Performance analysis of a high-sensitivity multi-pinhole cardiac SPECT system with hemi-ellipsoid detectors.

PURPOSE: Single-photon emission computed tomography (SPECT) is a noninvasive imaging modality, used in myocardial perfusion imaging. The challenges facing the majority of clinical SPECT systems are low sensitivity, poor resolution, and the relatively high radiation dose to the patient. New generation systems (GE Discovery, DSPECT) dedicated to cardiac imaging improve sensitivity by a factor of 5-8. This improvement can be used to decrease acquisition time and/or dose. However, in the case of ultra-low dose (~3 mCi) injections, acquisition times are still significantly long, taking 10-12 min. The purpose of this work is to investigate a new gamma camera design with 21 hemi-ellipsoid detectors each with a pinhole collimator for cardiac SPECT for further improvement in sensitivity and resolution and reduced patient exposures and imaging times. METHODS: To evaluate the resolution of our hemi-ellipsoid system, GATE Monte-Carlo simulations were performed on point-sources, rod-sources, and NCAT phantoms. For average full-width-half-maximum (FWHM) equivalence with base flat-detector, the pinhole-diameter for the curved hemi-ellipsoid detector was found to be 8.68 mm, an operating pinhole-diameter nominally expected to be ~3 times more sensitive than state-of-the-art systems. Rod-sources equally spaced within the region of interest were acquired with a 21-detector system and reconstructed with our multi-pinhole (MPH) iterative OSEM algorithm with collimator resolution recovery. The results were compared with the results of a state-of-the-art system (GE Discovery) available in the literature. The system was also evaluated using the mathematical anthropomorphic NCAT (NURBS-based Cardiac Torso; Segars et al. IEEE Trans Nucl Sci. 1999;46:503-506) phantom with a full (clinical)-dose acquisition (25 mCi) for 2 min and an ultra-low dose acquisition of 3 mCi for 5.44 min. The estimated left ventricle (LV) counts were compared with the available literature on a state-of-the-art system (DSPECT). FWHM of the LV wall on MPH-OSEM-reconstructed images with collimator resolution recovery was estimated. RESULTS: On acquired rod-sources, the average resolution (FWHM) after reconstruction with resolution recovery in the entire region of interest (ROI) for cardiac imaging was on the average 4.44 mm (±2.84), compared to 6.9 mm (±1 mm) reported for GE Discovery (Kennedy et al., J Nucl Cardiol. 2014:21:443-452). For NCAT studies, improved sensitivity allowed a full-dose (25 mCi) 2-min acquisition (Ell8.68mmFD) which yielded 3.79 M LV counts. This is ~3.35 times higher compared to 1.13 M LV counts acquired in 2 min for clinical full dose for state-of-the-art DSPECT. The increased sensitivity also allowed an ultra-low dose acquisition protocol (Ell8.68 mmULD), 3 mCi (eight times less injected dose) in 5.44 min. This ultra-low dose protocol yielded ~1.23 M LV counts which was comparable to the full-dose 2-min acquisition for DSPECT. The estimated NCAT average FWHM at the LV wall after 12 iterations of the OSEM reconstruction was 4.95 and 5.66 mm around the mid-short-axis slices for Ell8.68mmFD and Ell8.68mmULD, respectively. CONCLUSION: Our Monte-Carlo simulation studies and reconstruction suggest using (inverted wineglass sized) hemi-ellipsoid detectors with pinhole collimators can increase the sensitivity ~3.35 times over the new generation of dedicated cardiac SPECT systems, while also improving the reconstructed resolution for rod-sources with an average of 4.44 mm in region of interest. The extra sensitivity may be used for ultra-low dose imaging (3 mCi) at ~5.44 min for comparable clinical counts as state-of-the-art systems.

Simulations of a Multi-Pinhole SPECT Collimator for Clinical Dopamine Transporter (DAT) Imaging.

SPECT imaging of the dopamine transporter (DAT) is used for diagnosis and monitoring progression of Parkinson's Disease (PD), and differentiation of PD from other neurological disorders. The diagnosis is based on the DAT binding in the caudate and putamen structures in the striatum. We previously proposed a relatively inexpensive method to improve the detection and quantification of these structures for dual-head SPECT by replacing one of the fan-beam collimators with a specially designed multi-pinhole (MPH) collimator. In this work, we developed a realistic model of the proposed MPH system using the GATE simulation package and verified the geometry with an analytic simulator. Point source projections from these simulations closely matched confirming the accuracy of the pinhole geometries. The reconstruction of a hot-rod phantom showed that 4.8 mm resolution is achievable. The reconstructions of the XCAT brain phantom showed clear separation of the putamen and caudate, which is expected to improve the quantification of DAT imaging and PD diagnosis. Using this GATE model, point spread functions modeling physical factors will be generated for use in reconstruction. Also, further improvements in geometry are being investigated to increase the sensitivity of this base system while maintaining a target spatial resolution of 4.5-5 mm.

Design of a Multi-Pinhole Collimator for I-123 DaTscan Imaging on Dual-Headed SPECT Systems in Combination with a Fan-Beam Collimator.

