Calculated attenuation correction for awake small animal brain PET studies

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.

Advances in PET technology have led to improved resolution capability in modern PET scanners, andhence the impact of motion has become increasingly significant in order to produce high resolutionPET images. This thesis aims to advance the utility of motion correction in combined PET and MR byimproving the capabilities of motion correction, and by easing the effort required in order to applythem. In particular, PET-based data-driven motion tracking methods, which are able to track motionwithout requiring additional hardware, are investigated and applied to the head. First, existing techniques for motion correction, especially in the context of PET/MR, are reviewedand a general framework for PET motion correction is presented. The framework provides a top-levelperspective on PET motion correction, simplifying the process of comparing and contrasting variousmotion correction techniques. Next, the implementation of a patient-based orientation system withinthe open-source PET reconstruction packages the Software for Tomographic Image Reconstruction(STIR) and the Synergistic Image Reconstruction Software (SIRF) is described. Additionally, animplementation of the general PET motion correction framework platform is introduced. To investigate current technological limitations in combined PET and MR motion correction, theefficacy of a commercial PET/MR motion correction product, Brain COMPASS (herein just COMPASSfor brevity), was assessed. An experiment introduced a methodology for measuring motion blur invivo and uses this to measure reduction in motion blur after applying COMPASS. N=10 subjects worea head-mounted apparatus with fiducial markers affixed. COMPASS reduced blur in the directionof motion, measured by the principal component of the full-width at half-maximum (FWHM) ofthe source point-spread-function (PSF) distribution, only when the motion was sufficient to causethat blur to exceed 1.9 mm. However, blur across all directions almost always increased (mean=0.3mm) when COMPASS was used. Results suggested that any error in estimating the patient posewas low and was not the cause of the blur. Increases in overall blur were therefore suspected to becaused by interpolation when resampling transformed reconstructions. A second experiment measuredneocortical standardised uptake value ratio (SUVr) in an 18F-Florbetaben (18F-FBB) study of N=42young, healthy, asymptomatic volunteers with high polygenetic risk of developing Alzheimer’s Disease.No significant changes in neocortical SUVr were observed. This cohort exhibited low motion, andthe neocortex is a large region-of-interest, so is less sensitive to motion corruption than other cohorts.Hence, it was concluded that COMPASS did not aid this investigation, but also does not have adiscernible negative impact despite low motion. During the COMPASS investigation, MR acquisitions were the time-limiting factor of the session,meaning that the MR acquisitions introduced for PET motion correction increased the overall sessiontime. Because MR is not always available for motion tracking, alternative PET-alone motion correctiontechniques were investigated. Several data-driven tracking techniques are available; however, it is notclear which are most appropriate. A phantom investigation was conducted on a Biograph mCT Flowto determine which data-driven head motion tracking techniques were most appropriate. Of the fourmethodologies investigated principal component analysis (PCA) was found to be the most promisingtechnique for PET data-driven motion tracking of head motion. The PET-alone motion correction technique outlined above had two key limitations. Firstly, theyprovide frame-based motion correction with low temporal resolution. However, the type of motionseen in the COMPASS investigation were continuous “drooping” of the head, is not modelled in adiscrete, frame-based scheme. Secondly, the PET reconstructions without attenuation provide noisypose estimates compared to those from MR volume registration. Therefore, a scheme was proposedthat, unlike previous techniques, models head motion directly from motion surrogates. Here, a radialbasis function (RBF) regression relates the endogenous tracking signal to the exogenous rigid poseparameters, which are supplied by temporal-sparse MR acquisitions. A proof-of-concept is presentedin which low temporal resolution MR pose estimates are upsampled. The technique is compared tolinear and nearest-neighbour interpolation, and for the regression, both linear and RBF are investigated.The proposed technique was found to introduce some negligible blurring when no motion is present (<0.1 mm mean-of-maximum displacement (MMD)) but reduce blurring by 0.7 mm MMD when motionis present. This demonstrates the capability of the technique to reduce error in motion estimation byimproving the temporal resolution. In a clinical setting, motion correction is likely to become increasingly important in the future. Thework in this thesis will make motion correction easier to apply in a clinical setting, so that it may beapplied more regularly, providing wider benefit.

