SUV mean after MC. The statistical analysis of the MC/NOMC ratio found no significant differences between the methods.ConclusionBoth motion correction techniques deliver comparable improvements of SUV max, SUV mean, and CNR after MC on clinical and phantom data. The fast elastic motion compensation technique DEB-MC may thereby be a valuable alternative to state-of-the art motion correction techniques.

Patient motion during cardiac SPECT imaging can cause diagnostic imaging artifacts. Our approach is to monitor patient motion during cardiac SPECT imaging using the Polaris stereo-IR real-time motion-tracking system. In our earlier work we obtained excellent correlation of axial and vertical motion as measured by our SPECT system with the Polaris. We also showed a good correlation for Polaris tracking of respiration for volunteers with data from a pneumatic bellows. Herein, we show the successful monitoring of patients during cardiac SPECT perfusion imaging. We wrapped elastic belts with four IR reflecting spheres on each about the chest and abdomen of the patients. The Polaris system reported the 3D location of these spheres in a random order intermixed with the location of spheres. We developed routines to automatically recognize and discard the phantom spheres, consistently order the true spheres, and covert Polaris coordinates to SPECT coordinates given a calibration. For our 12 analyzed clinical patients the data shows that both males and females at rest were primarily abdomen breathers with the male peak to peak average vertical respiration amplitude larger at 9.2 mm than that for the females at 5.6 mm. The male chest average vertical amplitude was also a bit larger at 1.6 mm vs. 1.4 mm for females. During the 16 minute SPECT acquisition the average vertical axis difference between end-expiration levels for the abdomen for combined males and females was -4.2 mm, with males slightly larger at -4.72 mm vs. females at -3.81 mm. The largest vertical end expiration change was -9.0 mm, and was observed in the male with the highest body mass index (BMI) of 44.2.

Attenuation correction of small animal PET data is very important when quantitative images are of interest. Attenuation correction coefficients are conventionally obtained via a transmission or a computed tomography scan, which require anaesthetisation of the animal. However, in the context of awake and/or freely moving animals, where animal motion is compensated via appropriate motion tracking and correction techniques, anaesthetisation is no longer required. In this work we investigate the accuracy of a transmission-less attenuation correction approach based on the segmentation of the motion corrected emission image. Results on both phantom and real rat data acquired on the microPET Focus220 scanner, indicate good agreement between the segmentation based and conventional transmission based approach (∼ 2% difference). In addition, the segmentation based approach has the potential to eliminate noise propagation from the measured transmission data to the reconstructed attenuation corrected emission images.

Optical computed tomography (optical-CT) and optical-emission computed tomography (optical-ECT) are new techniques for imaging the 3D structure and function (including gene expression) of whole unsectioned tissue samples. This work presents a method of improving the quantitative accuracy of optical-ECT by correcting for the ‘self’-attenuation of photons emitted within the sample. The correction is analogous to a method commonly applied in single-photon-emission computed tomography reconstruction. The performance of the correction method was investigated by application to a transparent cylindrical gelatin phantom, containing a known distribution of attenuation (a central ink-doped gelatine core) and a known distribution of fluorescing fibres. Attenuation corrected and uncorrected optical-ECT images were reconstructed on the phantom to enable an evaluation of the effectiveness of the correction. Significant attenuation artefacts were observed in the uncorrected images where the central fibre appeared ∼24% less intense due to greater attenuation from the surrounding ink-doped gelatin. This artefact was almost completely removed in the attenuation-corrected image, where the central fibre was within ∼4% of the others. The successful phantom test enabled application of attenuation correction to optical-ECT images of an unsectioned human breast xenograft tumour grown subcutaneously on the hind leg of a nude mouse. This tumour cell line had been genetically labelled (pre-implantation) with fluorescent reporter genes such that all viable tumour cells expressed constitutive red fluorescent protein and hypoxia-inducible factor 1 transcription-produced green fluorescent protein. In addition to the fluorescent reporter labelling of gene expression, the tumour microvasculature was labelled by a light-absorbing vasculature contrast agent delivered in vivo by tail-vein injection. Optical-CT transmission images yielded high-resolution 3D images of the absorbing contrast agent, and revealed highly inhomogeneous vasculature perfusion within the tumour. Optical-ECT emission images yielded high-resolution 3D images of the fluorescent protein distribution in the tumour. Attenuation-uncorrected optical-ECT images showed clear loss of signal in regions of high attenuation, including regions of high perfusion, where attenuation is increased by increased vascular ink stain. Application of attenuation correction showed significant changes in an apparent expression of fluorescent proteins, confirming the importance of the attenuation correction. In conclusion, this work presents the first development and application of an attenuation correction for optical-ECT imaging. The results suggest that successful attenuation correction for optical-ECT is feasible and is essential for quantitatively accurate optical-ECT imaging.