For the 2011 FDA approved Parkinson's Disease (PD) SPECT imaging agent I-123 labeled DaTscan, the volume of interest (VOI) is the interior portion of the brain. However imaging of the occipital lobe is also required with PD for calculation of the striatal binding ratio (SBR), a parameter of significance in early diagnosis, differentiation of PD from other disorders with similar clinical presentations, and monitoring progression. Thus we propose the usage of a combination of a multi-pinhole (MPH) collimator on one head of the SPECT system and a fan-beam on the other. The MPH would be designed to provide high resolution and sensitivity for imaging of the interior portion of the brain. The fan-beam collimator would provide lower resolution but complete sampling of the brain addressing data sufficiency and allowing a volume-of-interest to be defined over the occipital lobe for calculation of SBR's. Herein we focus on the design of the MPH component of the combined system. Combined reconstruction will be addressed in a subsequent publication. An analysis of 46 clinical DaTscan studies was performed to provide information to define the VOI, and design of a MPH collimator to image this VOI. The system spatial resolution for the MPH was set to 4.7 mm, which is comparable to that of clinical PET systems, and significantly smaller than that of fan-beam collimators employed in SPECT. With this set, we compared system sensitivities for three aperture array designs, and selected the 3 × 3 array due to it being the highest of the three. The combined sensitivity of the apertures for it was similar to that of an ultra-high resolution fan-beam (LEUHRF) collimator, but smaller than that of a high-resolution fan-beam collimator (LEHRF). On the basis of these results we propose the further exploration of this design through simulations, and the development of combined MPH and fan-beam reconstruction.

Adaptation of the modified Bouc-Wen model to compensate for hysteresis in respiratory motion for the list-mode binning of cardiac SPECT and PET acquisitions: testing using MRI.

PURPOSE: Binning list-mode acquisitions as a function of a surrogate signal related to respiration has been employed to reduce the impact of respiratory motion on image quality in cardiac emission tomography (SPECT and PET). Inherent in amplitude binning is the assumption that there is a monotonic relationship between the amplitude of the surrogate signal and respiratory motion of the heart. This assumption is not valid in the presence of hysteresis when heart motion exhibits a different relationship with the surrogate during inspiration and expiration. The purpose of this study was to investigate the novel approach of using the Bouc-Wen (BW) model to provide a signal accounting for hysteresis when binning list-mode data with the goal of thereby improving motion correction. The study is based on the authors' previous observations that hysteresis between chest and abdomen markers was indicative of hysteresis between abdomen markers and the internal motion of the heart. METHODS: In 19 healthy volunteers, they determined the internal motion of the heart and diaphragm in the superior-inferior direction during free breathing using MRI navigators. A visual tracking system (vts) synchronized with MRI acquisition tracked the anterior-posterior motions of external markers placed on the chest and abdomen. These data were employed to develop and test the Bouc-Wen model by inputting the vts derived chest and abdomen motions into it and using the resulting output signals as surrogates for cardiac motion. The data of the volunteers were divided into training and testing sets. The training set was used to obtain initial values for the model parameters for all of the volunteers in the set, and for set members based on whether they were or were not classified as exhibiting hysteresis using a metric derived from the markers. These initial parameters were then employed with the testing set to estimate output signals. Pearson's linear correlation coefficient between the abdomen, chest, average of chest and abdomen markers, and Bouc-Wen derived signals versus the true internal motion of the heart from MRI was used to judge the signals match to the heart motion. RESULTS: The results show that the Bouc-Wen model generated signals demonstrated strong correlation with the heart motion. This correlation was slightly larger on average than that of the external surrogate signals derived from the abdomen marker, and average of the abdomen and chest markers, but was not statistically significantly different from them. CONCLUSIONS: The results suggest that the proposed model has the potential to be a unified framework for modeling hysteresis in respiratory motion in cardiac perfusion studies and beyond.

Use of MRI to assess the prediction of heart motion with gross body motion in myocardial perfusion imaging by stereotracking of markers on the body surface.

PURPOSE: The aim of this study is to determine using MRI in volunteers whether the rigid-body-motion (RBM) model can be approximately used to estimate the gross body-motion of the heart from that of external markers on patient's chest. Our target clinical application is to use a visual-tracking-system (VTS) which employs stereoimaging to estimate heart motion during SPECT/CT and PET∕CT myocardial perfusion imaging. METHODS: To investigate body-motion separate from the respiration the authors had the volunteers hold their breath during the acquisition of a sequence of two sets of EKG-triggered MRI sagittal slices. The first set was acquired pre-motion, and the second postmotion. The motion of the heart within each breath-hold set of slices was estimated by registration to the semiautomatic 3D segmentation of the heart region in a baseline set acquired using the Navigator technique. The motion of the heart between the pre- and postmotion sets was then determined as the difference in the individual motions in comparison to the Navigator sets. An analysis of the combined motion of the individual markers on the chest was used to obtain an estimate of the six-degree-of-freedom RBM from the VTS system. The metric for judging agreement between the motion estimated by MRI and the VTS was the average error. This was defined as the average of the magnitudes of the differences in the vector displacements of all voxels in the heart region. Studies with the Data Spectrum Anthropomorphic Phantom and "No-Motion" studies in which the volunteer did not intentionally move were used to establish a baseline for agreement. With volunteer studies a t-test was employed to determine when statistically significant differences in Average Errors occurred compared to the No-motion studies. RESULTS: For phantom acquisitions, the Average Error when the motion was just translation was 0.1 mm. With complex motions, which included a combination of rotations and translations, the Average Error increased to 3.6 mm. In the volunteers the Average Error averaged over all No-Motion acquisitions was 1.0 mm. For the case of translational motion, which might be expected to be RBM, the Average Error averaged over all volunteer studies increased to 2.6 mm, which was statistically different from the No-Motion studies. For the case of bends and twists of the torso, which would be expected to challenge the RBM model, the Average Error averaged over all such volunteer studies was 4.9 mm and was again statistically different. Investigations of motion of the arm including just bending at the elbow and leg motion resulted in Average Errors which were not statistically different from the No-Motion studies. However, when shoulder movement was included with arm motion the Average Error was near that of torso bends and twists, and statistically different. CONCLUSIONS: Use of the RBM model with VTS predictions of heart motion during reconstruction should decrease the extent of artifacts for the types of patient motion studied. The impact of correction would be less for torso bends and twists, and arm motion which includes the shoulders.