Patient motion artifacts created in cardiac SPECT imaging can lead to misinterpretation of the images, resulting in false diagnoses. This simulation study proposes a new technique for patient motion correction (MC), where we utilize a modified template projection/reconstruction (TPR) algorithm to perform a voxel-by-voxel correction to the original image. Using NCAT, we developed two female phantoms with large breasts containing a non-beating heart (heart: background=5:1). Phantom 1 had a healthy heart, and phantom 2 had a heart with a small (10%) perfusion defect in the lateral wall (severity=50%). The SimSET code was used to perform simulations for both phantoms modeling cardiac SPECT acquisitions with Tc-99m, 128×128 matrix, and 60 camera stops. In addition to two standard (no motion) acquisitions (ST) for each phantom, seven acquisitions with different degrees of phantom motion were created by manually shifting a selected number of projections in a given direction (motion ranged from 8 to 22 mm). MC images (MCI) were created using a modified TPR, where the projected template was adjusted to match the motion detected in the experimental projections by aligning the center of mass in each projection. All reconstructions were performed using OSEM with resolution recovery and attenuation correction. For all simulated movements, the MCI images exhibited improvements in both standard deviation (SD) and mean accuracy relative to the uncorrected experimental reconstructions (ER). On average, the accuracies calculated for ER, MCI and the ST reconstructions were 68%, 77%, and 76%, respectively. The average SD for ER, MCI and the ST reconstructions were 5.2, 4.0, and 4.0, respectively. Our proposed technique offers a voxel-by-voxel motion correction, which provides improved image accuracy and standard deviation of counts relative to the uncorrected images and, in many cases, the images created without patient motion.

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.

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.

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

BackgroundNoninvasive multimodality imaging is essential for preclinical evaluation of the biodistribution and pharmacokinetics of radionuclide therapy and for monitoring tumor response. Imaging with nonstandard positron-emission tomography [PET] isotopes such as 124I is promising in that context but requires accurate activity quantification. The decay scheme of 124I implies an optimization of both acquisition settings and correction processing. The PET scanner investigated in this study was the Inveon PET/CT system dedicated to small animal imaging.MethodsThe noise equivalent count rate [NECR], the scatter fraction [SF], and the gamma-prompt fraction [GF] were used to determine the best acquisition parameters for mouse- and rat-sized phantoms filled with 124I. An image-quality phantom as specified by the National Electrical Manufacturers Association NU 4-2008 protocol was acquired and reconstructed with two-dimensional filtered back projection, 2D ordered-subset expectation maximization [2DOSEM], and 3DOSEM with maximum a posteriori [3DOSEM/MAP] algorithms, with and without attenuation correction, scatter correction, and gamma-prompt correction (weighted uniform distribution subtraction).ResultsOptimal energy windows were established for the rat phantom (390 to 550 keV) and the mouse phantom (400 to 590 keV) by combining the NECR, SF, and GF results. The coincidence time window had no significant impact regarding the NECR curve variation. Activity concentration of 124I measured in the uniform region of an image-quality phantom was underestimated by 9.9% for the 3DOSEM/MAP algorithm with attenuation and scatter corrections, and by 23% with the gamma-prompt correction. Attenuation, scatter, and gamma-prompt corrections decreased the residual signal in the cold insert.ConclusionsThe optimal energy windows were chosen with the NECR, SF, and GF evaluation. Nevertheless, an image quality and an activity quantification assessment were required to establish the most suitable reconstruction algorithm and corrections for 124I small animal imaging.

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.

Respiratory motion can introduce image artefacts not only in 3D PET but also in 4D PET due to incorrect attenuation correction. In this work the influence of different attenuation correction strategies on 3D and 4D PET has been investigated. An extensive phantom study was carried out, using a normal 3D CT (pitch 1.5), a slow 3D CT (pitch 0.5), an ultraslow 3D CT (pitch 0.15), an average CT and a maximum intensity projection calculated from a 4D CT (pitch 0.1) for attenuation correction of both a 3D and 4D PET of a respiratory motion phantom. Additionally, the 4D PET was corrected phase-wise with a 4D CT (phase-correlated attenuation correction). The reconstructed PET images were analyzed concerning the reconstructed volume, motion amplitude (for 4D PET), activity concentration and activity distribution. Moreover a patient study was carried out investigating the influence of the different attenuation correction strategies for 4D PET to patient data. Therefore 4D PET data from six patients with non-small cell lung cancer (NSCLC) was alternatively attenuation corrected with a normal 3D CT, an average CT and with phase-correlated attenuation correction. The tumor volume was analyzed and the motion amplitude of the tumor was obtained from the 4D PET data sets. For the phantom data the attenuation correction with the slow CT results in the best agreement between expected and measured values of the examined quantities in 3D PET, whereas in 4D PET this was the case for the phase-correlated attenuation correction. In the patient study only small differences between the 4D PET attenuation correction methods were found. This can be explained by the relative small tumor motion in the patient population investigated (peak to peak amplitude below 5 mm except for one patient).