For PET/CT systems, PET image reconstruction requires corresponding CT images for anatomical localization and attenuation correction. In the case of PET respiratory gating, multiple gated CT scans can offer phase-matched attenuation and motion correction, at the expense of increased radiation dose. We aim to minimize the dose of the CT scan, while preserving adequate image quality for the purpose of PET attenuation correction by introducing sparse view CT data acquisition.We investigated sparse view CT acquisition protocols resulting in ultra-low dose CT scans designed for PET attenuation correction. We analyzed the tradeoffs between the number of views and the integrated tube current per view for a given dose using CT and PET simulations of a 3D NCAT phantom with lesions inserted into liver and lung. We simulated seven CT acquisition protocols with {984, 328, 123, 41, 24, 12, 8} views per rotation at a gantry speed of 0.35 s. One standard dose and four ultra-low dose levels, namely, 0.35 mAs, 0.175 mAs, 0.0875 mAs, and 0.043 75 mAs, were investigated. Both the analytical Feldkamp, Davis and Kress (FDK) algorithm and the Model Based Iterative Reconstruction (MBIR) algorithm were used for CT image reconstruction. We also evaluated the impact of sinogram interpolation to estimate the missing projection measurements due to sparse view data acquisition. For MBIR, we used a penalized weighted least squares (PWLS) cost function with an approximate total-variation (TV) regularizing penalty function. We compared a tube pulsing mode and a continuous exposure mode for sparse view data acquisition. Global PET ensemble root-mean-squares-error (RMSE) and local ensemble lesion activity error were used as quantitative evaluation metrics for PET image quality.With sparse view sampling, it is possible to greatly reduce the CT scan dose when it is primarily used for PET attenuation correction with little or no measureable effect on the PET image. For the four ultra-low dose levels simulated, sparse view protocols with 41 and 24 views best balanced the tradeoff between electronic noise and aliasing artifacts. In terms of lesion activity error and ensemble RMSE of the PET images, these two protocols, when combined with MBIR, are able to provide results that are comparable to the baseline full dose CT scan. View interpolation significantly improves the performance of FDK reconstruction but was not necessary for MBIR. With the more technically feasible continuous exposure data acquisition, the CT images show an increase in azimuthal blur compared to tube pulsing. However, this blurring generally does not have a measureable impact on PET reconstructed images.Our simulations demonstrated that ultra-low-dose CT-based attenuation correction can be achieved at dose levels on the order of 0.044 mAs with little impact on PET image quality. Highly sparse 41- or 24- view ultra-low dose CT scans are feasible for PET attenuation correction, providing the best tradeoff between electronic noise and view aliasing artifacts. The continuous exposure acquisition mode could potentially be implemented in current commercially available scanners, thus enabling sparse view data acquisition without requiring x-ray tubes capable of operating in a pulsing mode.

Clinical Applications of Technetium-99m Quantitative Single-Photon Emission Computed Tomography/Computed Tomography.

High-resolution small-animal SPECT imaging plays a pivotal role in preclinical research by enabling quantitative visualization of radiopharmaceutical distribution in animal models. However, challenges, including physical degrading factors, such as photon attenuation, scattering, and limited spatial resolution hinder SPECT's quantitative accuracy. Advanced reconstruction algorithms are essential to mitigate these effects and enhance image fidelity. We developed a quantitative iterative reconstruction algorithm for the developed silicon photomultipliers (SiPMs)-based HiReSPECT II preclinical SPECT system, incorporating resolution recovery, attenuation correction, and scatter compensation. Resolution recovery was modelled using a distance-dependent Gaussian collimator-detector response (CDR). Attenuation correction was implemented via binary attenuation maps with photon path-length calculation using Siddon's ray-tracing method. Scatter correction was performed on list-mode data by estimating and subtracting scattered events using the Dual-Energy Window (DEW) technique. The reconstructed images were calibrated to absolute radiotracer concentration units. Quantitative imaging performance was validated using uniformity and NEMA NU 4-2008 image quality phantoms, followed by in vivo mouse imaging studies. The proposed algorithm significantly enhanced image quality and quantitative accuracy. Resolution recovery improved sharpness, while scatter and attenuation corrections minimized artifacts and ensured uniformity. Key metrics demonstrated substantial improvements in contrast, uniformity and resolution. Quantitative accuracy also significantly improved. Incorporating resolution recovery, scatter correction, and attenuation correction into preclinical SPECT image reconstruction is critical for achieving high quantitative accuracy. The integration of these techniques in systems, such as HiReSPECT II, establishes a new benchmark for preclinical imaging, facilitating radiotracer development and advancing translational research.