Iodine-125 is an inexpensive and widely available radioisotope that is used frequently in biological experiments. It is also possible to perform small animal imaging experiments with this isotope, although its low photon energy (27.5 keV) may lead to significant photon attenuation. We have developed a method to calibrate x-ray computed tomography (CT) image data in order to use microCT images to provide objective specific attenuation maps that are included in an iterative reconstruction algorithm to correct for photon attenuation. Phantom experiments with iodine-125 show that this method can compensate for the effects of photon attenuation. A uniform phantom (3.8 cm diameter) imaged without attenuation correction has a decrease in image intensity at its center of approximately 25%, but reconstruction with attenuation correction virtually eliminates the decreased image intensity in the center of the phantom. Using /sup 125/I-iodorotenone, an experimental myocardial flow tracer, we demonstrate photon attenuation correction for iodine-125 imaging in a rat. The addition of attenuation correction improves the uniformity of the resulting perfusion images, better matching the results obtained with autoradiography.

PET Attenuation Correction (AC) in small animal imaging is generally performed via transmission (TX) scans. In simultaneous PET/MR scanners, no transmission source is available, and MR-based AC (MRAC) or AC from emission data is necessary. However, MR-invisible objects such as the bed and the MR coils cannot be corrected from MR data. We quantified the effects of a Medres warming bed and a local brain coil on AC for small animal PET/MR imaging using a dedicated Inveon PET tomograph. Additionally, the effect of segmentation-based MRAC of rats in brain regions was evaluated using MR images separately acquired on a preclinical 7T MRI system.

Our goal in this work was to investigate the impact of CT-based attenuation correction on measurements of rat myocardial perfusion with (99m)Tc and (201)Tl single photon emission computed tomography (SPECT). Eight male Sprague-Dawley rats were injected with (99m)Tc-tetrofosmin and scanned in a small animal pinhole SPECT/CT scanner. Scans were repeated weekly over a period of 5 weeks. Eight additional rats were injected with (201)Tl and also scanned following a similar protocol. The images were reconstructed with and without attenuation correction, and the relative perfusion was analyzed with the commercial cardiac analysis software. The absolute uptake of (99m)Tc in the heart was also quantified with and without attenuation correction. For (99m)Tc imaging, relative segmental perfusion changed by up to +2.1%/-1.8% as a result of attenuation correction. Relative changes of +3.6%/-1.0% were observed for the (201)Tl images. Interscan and inter-rat reproducibilities of relative segmental perfusion were 2.7% and 3.9%, respectively, for the uncorrected (99m)Tc scans, and 3.6% and 4.3%, respectively, for the (201)Tl scans, and were not significantly affected by attenuation correction for either tracer. Attenuation correction also significantly increased the measured absolute uptake of tetrofosmin and significantly altered the relationship between the rat weight and tracer uptake. Our results show that attenuation correction has a small but statistically significant impact on the relative perfusion measurements in some segments of the heart and does not adversely affect reproducibility. Attenuation correction had a small but statistically significant impact on measured absolute tracer uptake.

BackgroundAccurate quantification of radioactivity, measured by an integrated positron emission tomography (PET) and magnetic resonance imaging (MRI) system, is still a challenge. One aspect of such a challenge is to correct for the hardware attenuation, such as the patient table and radio frequency (RF) resonators. For PET/MRI systems, computed tomography (CT) is commonly used to produce hardware attenuation correction (AC) maps, by converting Hounsfield units (HU) to a linear attenuation coefficients (LAC) map at the PET energy level 511 keV, using a bilinear model. The model does not address beam hardening, nor higher density materials, which can lead to inaccurate corrections.PurposeIn this study, we introduce a transmission-based (TX-based) AC technique with a static Germanium-68 (Ge-68) transmission source to generate hardware AC maps using the PET/MRI system itself, without the need for PET or medical CT scanners. The AC TX-based maps were generated for a homogeneous cylinder, made of acrylic as a validator. The technique thereafter was applied to the patient table and posterior part of an RF-phased array used in cardiovascular PET/MRI imaging. The proposed TX-based, and the CT-based, hardware maps were used in reconstructing PET images of one cardiac patient, and the results were analysed and compared.ResultsThe LAC derived by the TX-based method for the acrylic cylinder is estimated to be 0.10851 ± 0.00380 cm−1 compared to the 0.10698 ± 0.00321 cm−1 theoretical value reported in the literature. The PET photon counts were reduced by 8.7 ± 1.1% with the patient table, at the region used in cardiac scans, while the CT-based map, used for correction, over-estimated counts by 4.3 ± 1.3%. Reconstructed in vivo images using TX-based AC hardware maps have shown 4.1 ± 0.9% mean difference compared to those reconstructed images using CT-based AC.ConclusionsThe LAC of the acrylic cylinder measurements using the TX-based technique was in agreement with those in the literature confirming the validity of the technique. The over-estimation of photon counts caused by the CT-based model used for the patient table was improved by the TX-based technique. Therefore, TX-based AC of hardware using the PET/MRI system itself is possible and can produce more accurate images when compared to the CT-based hardware AC in cardiac PET images.

Attenuation correction (AC), as an essential component of quantitative SPECT imaging, is highly challenging in the absence of CT or transmission scanning in dedicated cardiac SPECT devices. This study investigated the potential of direct attenuation correction (AC) of <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">99m</sup> Tc-sestamibi SPECT myocardial perfusion imaging (MPI) in the image domain using residual (ResNet) and UNet deep convolutional neural networks. MPI-SPECT <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">99m</sup> Tc-ses-tamibi images of 99 subjects were retrospectively used, considering non-attenuation corrected SPECT images as input and CT-based attenuation corrected (CT-AC) SPECT images as reference. Chang’s AC technique was also performed as a baseline for evaluating the performance of deep learning-based models. The quantitative accuracy of the attenuation corrected SPECT images was validated using the proposed methods considering the corresponding CT-AC SPECT images of 19 external datasets as reference. Image-derived metrics, including the voxel-wise mean absolute error (MAE), relative error (RE), structural similarity index measure (SSIM), as well as clinically relevant indices, such as total perfusion deficit (TPD), were calculated. The quantitative results obtained from the external validation dataset of the deep learning models exhibited good agreement with the reference CT-based attenuation corrected MPI-SPECT images. The deep learning models showed superior performance over Chang’s AC method. The ResNet and UNet models resulted in MAE of 20.24±17.63 and 13.65±11.23 and SSIM of 0.99±0.04 and 0.98±0.05, respectively. In comparison, Chang’s approach led to MAE and SSIM of 80.27±47.56 and 0.93±0.09, respectively. Similarly, the clinical evaluation showed a mean TPD of 12.78±9.22% and 12.57±8.93% for ResNet and UNet models, respectively, compared to TPD of 12.84±8.63% for reference SPECT CT-AC images. In contrast, Chang’s approach led to a mean TPD of 16.68±11.24%. The evaluation of deep learning approaches implemented in this work showed the promising potential of deep learning-based techniques in producing attenuation corrected MPI-SPECT images in the image domain without anatomical imaging.

In this study open-source software (QSPECT) suitable for the iterative reconstruction of single-photon emission computed tomography (SPECT) data is presented. QSPECT implements maximum likelihood expectation maximization and ordered subsets expectation maximization algorithms in a user-friendly graphical interface. The software functionality is described and validation results are presented. Maximum likelihood expectation maximization and ordered subsets expectation maximization algorithms are implemented in C++. The Qt toolkit, a standard C++ framework for developing high-performance cross-platform applications, has been used for the graphical user interface development. QSPECT is tested using original projection data from two clinical SPECT systems: (i) APEX SPX-6/6HR and (ii) Millennium MG. Phantom experiments were carried out to evaluate the quality of reconstructed images in terms of (i) spatial resolution, (ii) sensitivity to activity variations, and (iii) the presence of scatter media. A cardiac phantom was used to simulate a normal and abnormal scenario. Finally, clinical cardiac SPECT images were reconstructed. In all cases, QSPECT results were compared with the clinical systems reconstruction software that uses the standard filtered backprojection algorithm. The reconstructed images show that QSPECT, when compared with standard clinical reconstruction, provides images with higher contrast, reduced background, and better separation of small sources located in small distances. In addition, reconstruction with QSPECT provides more quantitative images, and reduces the background created by scatter media. Finally, the phantom and clinical cardiac images are reconstructed with similar quality. QSPECT is a freely distributed, open-source standalone application that provides real-time, high-quality SPECT images. The software can be further modified to improve reconstruction algorithms, and include more correction techniques, such as, scatter and attenuation correction.