We evaluated a novel normal database (NDB) generated using single photon emission computed tomography (SPECT) data obtained from healthy brains by using a SPECT/CT system, analyzed using a resolution recovery (RR) technique applied to the three-dimensional stereotactic surface projection (3D-SSP) technique. We used a three-dimensional ordered subset expectation maximization method (3D-OSEM) with applied scatter correction (SC), attenuation correction, and RR to reconstruct the data. We verified the accuracy of the novel NDB's values (Z, extent, and error scores), and compared the novel NDB to the 3D-SSP technique by using simulated misery perfusion-related patient data from a conventional NDB. In addition, Z, extent, and error scores at the precuneus, cuneus, and posterior cingulate were compared under different reconstruction conditions by using the patient data. In the simulation, Z scores decreased when using the novel NDB corrected using computed tomography-based attenuation correction (CTAC), SC, and RR. The extent scores of the posterior cingulate increased using the novel NDB, relative to the other NDBs. The error score with the novel NDB without RR decreased by 15% compared to that of the conventional NDB. Z scores generated from patient data decreased in the novel NDB with RR. The extent scores tended to decrease in the novel NDB with RR. The extent scores in the novel NDB with RR improved at the posterior cingulate, compared to the scores with the other NDBs. However, applying RR to the novel NDB conferred no advantage because the cut-off of the current Z score must be reconsidered when using the additive RR technique.

Attenuation correction of PET activation studies in the presenceof task-related motion

Motion estimation strategies found in literature may be categorized primarily into two types: data-driven using the SPECT acquisition data itself to determine motion, and external surrogate-based, where motion is obtained from a dedicated motion-tracking system. The surrogate-based motion estimates though accurate, measure only the motion exhibited externally which may not correlate exactly with the movement of the heart inside the body, whereas the accuracy of data-driven strategies is limited by the type of motion to be estimated and various degrading factors such as noise, attenuation, scatter, and collimator blurring. The goal of this work is to evaluate and compare existing data-driven strategies for cardiac SPECT studies, and ultimately to devise methods to integrate the data-driven and surrogate-based motion estimation to overcome their individual limitations.

To develop an efficient navigator-based motion and temporal B0-shift correction technique for 3D multi-echo gradient-echo (ME-GRE) MRI for quantitative susceptibility mapping (QSM) and mapping. A dual-echo 3D stack-of-spiral navigator was designed to interleave with the Cartesian multi-echo gradient-echo acquisitions, allowing the acquisition of both low-echo and high-echo time signals. We additionally designed a novel conjugate phase-based reconstruction method for the joint correction of motion and temporal B0 shifts. We performed numerical simulation, phantom scans,and in vivo human scans to assess the performance of the methods. Numerical simulation and human brain scans demonstrated that the proposed technique successfully corrected artifacts induced by both head motions and temporal B0 changes. Efficient B0-change correction with conjugate-phase reconstruction can be performed on fewer than 10 clustered k-space segments. In vivo scans showed that combining temporal B0 correction with motion correction further reduced artifacts and improved image quality in both and QSM images. Our proposed approach of using 3D spiral navigators and a novel conjugate-phase reconstruction method can improve susceptibility-related measurements using MR.

The purpose of this study was to demonstrate the feasibility of accurate quantification in pinhole SPECT using micro-CT information. Pinhole SPECT scans were performed using a clinical dual-head gamma camera. Each pinhole SPECT scan was followed by a micro-CT acquisition. Functional and anatomical images were coregistered using six point sources visible with both modalities. Pinhole SPECT images were reconstructed iteratively. Attenuation correction was based on micro-CT information. Scatter correction was based on dual and triple-energy window methods. Phantom and animal experiments were performed. A phantom containing nine vials was filled with different concentrations of (99m)Tc. Three vials were also filled with CT contrast agent to increase attenuation. Activity concentrations measured on the pinhole SPECT images were compared with activity concentrations measured by the dose calibrator. In addition, 11 mice were injected with (99m)Tc-labelled Nanobodies. After acquiring functional and anatomical images, the animals were killed and the liver activity was measured using a gamma-counter. Activity concentrations measured on the reconstructed images were compared with activity concentrations measured with the gamma counter. The phantom experiments demonstrated an average error of -27.3 +/- 15.9% between the activity concentrations measured on the uncorrected pinhole SPECT images and in the dose calibrator. This error decreased significantly to -0.1 +/- 7.3% when corrections were applied for nonuniform attenuation and scatter. The animal experiment revealed an average error of -18.4 +/- 11.9% between the activity concentrations measured on the uncorrected pinhole SPECT images and measured with the gamma counter. This error decreased to -7.9 +/- 10.4% when attenuation and scatter correction was applied. Attenuation correction obtained from micro-CT data in combination with scatter correction allows accurate quantification in pinhole SPECT.